The sharing economy and the future of movement in smart, human-scale cities

("Visionary City" by William Robinson Leigh)

(William Robinson Leigh’s 1908 painting “Visionary City” envisaged future cities constructed from mile-long buildings of hundreds of stories connected by gas-lit skyways for trams, pedestrians and horse-drawn carriages. A century later we’re starting to realise not only that developments in transport and power technology have eclipsed Leigh’s vision, but that we don’t want to live in cities constructed from buildings on this scale.)

One of the defining tensions throughout the development of cities has been between our desire for quality of life and our need to move ourselves and the things we depend on around.

The former requires space, peace, and safety in which to work, exercise, relax and socialise; the latter requires transport systems which, since the use of horsedrawn transport in medieval cities, have taken up space, created noise and pollution – and are often dangerous. Enrique Penalosa, whose mayorship of Bogota was defined by restricting the use of car transport, often refers to the tens of thousands of children killed by cars on the world’s roads every year and his astonishment that we accept this as the cost of convenient transport.

This tension will intensify rapidly in coming years. Not only are our cities growing larger and denser, but according to the analysis of city systems by Professors Geoffrey West and Louis Bettencourt of the Los Alamos National Laboratory and Professor Ian Robertson’s study of human behaviour, our interactions within them are speeding up and intensifying.

Arguably, over the last 50 years we have designed cities around large-scale buildings and transport structures that have supported – and encouraged – growth in transport and the size of urban economies and populations at the expense of some aspects of quality of life.

Whilst standards of living across the world have improved dramatically in recent decades, inequality has increased to an even greater extent; and many urbanists would agree that the character of some urban environments contributes significantly to that inequality. In response, the recent work of architects such as Jan Gehl and Kelvin Campbell, building on ideas first described by Jane Jacobs in the 1960s, has led to the development of the “human scale cities” movement with the mantra “first life, then space, then buildings”.

The challenge at the heart of this debate, though, is that the more successful we are in enabling human-scale value creation; the more demand we create for transport and movement. And unless we dramatically improve the impact of the systems that support that demand, the cities of the future could be worse, not better, places for us to live and work in.

Human scale technology creates complexity in transport

As digital technology pervades every aspect of our lives, whether in large-scale infrastructures such as road-use charging systems or through the widespread adoption of small-scale consumer technology such as smartphones and social media, we cannot afford to carry out the design of future cities without considering it; nor can we risk deploying it without concern for its affect on the quality of urban life.

Digital technologies do not just make it easier for us to communicate and share information wherever we are: those interactions create new opportunities to meet in person and to exchange goods and services; and so they create new requirements for transport. And as technologies such as 3D printing, open-source manufacturing and small-scale energy generation make it possible to carry out traditionally industrial activities at much smaller scales, some existing bulk movement patterns will be replaced by thousands of smaller, peer-to-peer interactions created by transactions in online marketplaces. We can already see the effects of this trend in the vast growth of traffic delivering goods that are purchased or exchanged online.

Estimates of the size of this “sharing economy“, defined by Wikipedia as “economic and social systems that enable shared access to goods, services, data and talent“, vary widely, but are certainly significant. The UK Economist magazine reports one estimate that it is a $26 billion economy already, whilst 2 Degrees Network report that just one aspect of it – small-scale energy generation – could save UK businesses £33 billion annually by 2030Air B’n’B – a peer-to-peer accommodation service – reported recently that they had contributed $632 million in value to New York’s economy in 2012 by enabling nearly 5,000 residents to earn an average of $7,500 by renting their spare rooms to travellers; and as a consequence of those travellers additionally spending an average of $880 in the city during their stay. The emergence in general of the internet as a platform for enabling sales, marketing and logistics for small and micro-businesses is partly responsible for a significant rise in self-employment and “micro-entrepreneurial” enterprises over the last few years, which now account for 14% of the US economy.

Digital technology will create not just great growth in our desire to travel and move things, but great complexity in the way we will do so. Today’s transport technologies are not only too inefficient to scale to our future needs; they’re not sophisticated and flexible enough to cope with the complexity and variety of demand.

Many of the future components of transport systems have already been envisaged, and deployed in early schemes: elevated cycleways; conveyor belts for freight; self-driving vehicles and convoys; and underground pneumatic networks for recycling. And to some extent, we have visualised the cities that they will create: Professor Miles Tight, for example, has considered the future living scenarios that might emerge from various evolutions of transport policy and human behavioural choices in the Visions 2030 project.

The task for the Smarter Cities movement should be to extend this thinking to envision the future of cities that are also shaped by emerging trends in digital technology and their effect on the wider economy and social systems. We won’t do that successfully by considering these subjects separately or in the abstract; we need to envision how they will collectively enable us to live and work from the smallest domestic scale to the largest city system.

(Packages from Amazon delivered to Google’s San Francisco office. Photo by moppet65535)

What we’ll do in the home of the future

Rather than purchasing and owning goods such as kitchen utensils, hobby and craft items, toys and simple house and garden equipment, we will create them on-demand using small-scale and open-source manufacturing technology and smart-materials. It will even be possible – though not all of us will choose to do so – to manufacture some food in this way.

Conversely, there will still be demand for handmade artisan products including clothing, gifts, jewellery, home decorations, furniture, and food. Many of us will earn a living producing these goods in the home while selling and marketing them locally or through online channels.

So we will leave our home of the future less often to visit shops; but will need not just better transport services to deliver the goods we purchase online to our doorsteps, but also a new utility to deliver the raw materials from which we will manufacture them ourselves; and new transport services to collect the products of our home industries and to deliver supplies to them.

We will produce an increasing amount of energy at home; whether from existing technologies such as solar panels or combined heat and power (CHP) systems; or through new techniques such as bio-energy. The relationships between households, businesses, utilities and transportation will change as we become producers of energy and consumers of waste material.

And whilst remote working means we will continue to be less likely to travel to and from the same office each day, the increasing pace of economic activity means that we will be more likely to need to travel to many new destinations as it becomes necessary to meet face to face with the great variety of customers, suppliers, co-workers and business partners with whom online technologies connect us.

What we’ll do in the neighbourhoods of the future

As we increasingly work remotely from within our homes or by travelling far away from them, less of us work in jobs and for businesses that are physically located within the communities in which we live; and some of the economic ties that have bound those communities in the past have weakened. But most of us still feel strong ties to the places we live in; whether they are historical, created by the character of our homes or their surrounding environment, or by the culture and people around us. These ties create a shared incentive to invest in our community.

Perhaps the greatest potential of social media that we’re only begin to exploit is its power to create more vibrant, sustainable and resilient local communities through the “sharing economy”.

The motivations and ethics of organisations participating in the sharing economy vary widely – some are aggressively commercial, whilst others are “social enterprises” with a commitment to reinvest profits in social growth. The social enterprise sector, comprised of mutuals, co-operatives, employee-owned businesses and enterprises who submit to “triple bottom line” accounting of financial, social and environmental capital, is about 15% of the value of most economies, and has been growing and creating jobs faster than traditional business since the 2008 crash. There is enormous potential for cities to achieve their “Smarter” objectives for sustainable, equitably distributed economic growth through contributions from social enterprises using technology to implement sharing economy business models within their region.

Sharing economy models which enable transactions between participants within a walkable or cyclable area can be a particularly efficient mechanism for collaboration, as the related transport can be carried out using human power. Joan Clos, Exective Director of UN-Habitat, has asserted that cities will only become sustainable when they are built at a sufficient population density that a majority of interactions within them can be carried out in this way (as reported informally by Tim Stonor from Dr. Clos’s remarks at the “Urban Planning for City Leaders” conference at the Crystal, London in 2012).

The Community Lovers’ Guide has published stories from across Europe of people who have collaborated to make the places that they share better, often using technology; and schemes such as Casserole Club and Land Share are linking the supply and demand of land, food, gardening and cooking skills within local communities, helping neighbours to help each other. At local, national and international levels, sharing economy ideas are creating previously unrealised social and economic value, including access to employment opportunities that replace some of those traditional professions that are shrinking as the technology used by industrial business changes.

Revenue-earning businesses are a necessary component of vibrant communities, at a local neighbourhood scale as well as city-wide. At the Academy of Urbanism Congress in Bradford this year, Michael Ward, Chair of the Centre for Local Economic Strategies, asserted that “the key task facing civic leaders in the 21st Century is this: how, in a period of profound and continuing economic changes, will our citizens earn a living and prosper?”

(“Makers” at the Old Print Works in Balsall Heath, Birmingham, sharing the tools, skills and ideas that create successful small businesses)

So whilst we work remotely from direct colleagues, we may chose to work in a collaborative workspace with near neighbours, with whom we can exchange ideas, make new contacts and start new enterprises and ventures. As the “maker” economy emerges from the development of sophisticated, small-scale manufacturing, and the resurgence in interest in artisan products, community projects such as the Old Print Works in Balsall Heath, Birmingham are emerging in low-cost ex-industrial space as people come together to share the tools and expertise required to make things and run businesses.

We will also manage and share our use of resources such as energy and water at neighbourhood scale. The scale and economics of movement of the raw materials for bio-energy generation, for example, currently dictate that neighbourhood-scale generation facilities – as opposed to city-wide, regional or domestic scale – are the most efficient. Aston University’s European Bio-Energy Research Institute is demonstrating these principles in the Aston district of Birmingham. And schemes from the sustainability pilot in Dubuque, Iowa to the Energy Sharing Co-operative in the West Midlands of the UK and the Chale community project on the Isle of Wight have shown that community-scale schemes can create shared incentives to use resources more efficiently.

One traditional centre of urban communities, the retail high street or main street, has fared badly in recent times. The shift to e-commerce, supermarkets and out-of-town shopping parks has led to many of them loosing footfall and trade, and seeing “payday lenders“, betting shops and charity shops take the place of traditional retailers.

High streets needs to be freed from the planning, policy and tax restrictions that are preventing their recovery. The retail-dominated highstreet of the 20th century emerged from a particular and temporary period in the evolution of the private car as the predominant form of transport supporting household-scale economic transactions. Developments in digital and transport technology as well as economy and society have made it non-viable in its current form; but legislation that prevents change in the use of highstreet property, and that keeps business taxes artificially high, is preventing highstreets from adapting in order to benefit from technology and the opportunities of the sharing economy.

Business Improvement Districts, already emerging in the UK and US to replace some local authority services, offer one way forward. They need to be given more freedom to allow the districts they manage to develop as best meets the economic and social needs of their area according to the future, not the past. And they need to become bolder: to invest in the same advanced technology to maximize footfall and spend from their customers as shopping malls do on behalf of their tenants, as recommended by a recent report to UK Government on the future of the high street.

The future high street will not be a street of clothes shops, bookshops and banks: some of those will still exist, but the high street will also be a place for collaborative workers; for makers; for sharing and exchanging; for local food produce and artisan goods; for socialising; and for starting new businesses. We will use social media to share our time and our resources in the sharing economy; and will meet on the high street when those transactions require the exchange of physical goods and services. We will walk and cycle to local shops and transport centres to collect and deliver packages for ourselves, or for our neighbours.

The future of work, life and transport at city-scale

Whilst there’s no universally agreed definition, an urban areas is generally agreed to be a continuously built-up area with a total population of between 2,000 and 40 million people; living at a density of around 1,000 per square kilometre; and employed primarily in non-agricultural activities (the appendices to the 2007 revision of the UN World Urbanisation Prospects summarise such criteria from around the world; 38.7 million is estimated to be the population of the world’s largest city, Tokyo, in 2025 by the UN World Urbanisation Prospects 2011).

(An analysis based on GPS data from mobile phones of end-to-end journeys undertaken by users of Abidjan’s bus services. By comparing existing bus routes to end-to-end journey requirements, the analysis identified four new bus routes and led to changes in many others. As a result, 22 routes now show increased ridership, and city-wide journey times have decreased by 10%.)

That is living at an industrial scale. The sharing economy may be a tremendously powerful force, but – at least for the foreseeable future – it will not scale to completely replace the supply chains that support the needs of such enormous and dense populations.

Take food, for example. One hectare of highly fertile, intensively farmed land can feed 10 people. Birmingham, my home city, has an area of 60,000 hectares of relatively infertile land, most of which is not available for farming at all; and a population of around 1 million. Those numbers don’t add up to food self-sufficiency; and Birmingham is a very low-density city – between one-half and one-tenth as dense as the growing megacities of Asia and South America.

Until techniques such as vertical farming and laboratory-grown food become both technically and economically viable, and culturally acceptable – if they ever do – cities will not feed themselves. And these techniques hardly represent locally-grown food exchanged between peers – they are highly technical and likely to operate initially at industrial scale. Sharing economy businesses such as Casserole Club, Kitchen Surfing, and Big Barn will change the way we distribute, process and prepare food within cities, but many of the raw materials will continue to be grown and delivered to cities through the existing industrial-scale distribution networks that import them from agricultural regions.

We are drawn to cities for the opportunities they offer: for work, for entertainment, and to socialise. As rapidly as technology has improved our ability to carry out all of those activities online, the world’s population is still increasingly moving to cities. In many ways, technology augments the way we carry out those activities in the real world and in cities, rather than replacing them with online equivalents.

Technology has already made cultural events in the real world more frequent, accessible and varied. Before digital technology, the live music industry depended on mass-marketing and mass-appeal to create huge stadium-selling tours for a relatively small number of professional musicians; and local circuits were dominated by the less successful but similar-sounding acts for which sufficiently large audiences could be reached using the media of the time. I attempted as an amateur musician in the pre-internet 1990s to find a paying audience for the niche music I enjoyed making: I was not successful. Today, social media can be used to identify and aggregate demand to make possible a variety of events and artforms that would never previously have reached an audience. Culture in the real-world is everywhere, all the time, as a result, and life is the richer for it. We discover much of it online, but often experience it in the real world.

(Birmingham’s annual “Zombie Walk” which uses social media to engage volunteers raising money for charity. Photo by Clare Lovell).

Flashmobs” use smartphones and social media to spontaneously bring large numbers of people together in urban spaces to celebrate; socialise or protest; and while we will play and tell stories in immersive 3D worlds in the future – whether we call them movies, interactive fiction or “massive multi-player online role-playing games” – we’ll increasingly do so in the physical world too, in “mixed reality” games. Technologies such as Google Glasscognitive computing and Brain/Computer Interfaces will accelerate these trends as they remove the barrier between the physical world and information systems.

We will continue to come to city centres to experience those things that they uniquely combine: the joy and excitement of being amongst large numbers of people; the opportunity to share ideas; access to leading-edge technologies that are only economically feasible at city-scale; great architecture, culture and events; the opportunity to shop, eat, drink and be entertained with friends. All of these things are possible anywhere; but it is only in cities that they exist together, all the time.

The challenge for city-scale living will be to support the growing need to transport goods and people into, out of and around urban areas in a way that is efficient and productive, and that minimises impact on the liveability of the urban environment. In part this will involve reducing the impact of existing modes of transport by switching to electric or hydrogen power for vehicles; by predicting and optimising the behaviour of traffic systems to prevent congestion; by optimising public transport as IBM have helped AbidjanDublin, Dubuque and Istanbul to do; and by improving the spatial organisation of transport through initiatives such as Arup’s Regent Street delivery hub.

We will also need new, evolved or rejuvenated forms of transport. In his lecture for the Centenary of the International Federation for Housing and Planning, Sir Peter Hall spoke eloquently of the benefits of Bus Rapid Transit systems, urban railways and trams. All can combine the speed and efficiency of rail for bringing goods and people into cities quickly from outlying regions, with the ability to stop frequently at the many places in cities which are the starting and finishing points of end-to-end journeys.

Vehicle journeys on major roads will be undertaken in the near future by automated convoys travelling safely at a combined speed and density beyond the capability of human drivers. Eventually the majority of journeys on all roads will be carried out by such autonomous vehicles. Whilst it is important that these technologies are developed and introduced in a way that emphasises safety, the majority of us already trust our lives to automated control systems in our cars – every time we use an anti-lock braking system, for example. We will still drive cars for fun, pleasure and sport in the future – but we will probably pay dearly for the privilege; and our personal transport may more closely resemble the rapid transit pods that can already be seen at Heathrow Terminal 5.

Proposals intended to accelerate the adoption of autonomous vehicles include the “Qwik lane” elevated highway for convoy traffic; or the “bi-modal glideway” and “tracked electric vehicle” systems which could allow cars and lorries to travel at great speed safely along railway networks or dedicated “tracked” roads. Alternative possibilities which could achieve similar levels of efficiency and throughput are to extend the use of conveyor belt technology – already recognised as far more efficient than lorries for transporting resources and goods over distances of tens of miles in quarries and factories – to bring freight in and out of cities; or to use pneumatically powered underground tunnel networks, which are already being used in early schemes for transporting recyclable waste in densely populated areas. Elon Musk, the inventor of the Tesla electric supercar, has even suggested that a similar underground “vacuum loop” could be used to replace long-distance train and air travel for humans, at speeds over 1000 kilometres per hour.

The majority of these transport systems won’t offer us as individuals the same autonomy and directness in our travel as we believe the private car offers us today – even though that autonomy is often severely restricted by traffic congestion and delays. Why will we chose to relinquish that control?

(Optimod's vision for integrated, predictive mobile, multi-modal transport information)

(Optimod‘s vision for integrated, predictive mobile, multi-modal transport information)

Some of us will simply prefer to, finding different value in other ways to get around.

Walking and cycling are gaining in popularity over driving in many cities. I’ve personally found it a revelation in recent years to walk around cities rather than drive around them as I might previously have done. Cities are interesting and exciting places, and walking is often an enjoyable as well as efficient way of moving about them. (And for urbanists, of course, walking offers unparalleled opportunities to understand cities). Many of us are also increasingly conscious of the health benefits of walking and cycling, particularly as recent studies in the UK and US have shown that adults today will be the first generation in recorded history to die younger than their parents because of our poor diets and sedentary lifestyles.

Alternatively, we may choose to travel by public transport in the interests of productivity – reading or working while we travel, especially as network coverage for telephony and the internet improves. As the world’s population and economies grow, competition and the need to improve productivity will lead more and more of us to this take this choice.

It is increasingly easy to walk, cycle, or use public or shared transport to travel into and around cities thanks to the availability of bicycle hire schemes, car clubs and walking route information services such as walkit.com. The emergence of services that provide instant access to travel information across all forms of transport – such as the Moovel service in Germany or the Optimod service in Lyon, France – will enhance this usability, making it easier to combine different forms of transport into a single journey, and to react to delays and changes in plans whilst en route.

Legislation will also drive changes in behaviour, from national and international initiatives such as the European Union legislation limiting carbon emissions of cars to local planning and transport policies – such as Birmingham’s recent Mobility Action Plan which announced a consultation to consider closing the city’s famous system of road tunnels.

(Protesters at Occupy Wallstreet using digital technology to coordinate their demonstration. Photo by David Shankbone)

Are we ready for the triumph of the digital city?

Regardless of the amazing advances we’re making in online technology, life is physical. Across the world we are drawn to cities for opportunity; for life-support; to meet, work and live.  The ways in which we interact and transport ourselves and the goods we exchange have changed out of all recognition throughout history, and will continue to do so. The ever increasing level of urbanisation of the world’s population demonstrates that there’s no sign yet that those changes will make cities redundant: far from it, they are thriving.

It is not possible to understand the impact on our lives of new ideas in transport, technology or cities in isolation. Unless we consider them together and in the context of changing lifestyles, working patterns and economics, we won’t design and build cities of the future to be resilient, sustainable, and equitable.  The limitation of our success in doing that in the past is illustrated by the difference in life expectancy of 20 years between the richest and poorest areas of UK cities; the limitation of our success in doing so today is illustrated by the fact that a huge proportion of the world’s population does not have access to the digital technologies that are changing our world.

I recently read the masterplan for a European city district regarded as a good example of Smart City thinking. It contained many examples of the clever and careful design of physical space for living and for today’s forms of transport, but did not refer at all to the changes in patterns of work, life and movement being driven by digital technology. It was certainly a dramatic improvement over some plans of the past; but it was not everything that a plan for the future needs to be. 

Across domains such as digital technology, urban design, public policy, low carbon engineering, economic development and transport we have great ideas for addressing the challenges that urbanisation, population growth, resource constraints and climate change will bring; but a lot of work to do in bringing them together to create good designs for the liveable cities of the future.

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Can Smarter City technology measure and improve our quality of life?

(Photo of Golden Gate Bridge, San Francisco, at night by David Yu)

Can information and technology measure and improve the quality of life in cities?

That seems a pretty fundamental question for the Smarter Cities movement to address. There is little point in us expending time and money on the application of technology to city systems unless we can answer it positively. It’s a question that I had the opportunity to explore with technologists and urbanists from around the world last week at the Urban Systems Collaborative meeting in London, on whose blog this article will also appear.

Before thinking about how we might approach such a challenging and complex issue, I’d like to use two examples to support my belief that we will eventually conclude that “yes, information and technology can improve the quality of life in cities.”

The first example, which came to my attention through Colin Harrison, who heads up the Urban Systems Collaborative, concerns public defibrillator devices – equipment that can be used to give an electric shock to the victim of a heart attack to restart their heart. Defibrillators are positioned in many public buildings and spaces. But who knows where they are and how to use them in the event that someone nearby suffers a heart attack?

To answer those questions, many cities now publish open data lists of the locations of publically-accessible Defibrillators. Consequently, SmartPhone apps now exist that can tell you where the nearest one to you is located. As cities begin to integrate these technologies with databases of qualified first-aiders and formal emergency response systems, it becomes more feasible that when someone suffers a heart attack in a public place, a nearby first-aider might be notified of the incidence and of the location of a nearby defibrillator, and be able to respond valuable minutes before the arrival of emergency services. So in this case, information and technology can increase the chancees of heart attack victims recovering.

(Why Smarter Cities matter: "Lives on the Line" by James Cheshire at UCL's Centre for Advanced Spatial Analysis, showing the variation in life expectancy and correlation to child poverty in London. From Cheshire, J. 2012. Lives on the Line: Mapping Life Expectancy Along the London Tube Network. Environment and Planning A. 44 (7). Doi: 10.1068/a45341)

(Why Smarter Cities matter: “Lives on the Line” by James Cheshire at UCL’s Centre for Advanced Spatial Analysis, showing the variation in life expectancy across London. From Cheshire, J. 2012. Lives on the Line: Mapping Life Expectancy Along the London Tube Network. Environment and Planning A. 44 (7). Doi: 10.1068/a45341)

In a more strategic scenario, the Centre for Advanced Spatial Analysis (CASA) at University College London have mapped life expectancy at birth across London. Life expectancy across the city varies from 75 to 96 years, and CASA’s researchers were able to correlate it with a variety of other issues such as child poverty.

Life expectancy varies by 10 or 20 years in many cities in the developed world; analysing its relationship to other economic, demographic, social and spatial information can provide insight into where money should be spent on providing services that address the issues leading to it, and that determine quality of life. The UK Technology Strategy Board cited Glasgow’s focus on this challenge as one of their reasons for investing £24 million in Glasgow’s Future Cities Demonstrator project – life expectancy at birth for male babies in Glasgow varies by 26 years between the poorest and wealthiest areas of the city.

These examples clearly show that in principle urban data and technology can contribute to improving quality of life in cities; but they don’t explain how to do so systematically across the very many aspects of quality of life and city systems, and between the great variety of urban environments and cultures throughout the world. How could we begin to do that?

Deconstructing “quality of life”

We must first think more clearly about what we mean by “quality of life”. There are many needs, values and outcomes that contribute to quality of life and its perception. Maslow’s “Hierarchy of Needs” is a well-researched framework for considering them. We can use this as a tool for considering whether urban data can inform us about, and help us to change, the ability of a city to create quality of life for its inhabitants.

(Maslow’s Hierarchy of Needs, image by Factoryjoe via Wikimedia Commons)

But whilst Maslow’s hierarchy tells us about the various aspects that comprise the overall quality of life, it only tells us about our relationship with them in a very general sense. Our perception of quality of life, and what creates it for us, is highly variable and depends on (at least) some of the following factors:

  • Individual lifestyle preferences
  • Age
  • Culture and ethnicity
  • Social standing
  • Family status
  • Sexuality
  • Gender
  • … and so on.

Any analysis of the relationship between quality of life, urban data and technology must take this variability into account; either by allowing for it in the analytic approach; or by enabling individuals and communities to customise the use of data to their specific needs and context.

Stress and Adaptability

Two qualities of urban systems and life within them that can help us to understand how urban data of different forms might relate to Maslow’s hierarchy of needs and individual perspectives on it are stress and adaptability.

Jurij Paraszczak, IBM’s Director of Research for Smarter Cities, suggested that one way to improve quality of life is to reduce stress. A city with efficient, well integrated services – such as transport; availability of business permits etc. – will likely cause less stress, and offer a higher quality of life, than a city whose services are disjointed and inefficient.

One cause of stress is the need to change. The Physicist Geoffrey West is one of many scientists who has explored the roles of technology and population growth in speeding up city systems; as our world changes more and more quickly, our cities will need to become more agile and adaptable – technologists, town planners and economists all seem to agree on this point.

The architect Kelvin Campbell has explored how urban environments can support adaptability by enabling actors within them to innovate with the resources available to them (streets, buildings, spaces, technology) in response to changes in local and global context – changes in the economy of cultural trends, for example.

Service scientists” analyse the adaptability of systems (such as cities) by considering the “affordances” they offer to actors within them. An “affordance” is a capability within a system that is not exercised until an actor chooses to exercise it in order to create value that is specific to them, and specific to the time, place and context within which they act.

An “affordance” might be the ability to start a temporary business or “pop-up” shop within a disused building by exploiting a temporary exemption from planning controls. Or it might be the ability to access open city data and use it as the basis of new information-based business services. (I explored some ideas from science, technology, economics and urbanism for creating adaptability in cities in an article in March this year).

(Photo by lecercle of a girl in Mumbai doing her homework on whatever flat surface she could find. Her use of a stationary tool usually employed for physical mobility to enhance her own social mobility is an example of the very basic capacity we all have to use the resources available to us in innovative ways)

Stress and adaptability are linked. The more personal effort that city residents must exert in order to adapt to changing circumstances (i.e. the less that a city offers them useful affordances), then the more stress they will be subjected to.

Stress; rates of change; levels of effort and cost exerted on various activities: these are all things that can be measured.

Urban data and quality of life in the district high street

In order to explore these ideas in more depth, our discussion at the Urban Systems Collaborative meeting explored a specific scenario systematically. We considered a number of candidate scenarios – from a vast city such as New York, with a vibrant economy but affected by issues such as flood risk; through urban parks and property developments down to the scale of an individual building such as a school or hospital.

We chose to start with a scenario in the middle of that scale range that is the subject of particularly intense debate in economics, policy and urban design: a mixed-demographic city district with a retail centre at its heart spatially, socially and economically.

We imagined a district with a population of around 50,000 to 100,000 people within a larger urban area; with an economy including the retail, service and manufacturing sectors. The retail centre is surviving with some new businesses starting; but also with some vacant property; and with a mixture of national chains, independent specialist stores, pawnshops, cafes, payday lenders, pubs and betting shops. We imagined that local housing stock would support many levels of wealth from benefits-dependent individuals and families through to millionaire business owners. A district similar to Kings Heath in Birmingham, where I live, and whose retail economy was recently the subject of an article in the Economist magazine.

We asked ourselves what data might be available in such an environment; and how it might offer insight into the elements of Maslow’s hierarchy.

We began by considering the first level of Maslow’s hierarchy, our physiological needs; and in particular the availability of food. Clearly, food is a basic survival need; but the availability of food of different types – and our individual and cultural propensity to consume them – also contributes to wider issues of health and wellbeing.

(York Road, Kings Heath, in the 2009 Kings Heath Festival. Photo by Nick Lockey)

Information about food provision, consumption and processing can also give insights into economic and social issues. For example, the Economist reported in 2011 that since the 2008 financial crash, some jobs lost in professional service industries such as finance in the UK had been replaced by jobs created in independent artisan industries such as food. Evidence of growth in independent businesses in artisan and craft-related sectors in a city area may therefore indicate the early stages of its recovery from economic shock.

Similarly, when a significant wave of immigration from a new cultural or ethnic group takes place in an area, then it tends to result in the creation of new, independent food businesses catering to preferences that aren’t met by existing providers. So a measure of diversity in food supply can be an indicator of economic and social growth.

So by considering a need that Maslow’s hierarchy places at the most basic level, we were able to identify data that describes an urban area’s ability to support that need – for example, the “Enjoy Kings Heath” website provides information about local food businesses; and furthermore, we identified ways that the same data related to needs throughout the other levels of Maslow’s hierarchy.

We next considered how economic flows within and outside an area can indicate not just local levels of economic activity; but also the area’s trading surplus or deficit. Relevant information in principle exists in the form of the accounts and business reports of businesses. Initiatives such as local currencies and loyalty schemes attempt to maximise local synergies by minimising the flow of money out of local economies; and where they exploit technology platforms such as Droplet’s SmartPhone payments service, which operates in London and Birmingham, the money flows within local economies can be measured.

These money flows have effects that go beyond the simple value of assets and property within an area. Peckham high street in London has unusually high levels of money flow in and out of its economy due to a high degree of import / export businesses; and to local residents transferring money to relatives overseas. This flow of money makes business rents in the area disproportionally high  compared to the value of local assets.

Our debate also touched on environmental quality and transport. Data about environmental quality is increasingly available from sensors that measure water and air quality and the performance of sewage systems. These clearly contribute insights that are relevant to public health. Transport data provides perhaps more subtle insights. It can provide insight into economic activity; productivity (traffic jams waste time); environmental impact; and social mobility.

My colleagues in IBM Research have recently used anonymised data from GPS sensors in SmartPhones to analyse movement patterns in cities such as Abidjan and Istanbul on behalf of their governments and transport authorities; and to compare those movement patterns with public transport services such as bus routes. When such data is used to alter public transport services so that they better match the end-to-end journey requirements of citizens, an enormous range of individual, social, environmental and economic benefits are realised.

(The origins and destinations of end-to-end journeys made in Abidjan, identified from anonymised SmartPhone GPS data)

(The origins and destinations of end-to-end journeys made in Abidjan, identified from anonymised SmartPhone GPS data)

Finally, we considered data sources and aspects of quality of life relating to what Maslow called “self-actualisation”: the ability of people within the urban environment of our scenario to create lifestyles and careers that are individually fulfilling and that reward creative self-expression. Whilst not direct, measurements of the registration of patents, or of the formation and survival of businesses in sectors such as construction, technology, arts and artisan crafts, relate to those values in some way.

In summary, the exercise showed that a great variety of data is available that relates to the ability of an urban environment to provide Maslow’s hierarchy of needs to people within it. To gain a fuller picture, of course, we would need to repeat the exercise with many other urban contexts at every scale from a single building up to the national, international and geographic context within which the city exists. But this seems a positive start.

Recognising the challenge

Of course, it is far from straightforward to convert these basic ideas and observations into usable techniques for deriving insight and value concerning quality of life from urban data.

What about the things that are extremely hard to measure but which are often vital to quality of life – for example the cash economy? Physical cash is notoriously hard to trace and monitor; and arguably it is particularly important to the lives of many individuals and communities who have the most significant quality of life challenges; and to those who are responsible for some of the activities that detract from quality of life – burglary, mugging and the supply of narcotics, for example.

The Urban Systems Collaborative’s debate also touched briefly on the question of whether we can more directly measure the outcomes that people care about – happiness, prosperity, the ability to provide for our families, for example. Antti Poikola has written an article on his blog, “Vital signs for measuring the quality of life in cities“, based on the presentation on that topic by Samir Menon of Tata Consulting Services. Samir identified a number of “happiness indices” that have been proposed by the UK Prime Minister, David Cameron, the European Quality of Life Survey, the OECD’s Better Life Index, and the Social Progress Index created by economist Michael Porter. Those indices generally attempt to correlate a number of different quantitative indicators with qualitative information from surveys into an overall score. Their accuracy and usefulness is the subject of contentious debate.

As an alternative, Michael Mezey of the Royal Society for the Arts recently collected descriptions of attempts to measure happiness more directly by identifying the location of issues or events associated with positive or negative emotions – such as parks and pavements fouled by dog litter or displays of emotion in public. It’s fair to say that the results of these approaches are very subjective and selective so far, but it will be interesting to observe what progress is made.

There is also a need to balance our efforts between creating value from the data that is available to us – which is surely a resource that we should exploit – with making sure that we focus our efforts on addressing our most important challenges, whether or not data relevant to them is easily accessible.

And in practise, a great deal of the data that describes cities is still not very accessible or useful. Most of it exists within IT systems that were designed for a specific purpose – for example, to allow building owners to manage the maintenance of their property. Those systems may not be very good at providing data in a way that is useful for new purposes – for example, identifying whether a door is connected to a pavement by a ramp or by steps, and hence how easy it is for a wheelchair user to enter a building.

(Photo by Closed 24/7 of the Jaguar XF whose designers used “big data” analytics to optimise the emotional response of potential customers and drivers)

Generally speaking, transforming data that is useful for a specific purpose into data that is generally useful takes time, effort and expertise – and costs money. We may desire city data to be tidied up and made more readily accessible; just as we may desire a disused factory to be converted into useful premises for shops and small businesses. But securing the investment required to do so is often difficult – this is why open city data is a “brownfield regeneration” challenge for the information age.

We don’t yet have a general model for addressing that challenge, because the socio-economic model for urban data has not been defined. Who owns it? What does it cost to create? What uses of it are acceptable? When is it proper to profit from data?

Whilst in principle the data available to us, and our ability to derive insight and knowledge from it, will continue to grow, our ability to benefit from it in practise will be determined by these crucial ethical, legal and economic issues.

There are also more technical challenges. As any mathematician or scientist in a numerate discipline knows, data, information and analysis models have significant limitations.

Any measurement has an inherent uncertainty. Location information derived from Smartphones is usually accurate to within a few meters when GPS services are available, for example; but only to within a few hundred meters when derived by triangulation between mobile transmission masts. That level of inaccuracy is tolerable if you want to know which city you are in; but not if you need to know where the nearest defibrilator is.

These limitations arise both from the practical limitations of measurement technology; and from fundamental scientific principles that determine the performance of measurement techniques.

We live in a “warm” world – roughly 300 degrees Celsius above what scientists call “absolute zero“, the coldest temperature possible. Warmth is created by heat energy; that energy makes the atoms from which we and our world are made “jiggle about” – to move randomly. When we touch a hot object and feel pain it is because this movement is too violent to bear – it’s like being pricked by billions of tiny pins. This random movement creates “noise” in every physical system, like the static we hear in analogue radio stations or on poor quality telephone lines.

And if we attempt to measure the movements of the individual atoms that make up that noise, we enter the strange world of quantum mechanics in which Heisenberg’s Uncertainty Principle states that the act of measuring such small objects changes them in unpredictable ways. It’s hardly a precise analogy, but imagine trying to measure how hard the surface of a jelly is by hitting it with a hammer. You’d get an idea of the jelly’s hardness by doing so, but after the act of “measurement” you wouldn’t be left with the same jelly. And before the measurement you wouldn’t be able to predict the shape of the jelly afterwards.

(A graph from my PhD thesis showing experimental data plotted against the predictions of an analytic. Notice that whilst the theoretical prediction (the smooth line) is a good guide to the experimental data, that each actual data point lies above or below the line, not on it. In addition, each data point has a vertical bar expressing the level of uncertainty involved in its measurement. In most circumstances, data is uncertain and theory is only a rough guide to reality.)

Even if our measurements were perfect, our ability to understand what they are telling us is not. We draw insight into the behaviour of a real system by comparing measurements of it to a theoretical model of its behaviour. Weather forecasters predict the weather by comparing real data about temperature, air pressure, humidity and rainfall to sophisticated models of weather systems; but, as the famous British preoccupation with talking about the weather illustrates, their predictions are frequently inaccurate. Quite simply this is because the weather system of our world is more complicated than the models that weather forecasters are able to describe using mathematics; and process using today’s computers.

This may all seem very academic; and indeed it is – these are subjects that I studied for my PhD in Physics. But all scientists, mathematicians and engineers understand them; and whether our work involves city systems, motor cars, televisions, information technology, medicine or human behaviour, when we work with data, information and analysis technology we are very much aware and respectful of their limitations.

Most real systems are more complicated than the theoretical models that we are able to construct and analyse. That is especially true of any system that includes the behaviour of people – in other words, the vast majority of city systems. Despite the best efforts of psychology, social science and artificial intelligence we still do not have an analytic model of human behaviour.

For open data and Smarter Cities to succeed, we need to openly recognise these challenges. Data and technology can add immense value to city systems – for instance, IBM’s “Deep Thunder” technology creates impressively accurate short-term and short-range predictions of weather-related events such as flash-flooding that have the potential to save lives. But those predictions, and any other result of data-based analysis, have limitations; and are associated with caveats and constraints.

It is only by considering the capabilities and limitations of such techniques together that we can make good decisions about how to use them – for example, whether to trust our lives to the automated analytics and control systems involved in anti-lock braking systems, as the vast majority of us do every time we travel by road; or whether to use data and technology only to provide input into a human process of consideration and decision-making – as takes place in Rio when city agency staff consider Deep Thunder’s predictions alongside other data and use their own experience and that of their colleagues in determining how to respond.

In current discussions of the role of technology in the future of cities, we risk creating a divide between “soft” disciplines that deal with qualitative, subjective matters – social science and the arts for example; and “hard” disciplines that deal with data and technology – such as science, engineering, mathematics.

In the most polarised debates, opinion from “soft” disciplines is that “Smart cities” is a technology-driven approach that does not take human needs and nature into account, and does not recognise the variability and uncertainty inherent in city systems; and opinion from “hard” disciplines is that operational, design and policy decisions in cities are taken without due consideration of data that can be used to inform them and predict their outcomes. As Stephan Shakespeare wrote in the “Shakespeare Review of Public Sector Information“, “To paraphrase the great retailer Sir Terry Leahy, to run an enterprise without data is like driving by night with no headlights. And yet that is what government often does.”

There is no reason why these positions cannot be reconciled. In some domains “soft” and “hard” disciplines regularly collaborate. For example, the interior and auditory design of the Jaguar XF car, first manufactured in 2008, was designed by re-creating the driving experience in a simulator at the University of Warwick, and analysing the emotional response of test subjects using physiological sensors and data. Such techniques are now routinely used in product design. And many individuals have a breadth of knowledge that extends far beyond their core profession into a variety of areas of science and the arts.

But achieving reconciliation between all of the stakeholders involved in the vastly complex domain of cities – including the people who live in them, not just the academics, professionals and politicians who study, design, engineer and govern them – will not happen by default. It will only happen if we have an open and constructive debate about the capabilities and the limitations of data, information and technology; and if we are then able to communicate them in a way that expresses to everyone why Smarter City systems will improve their quality of life.

(“Which way to go?” by Peter Roome)

What’s next?
It’s astonishing and encouraging that we could use a model of individual consciousness to navigate the availability and value of data in the massively collective context of an urban scenario. To continue developing an understanding of the ability of information and technology to contribute to quality of life within cities, we need to expand that approach to explore the other dimensions we identified that affect perceptions of quality of life: culture, age and family status, for example; and within both larger and smaller scales of city context than the “district” scenario that we started with.

And we need to compare that approach to existing research work such as the Liveable Cities research collaboration between UK Universities that is establishing an evidence-based technique for assessing wellbeing; or the IBM Research initiative “SCRIBE” which seeks to define the meaning of and relationships between the many types of data that describe cities.

As a next step, the Urban Systems Collaborative attendees suggested that it would be useful to consider how people in different circumstances in cities use data, information and technology to take decisions:  for example, city leaders, businesspeople, parents, hostel residents, commuters, hospital patients and so forth across the incredible variety of roles that we play in cities. You can find out more about how the Collaborative is taking this agenda forward on their website.

But this is not a debate that belongs only within the academic community or with technologists and scientists. Information and technology are changing the cities, society and economy that we live in and depend on. But that information results from data that in large part is created by all of our actions and activities as individuals, as we carry out our lives in cities, interacting with systems that from a technology perspective are increasingly instrumented, interconnected and intelligent. We are the ultimate stakeholders in the information economy, and we should seek to establish an equitable consensus for how our data is used; and that consensus should include an understanding and acceptance between all parties of both the capabilities and limitations of information and technology.

I’ve written before about the importance of telling stories that illustrate ways in which technology and information can change lives and communities for the better. The Community Lovers’ Guide to Birmingham is a great example of doing this. As cities such as Birmingham, Dublin and Chicago demonstrate what can be achieved by following a Smarter City agenda, I’m hoping that those involved can tell stories that will help other cities across the world to pursue these ideas themselves.

(This article summarises a discussion I chaired this week to explore the relationship between urban data, technology and quality of life at the Urban Systems Collaborative’s London workshop, organised by my ex-colleague, Colin Harrison, previously an IBM Distinguished Engineer responsible for much of our Smarter Cities strategy; and my current colleague, Jurij Paraszczak, Director of Industry Solutions and Smarter Cities for IBM ResearchI’m grateful for the contributions of all of the attendees who took part. The article also appears on the Urban Systems Collaborative’s blog).

Do we need a Pattern Language for Smarter Cities?

(Photo of the Athens Olympic Sports Complex from Space by the NASA Goddard Space Flight Center)

The UK Department of Business, Innovation and Skills held a workshop recently to determine how to create guidance for cities considering their approach to Smarter Cities.

A robust part of the debate centred on the challenge of providing “delivery guidance” for cities embarking on Smarter Cities initiatives: whilst there are many visions for smart and future cities; and many examples of projects that have been carried out; there is little prescriptive guidance to assist cities in defining and delivering their own strategy (although I’ve provided my own humble contribution in “Six steps to a smarter city” on this blog; an article which organises a broad set of resources into an admittedly very high level framework).

In setting out a transformative smarter city vision and then taking the steps to achieve it, a great deal of change is involved. Large, formal organisations tend to approach change with prescriptive , process-driven techniques – for all that the objective of change might be defined disruptively by individual insight and leadership or through the application of techniques such as “design thinking“; the execution of the changes required to achieve that objective is usually driven by a controlled process with well defined roles, scope, milestones, risks and performance indicators.

My own employer, IBM, is a vast organisation with over 400,000 employees; a similar number of people to the population of a city of modest size. It was the subject of one of the most famous transformations in corporate history when Lou Gerstner saved it from near-failure in the 1990s. The transformation was achieved by brilliant personal leadership; trial and error; and a variety of techniques and ideas from different sources – there was no “off-the-shelf” process to follow at this scale of organisational change.

But transforming a city is not the same thing as changing an organisation, however big. A city is a complex system of systems, and we have comparatively little knowledge about how to drive change in such an environment. Arguably,we should not even think about “driving change” in city ecosystems, but rather consider how to influence the speed and direction of the changes that will emerge from them anyway.

Some very different approaches to process-driven change have emerged from thinking in policy, economics, planning and architecture: the Collective Research Initiatives Trust‘s study of Mumbai, “Being Nicely Messy“; Colin Rowe and Fred Koetter’s “Collage City“; Manu Fernandez’s “Human Scale Cities” project; the “Massive / Small” concept and associated “Urban Operating System” from Kelvin Campbell and Urban Initiatives; and CHORA’s Taiwan Strait Atlas, for example have all suggested an approach that involves a “toolkit” of ideas for individuals and organisations to apply in their local context.

(In this light, it’s interesting to observe that in order to steer the ongoing growth of IBM following the transformation led by Lou Gerstner, his successor as CEO, Sam Palmisano, took the organic approach of seeking to inspire a consistent evolution of business behaviour across all 400,000 individual IBMers by co-creating and adopting a common and explicit set of “values”).

(Stories of Mumbai: an exploration of Mumbai’s history of urban development, and its prospects for the future, using storytelling and puppetshows, by the BMW Guggenheim Lab)

In “Resilience: Why Things Bounce Back“, Andrew Zolli and Ann Marie Healy, give a fascinating description of the incredible impact such approaches can achieve through the example of the response to the earthquake near Port-au-Prince in Haiti on January 10, 2010 that was led by Patrick Meier, the Ushahidi information crowd-sourcing platform and the Tufts Fletcher School of Law and Diplomacy in Massachusetts. Meier catalysed an incredible multi-national response to the earthquake that included the resources of organisations such as Thomson Reuters, Digicel (the largest mobile phone company in Haiti), and MedicMobile; and just as importantly hundreds of individuals literally spread across the world, with nothing more in common than a desire to do what they could to contribute:

“I told people, ‘We’re going to let this be emergent,’” Meier explained. “There are so many things that need to happen every single hour and so many things that need to keep evolving in such a short amount of time. I have to just let it flourish and deal with what happens when it starts getting inefficient.” The open nature of the platform – both the code that powers Ushahidi and the collaborative nature of the mapping – meant that people could easily be recruited to perform discrete, useful tasks with a minimum of formal authority.”

(Patrick Meier, quoted in “Resilience: Why Things Bounce Back“, p179, by Andrew Zolli and Ann Marie Healy)

In my own work, I’ve tried to follow a similar course, inspired first by the Knight Foundation’s report on the Information Needs of Communities. The Knight Foundation counsel a process of engagement and understanding between institutions and communities, in order to identify the specific information and resources that can be most usefully made available by city institutions to individual citizens, businesses and social organisations. As I described in “The Amazing Heart of a Smarter City: the Innovation Boundary“, the resulting portfolio provides a toolkit customised to the needs of a city, and that can be used to shape a collective case for investment in the development of that city.

The idea of a toolkit recognises both that no one approach, philosophy or framework is applicable to every city, or to every context within a single city; and that an idea that works in one place might work in many others.

For example, in the UK, the regions around the cities of Birmingham and Manchester are of similar size in terms of population and economic activity; but they are very different in the structure of their political administrations and economies. The approach that one of these cities adopts as its Smarter City strategy will not necessarily transfer to the other.

In contrast, however, specific ideas concerning economic development and the attraction of talented young people that I’ve found useful in Sunderland in the UK have been inspired by past experience in Wuxi, China and New York State; and in turn have informed initiatives in Spain, Singapore and Nairobi; in other words they have transcended contexts of vastly different size, culture and economics.

A tool that emerged from town planning in the 1970s and that was then adopted across the information technology industry in the 1980s and 1990s might just provide the approach we need to harness this information. And it’s perhaps not surprising that a tool with such provenance should become relevant at at time when the architects of information technology systems, buildings and cities are finding that they are working within a common context.

That tool is the “Design Pattern”.

A Pattern Language for Smarter Cities

(A pattern language for social software features, image by Amber Case)

The town planner Christopher Alexander invented “design patterns” in the 1970s. He addressed the challenge that many problems in planning were (and are) too large and complex for one person to consider them in their entirety at one time; and that it is hence necessary to break them down into sub-problems.

The difficulty is that it is not at all straightforward to break a problem into sub-problems that can be solved effectively in isolation from each other.

Consider city transport systems: in many cases, road management, bus operations and the rail network are the responsibility of different organisations. It “makes sense” to break up transport systems in this way because each is different; and so different organisations are better at running them effectively.

But from the perspective of the users of transport systems, it doesn’t make sense to do this. Bus and rail timetables don’t work together; cars, buses, freight vehicles, bicycles and pedestrians have conflicting requirements of road space; and the overall system does not behave as though it is designed to serve travellers consistently.

In “Notes on the Synthesis of Form” in 1969, Alexander described a mathematical technique that could be used to manage the complexity of large problems and to break them down into sub-problems in a way that accommodated interdependencies between them. As a result, those sub-problems could be solved separately from each other, then integrated to form an overall solution.

This process of decomposition, solution and integration is fundamental to process-driven approaches to the design and delivery of complex solutions. It is not possible, for example, to assign responsibilities to individuals and teams without going through it. Many projects that fail do so because the  problem that they are addressing is not decomposed effectively so that individual teams find that they have overlapping areas of responsibility and therefore experience duplication and conflict.

However, in developing his technique for decomposing problems, Alexander concluded that it was overly complex, rigid and impractical; and he recommended that it should never be used. Instead, he suggested that it was more useful to focus not on how we deal with problems; but on how we re-use successful solutions.

By identifying and characterising the components of solutions that have been proven to work, we enable them to be reused elsewhere. Christopher Alexander’s particular insight was to recognise that to do so successfully, it is vitally important to precisely describe the context in which a solution is applicable. He called the resulting description of reusable solutions a “design pattern”; and a collection of such descriptions, a “pattern language“.

Design patterns and pattern languages offer a useful combination of formal and informal approaches. They are formal in that each pattern is described in a consistent way, using a structured framework of characteristics. And they are informal in that the description isn’t constrained to that framework of characteristics; and because design patterns do not assert that they should be used: they are simply there to be used by anyone who chooses to do so.

Christopher Alexander’s patterns for town planning and architecture can be found in his books, or online at the “Pattern Language” community; in information technology, Martin Fowler’s “Enterprise Application Architecture Patterns” provide a similar example.

To my knowledge, no-one is yet curating a similar set of Smarter Cities patterns; I believe that there would be great value in doing so; and that in order to do so skills and expertise across domains such as planning, architecture, technology, social science and many others would be required.

In the final part of this article, I’d like to suggest some examples of Smarter City initiatives and ideas that I think can be usefully described as patterns; and to give one example of such a description. Please do share your views on whether this approach is useful by commenting on this blog, or through one of the Linked-In discussion groups where I’ve posted links to this article.

Design Patterns for Smarter Cities

Here are just a few of the ideas I’ve seen applied successfully in more than one place, either as part of a Smarter City strategy, or simply as valuable initiatives in their own right. It is certainly not an exhaustive list – a quick survey of Linked-In discussion Groups such as “Smart Cities and City 2.0“, “Smarter Cities” and “Smart Urbanism” will reveal many other examples that could be described in this way.

  • Information Partnerships – collaborations between city institutions, communities, service providers and research institutions to share and exploit city data in a socially and financially sustainable system. (I’ve provided a more detailed description of this example below).
  • Incubation Clouds – the use of Cloud Computing platforms and hybrid public/private commercial models to enable co-operative investment in technology capabilities that can lower the barriers to successful innovations in city services. Examples: Sunderland’s “City Cloud” and the Wuxi iPark.
  • Community Energy Initiatives – the formation of local energy companies to exploit “smart grid” technology, local energy generation (such as solar panels, wind power, wave power, geo-thermal power and bio-energy) and collaborative energy consumption to reduce carbon emissions and reliance on external energy sources. Examples: Eco-island and Birmingham Energy Savers.
  • Social Enterprises – a collective term for models of business that audit themselves against social and environmental outcomes, as well as financial sustainability and returns. Examples: co-operatives, credit unions and organisations using “triple-bottom-line” accounting.

(The components of a Smart City architecture I described in “The new architecture of Smart Cities“)

In order to describe these concepts more completely as re-usable patterns; and in a way that allows them to be compared, selected in comparison to each other, or used together; it is important that they are described consistently, and in a way that accurately identifies the context in which they are applicable.

To do so requires that we describe the same aspects of each pattern; and that we describe each aspect using a common language. For example:

  • The city systems, communities and infrastructures affected; using a framework such as the “The new architecture of Smart Cities” that I described last year, shown in the diagram above.
  • The commercial operating model that makes the pattern financially sustainable.
  • The driving forces that make the pattern applicable, such as traffic congestion; persistent localised economic inactivity; the availability of local energy sources; or the need to reduce public sector spending.
  • The benefits of using the pattern; including financial, social, environmental and long-term economic benefits.
  • The implications and risks of implementing the pattern – such as the risk that consumers will not chose to change their behaviour to adopt more sustainable modes of transport; or the increasing long-term costs of healthcare implied by initiatives that raise life-expectancy by creating a healthier environment.
  • The alternatives and variations that describe how the pattern can be adapted to particular local contexts.
  • Examples of where the pattern has been applied; what was involved in making it work; and the outcomes that were achieved as a result.
  • Sources of information that provide further explanation, examples of use and guidance for implementation.

I’ll finish this article by given an example of a Smarter City pattern described in that way – the “City Information Partnership”.

(Coders at work exploiting city information at the Birmingham “Smart Hack”, photographed by Sebastian Lenton)

An Example Pattern: City Information Partnership

(Note: the following description is not intended to be written in the fluent style that I usually hope to achieve in my blog articles; instead, it is meant to illustrate the value in bringing together a set of concisely expressed ideas in a structured format).

Summary of the pattern: a collaboration between city institutions, communities, service providers and research institutions to share and exploit city data in a socially and financially sustainable system.

City systems, communities and infrastructures affected:

(This description is based on the elements of Smarter City ecosystems presented in “The new Architecture of Smart Cities“).

  • Goals: Any.
  • People: Citizens; innovators.
  • Ecosystem: All.
  • Soft infrastructures: Innovation forums; networks and community organisations.
  • City systems: Any.
  • Hard infrastructures: Information and communications technology.

Commercial operating model:

City information partnerships are often incorporated as “Special Purpose Vehicles” (SPVs) jointly owned by city institutions such as local authorities; universities; other public sector organisations such as schools, healthcare providers and emergency services; services providers such as transportation authorities and utilities; asset owners and operators such as property developers and facility managers; local employers; and private sector providers such as technology companies.

A shared initial investment in technology infrastructure is often required; and in order to address legal issues such as intellectual property rights and liability agreements.

Long-term financial sustainability is dependent on the generation of commercial revenues by licensing the use of data by commercial operations. In cases where such initiatives have been supported only by public sector or research funding, that funding has eventually been reduced or terminated leading to the stagnation or cessation of the initiative.

Soft infrastructures, hard infrastructures and assets required:

Information partnerships only succeed where they are a component of a co-creative dialogue between individuals and organisations in city institutions such as entrepreneurs, community associations, local authorities and social enterprises.

Institutional support is required to provide the models of legal liability and intellectual property ownership that create a trusted and transparent context for collaborative innovation.

Technologies such as Cloud Computing platforms; information management; security; analytics, reporting; visualisation; and data catalogues are required to manage city information and make it available and useful to end users.

Information partnerships require the participation of organisations which between them own and are prepared to make available a sufficiently broad and rich collection of datasets.

Driving forces:

Information is transforming the world’s economy; it provides new insight to support business model creation and operation; makes new products and services possible; and creates new markets.

At the same time global and local demographic trends mean that the cost-base and resource usage of city systems must change.

Information partnerships expose city information to public, private, social and academic research and innovation to discover, create and operate new models for city services; with the potential for resale elsewhere; leading in turn to economic and social growth.

(A visualisation created by Daniel X O Neil of data from Chicago’s open data portal showing the activities of paid political lobbyists and their customers in the city)

Benefits:

Community hacktivism can usually be engaged by information partnerships to create useful community “apps” such as local transport information and accessibility advice.

The creation of new information-based businesses creates local employment opportunities, and economic export potential.

Information partnerships can provide information resources for technology education in schools, colleges and universities.

New city services developed as a result of the information partnership may provide lower-carbon alternatives to existing city systems such as transportation.

Implications and risks:

If participating organisations such as local authorities include the requirement to contribute data to the information partnership in procurement criteria, then tendering organisations will include any associated costs in their proposals.

For information partnerships to be sustainable, the operating entity needs to be able to accrue and reinvest profits from licenses to exploit data commercially.

The financial returns and economic growth created by information partnerships can take time to develop.

Genuinely constructive partnerships rely on effective engagement between city institutions, businesses and communities.

Existing contracts between local authorities and service providers are unlikely to require that data is contributed to the partnership; and the costs associated with making the data associated with those services available will need to be negotiated.

Alternatives and variations:

Some organisations have provided single-party open data platforms. These can be effective – for example, the APIs offered by e-Bay and Amazon; but individual organisations within cities will rarely have a critical mass of valuable data; or the resources required to operate effective and sustained programmes of engagement with the local community.

Many advocates of open data argue that such data should be freely available. However, the majority of platforms that have made data available freely have struggled to make data available in a form that is usable; to expand the data available; to offer data at a reliable level of service; or to sustain their operations over time. Making good quality data available reliably requires effort, and that effort needs to be paid for.

Examples:

Sources of information:

The UK Open Data Institute is championing open data in the UK – http://www.theodi.org/

O’Reilly Media have published many informative articles on their “Radar” website – http://search.oreilly.com/?q=open+data&x=0&y=0&tmpl=radar

The report “Information Marketplaces: The new economics of cities” published by Arup, The Climate Group, Accenture and Horizon, University of Nottingham – http://www.arup.com/Publications/Information_Marketplaces_the_new_economics_of_cities.aspx

Finally, I have written a series of articles on this blog that explore the benefits and challenges associated with the collaborative exploitation of city information:

What next?

It has been an interesting exercise for me to write this article. Many of the ideas and examples that I have included will not be new to regular readers of this blog. But in describing the idea of an “Information Partnership” as a formal design pattern I have brought them together in a particularly focussed and organised manner. There are many, many more ideas and examples of initiatives within the Smarter Cities domain that could be described in this way; and I personally believe that it would be valuable to do so.

But my opinion on that subject is less valuable than yours. I would really appreciate your thoughts on whether the “Smarter City Design Patterns” I’ve suggested and explored in this article would be a valuable contribution to our collective knowledge.

I look forward to hearing from you.

Happy Christmas, and thankyou, from the Urban Technologist

20121218-000314.jpg

(The Empire State Building as seen from Greenwich Village, New Year’s Eve 2006)

As 2012 draws to a close, I’d like to look back briefly at the first year of “The Urban Technologist”.

Whilst I first opened this WordPress account in 2008, I used it rather sporadically as a personal blog, with a loose focus on emerging technology.

But 12 months ago I decide to write in a more regular and focused way about my work in Smarter Cities. My motivation was to share that experience and to start new conversations that I could learn from.

I have spent 15 years as a technologist, identifying new trends, and delivering projects to exploit them. That has never been simple; often exciting; and always full of challenges. But in cities I have experienced over the last few years by far the most complex, subtle, beautiful, challenging and meaningful contexts for that work in my career.

It is always useful to understand one’s own strengths and limitations; and early on I realised that my amateur enthusiasm was not a sufficient basis from which to build a real understanding of cities. So I have consciously built new relationships with planners, architects, policy-makers, social enterprises, businesses and many of the other stakeholders who understand cities professionally; or who play a role in them. In the process, I have met an astonishing variety of people, all of whom taught me something; often through conversations in which they disagreed with me – or at least expanded my thinking – in interesting ways.

Social media, and in particular this blog, have given me the most incredible opportunity to extend those discussions: through comments posted on the blog itself; through discussions in the Linked-In groups I belong to; and through the wonderful conversations I have in person whenever I meet someone who’s read something I have written.

I’ve commented in many articles on this blog that new conversations between the stakeholders and communities in a city ecosystem are the key to creating the common interest and understanding needed to drive a city forward. That same principle applies to the creation of knowledge within the wider community of Smart Cities and future urbanism. I hope that by writing this blog, and by basing it on the insights discovered through the conversations I take part in, I have contributed in a small way to that community.

(The thoughtful statue floating in Barcelona's docks that I use as the header image for this blog)

(The thoughtful statue floating in Barcelona’s docks that I use as the header image for this blog)

I’ll be taking a couple of weeks off over Christmas; but I will use the break to update the “Six steps to a Smarter City” article that I maintain as a structured guide to the content on this blog.

Recent articles that I’ll add links to include the review of the decision-making, financing and governance processes that successful Smart City initiatives have followed in “Smart ideas for everyday cities” and “No-one is going to pay cities to become Smarter“; the description of the engineering and information technologies that make Smarter city systems possible in “Pens, paper, and conversations. And the other technologies that will make cities Smarter.“; and the more philosophical discussions of the organic innovation that city environments – including their information infrastructures – should support and enable in “Inspirational Simpli-city“, “Zen and the art of messy urbanism” and “Should technology improve cities, or should cities improve technology?“.

In the meantime, though, I’d like to say Happy Christmas; and also thankyou to everyone who has read this blog or commented on it; and to everyone who’s thinking has informed and inspired me. I look forward to continuing our conversation in 2013.

Why Open City Data is the Brownfield Regeneration Challenge of the Information Age

(Graphic of New York’s ethnic diversity from Eric Fischer)

I often use this blog to explore ways in which technology can add value to city systems. In this article, I’m going to dig more deeply into my own professional expertise: the engineering of the platforms that make technology reliably available.

Many cities are considering how they can create a city-wide information platform. The potential benefits are considerable: Dublin’s “Dublinked” platform, for example, has stimulated the creation of new high-technology businesses, and is used by scientific researchers to examine ways in which the city’s systems can operate more efficiently and sustainably. And the announcements today by San Francisco that they are legislating to promote open data and have appointed a “Chief Data Officer” for the city are sure to add to the momentum.

But if cities such as Dublin, San Francisco and Chicago have found such platforms so useful, why aren’t there more of them already?

To answer that question, I’d like to start by setting an expectation:

City information platforms are not “new” systems; they are a brownfield regeneration challenge for technology.

Just as urban regenerations need to take account of the existing physical infrastructures such as buildings, transport and utility networks; when thinking about new city technology solutions we need to consider the information infrastructure that is already in place.

A typical city authority has many hundreds of IT systems and applications that store and manage data about their city and region. Private sector organisations who operate services such as buses, trains and power, or who simply own and operate buildings, have similarly large and complex portfolios of applications and data.

So in every city there are thousands – probably tens of thousands – of applications and data sources containing relevant information. (The Dublinked platform was launched in October 2011 with over 3,000 data sets covering the environment, planning, water and transport, for example). Only a very small fraction of those systems will have been designed with the purpose of making information available to and usable by city stakeholders; and they certainly will not have been designed to do so in a joined-up, consistent way.

(A map of the IT systems of a typical organisation, and the interconnections between then)

The picture to the left is a reproduction of a map of the IT systems of a real organisation, and the connections between them. Each block in the diagram represents a major business application that manages data; each line represents a connection between two or more such systems. Some of these individual systems will have involved hundreds of person-years of development over decades of time. Engineering the connections between them will also have involved significant effort and expense.

Whilst most organisations improve the management of their systems over time and sometimes achieve significant simplifications, by and large this picture is typical of the vast majority of organisations today, including those that support the operation of cities.

In the rest of this article, I’ll explore some of the specific challenges for city data and open data that result from this complexity.

My intention is not to argue against bringing city information together and making it available to communities, businesses and researchers. As I’ve frequently argued on this blog, I believe that doing so is a fundamental enabler to transforming the way that cities work to meet the very real social, economic and environmental challenges facing us. But unless we take a realistic, informed approach and undertake the required engineering diligence, we will not be successful in that endeavour.

1. Which data is useful?

Amongst those thousands of data sets that contain information about cities, on which should we concentrate the effort required to make them widely available and usable?

That’s a very hard question to answer. We are seeking innovative change in city systems, which by definition is unpredictable.

One answer is to look at what’s worked elsewhere. For example, wherever information about transport has been made open, applications have sprung up to make that information available to travellers and other transport users in useful ways. In fact most information that describes the urban environment is likely to quickly prove useful; including maps, land use characterisation, planning applications, and the locations of shops, parks, public toilets and other facilities .

The other datasets that will prove useful are less predictable; but there’s a very simple way to discover them: ask. Ask local entrepreneurs what information they need to start new businesses. Ask existing businesses what information about the city would help them be more successful. Ask citizens and communities.

This is the approach we have followed in Sunderland, and more recently in Birmingham through the Smart City Commission and the recent “Smart Hack” weekend. The Dublinked information partnership in Dublin also engages in consultation with city communities and stakeholders to prioritise the datasets that are made available through the platform. The Knight Foundation’s “Information Needs of Communities” report is an excellent explanation of the importance of taking this approach.

2. What data is available?

How do we know what information is contained in those hundreds or thousands of data sets? Many individual organisations find it difficult to “know what they know”; across an entire city the challenge is much harder.

Arguably, that challenge is greatest for local authorities: whilst every organisation is different, as a rule of thumb private sector companies tend to need tens to low hundreds of business systems to manage their customers, suppliers, products, services and operations. Local authorities, obliged by law to deliver hundreds or even thousands of individual services, usually operate systems numbering in the high hundreds or low thousands. The process of discovering, cataloguing and characterising information systems is time-consuming and hence potentially expensive.

The key to resolving the dilemma is an open catalogue which allows this information to be crowdsourced. Anyone who knows of or discovers a data source that is available, or that could be made available, and whose existence and contents are not sensitive, can document it. Correspondingly, anyone who has a need for data that they cannot find or use can document that too. Over time, a picture of the information that describes a city, including what data is available and what is not, will build up. It will not be a complete picture – certainly not initially; but this is a practically achievable way to create useful information.

3. What is the data about?

The content of most data stores is organised by a “key” – a code that indicates the subject of each element of data. That “key” might be a person, a location or an organisation. Unfortunately, all of those things are very difficult to identify correctly and in a way that will be universally understood.

For example, do the following pieces of information refer to the same people, places and organisations?

“Mr. John Jones, Davis and Smith Delicatessen, Harbourne, Birmingham”
“J A Jones, Davies and Smythe, Harborne, B17”
“The Manager, David and Smith Caterers, Birmingham B17”
“Mr. John A and Mrs Jane Elizabeth Jones, 14 Woodhill Crescent, Northfield, Birmingham”

This information is typical of what might be stored in a set of IT systems managing such city information as business rates, citizen information, and supplier details. As human beings we can guess that a Mr. John A Jones lives in Northfield with his wife Mrs. Jane Elizabeth Jones; and that he is the manager of a delicatessen called “Davis and Smith” in Harborne which offers catering services. But to derive that information we have had to interpret several different ways of writing the names of people and businesses; tolerate mistakes in spelling; and tolerate different semantic interpretations of the same entity (is “Davis and Smith” a “Delicatessen” or a “Caterer”? The answer depends on who is asking the question).

(Two views of Exhibition Road in London, which can be freely used by pedestrians, for driving and for parking; the top photograph is by Dave Patten. How should this area be classified? As a road, a car park, a bus-stop, a pavement, a park – or something else? My colleague Gary looks confused by the question in the bottom photograph!)

All of these challenges occur throughout the information stored in IT systems. Some technologies – such as “single view” – exist that are very good at matching the different formats of names, locations and other common pieces of information. In other cases, information that is stored in “codes” – such as “LHR” for “London Heathrow” and “BHX” for “Birmingham International Airport” can be decoded using a glossary or reference data.

Translating semantic meanings is more difficult. For example, is the A45 from Birmingham to Coventry a road that is useful for travelling between the two cities? Or a barrier that makes it difficult to walk from homes on one side of the road to shops on the other? In time semantic models of cities will develop to systematically reconcile such questions, but until they do, human intelligence and interpretation will be required.

4. Sometimes you don’t want to know what the data is about

Sometimes, as soon as you know what something is about, you need to forget that you know. I led a project last year that applied analytic technology to derive new insights from healthcare data. Such data is most useful when information from a variety of sources that relate to the same patient is aggregated together; to do that, the sort of matching I’ve just described is needed. But patient data is sensitive, of course; and in such scenarios patients’ identities should not be apparent to those using the data.

Techniques such as anonymisation and aggregation can be applied to address this requirement; but they need to be applied carefully in order to retain the value of data whilst ensuring that identities and other sensitive information are not inadvertently exposed.

For example, the following information contains an anonymised name and very little address information; but should still be enough for you to determine the identity of the subject:

Subject: 00764
Name: XY67 HHJK6UB
Address: SW1A
Profession: Leader of a political party

(Please submit your answers to me at @dr_rick on Twitter!)

This is a contrived example, but the risk is very real. I live on a road with about 100 houses. I know of one profession to which only two people who live on the road belong. One is a man and one is a woman. It would be very easy for me to identify them based on data which is “anonymised” naively. These issues become very, very serious when you consider that within the datasets we are considering there will be information that can reveal the home address of people who are now living separately from previously abusive partners, for example.

5. Data can be difficult to use

(How the OECD identified the “Top 250 ICT companies” in 2006)

There are many, many reasons why data can be difficult to use. Data contained within a table within a formatted report document is not much use to a programmer. A description of the location of a disabled toilet in a shop can only be used by someone who understands the language it is written in. Even clearly presented numerical values may be associated with complex caveats and conditions or expressed in quantities specific to particular domains of expertise.

For example, the following quote from a 2006 report on the global technology industry is only partly explained by the text box shown in the image on the left:

“In 2005, the top 250 ICT firms had total revenues of USD 3 000 billion”.

(Source: “Information Technology Outlook 2006“, OECD)

Technology can address some of these issues: it can extract information from written reports; transform information between formats; create structured information from written text; and even, to a degree, perform automatic translation between languages. But doing all of that requires effort; and in some cases human expertise will always be required.

In order for city information platforms to be truly useful to city communities, then some thought also needs to be given for how those communities will be offered support to understand and use that information.

6. Can I trust the data?

Several British banks have recently been fined hundreds of millions of dollars for falsely reporting the interest rates at which they are able to borrow money. This information, the “London InterBank Offered Rate” (LIBOR) is an example of open data. The Banks who have been fined were found to have under-reported the interest rate at which they were able to borrow – this made them appear more creditworthy than they actually were.

Such deliberate manipulation is just one of the many reasons we may have to doubt information. Who creates information? How qualified are they to provide accurate information? Who assesses that qualification and tests the accuracy of the information?

For example, every sensor which measures physical information incorporates some element of uncertainty and error. Location information derived from Smartphones is usually accurate to within a few meters when derived from GPS data; but only a few hundred meters when derived by triangulation between mobile transmission masts. That level of inaccuracy is tolerable if you want to know which city you are in; but not if you need to know where the nearest cashpoint is. (Taken to its extreme, this argument has its roots in “Noise Theory“, the behaviour of stochastic processes and ultimately Heisenberg’s Uncertainty Principle in Quantum Mechanics. Sometimes it’s useful to be a Physicist!).

Information also goes out of date very quickly. If roadworks are started at a busy intersection, how does that affect the route-calculation services that many of us depend on to identify the quickest way to get from one place to another? When such roadworks make bus stops inaccessible so that temporary stops are erected in their place, how is that information captured? In fact, this information is often not captured; and as a result, many city transport authorities do not know where all of their bus stops are currently located.

I have barely touched in this section on an enormously rich and complex subject. Suffice to say that determining the “trustability” of information in the broadest sense is an immense challenge.

7. Data is easy to lose

(A computer information failure in Las Vegas photographed by Dave Herholz)

Whenever you find that an office, hotel room, hospital appointment or seat on a train that you’ve reserved is double-booked you’ve experienced lost data. Someone made a reservation for you in a computer system; that data was lost; and so the same reservation was made available to someone else.

Some of the world’s most sophisticated and well-managed information systems lose data on occasion. That’s why we’re all familiar with it happening to us.

If cities are to offer information platforms that local people, communities and businesses come to depend on, then we need to accept that providing reliable information comes at a cost. This is one of the many reasons that I have argued in the past that “open data” is not the same thing as “free data”. If we want to build a profitable business model that relies on the availability of data, then we should expect to pay for the reliable supply of that data.

A Brownfield Regeneration for the Information Age

So if this is all so hard, should we simply give up?

Of course not; I don’t think so, anyway. In this article, I have described some very significant challenges that affect our ability to make city information openly available to those who may be able to use it. But we do not need to overcome all of those challenges at once.

Just as the physical regeneration of a city can be carried out as an evolution in dialogue and partnership with communities, as happened in Vancouver as part of the “Carbon Talks” programme, so can “information regeneration”. Engaging in such a dialogue yields insight into the innovations that are possible now; who will create them; what information and data they need to do so; and what social, environmental and financial value will be created as a result.

That last part is crucial. The financial value that results from such “Smarter City” innovations might not be our primary objective in this context – we are more likely to be concerned with economic, social and environmental outcomes; but it is precisely what is needed to support the financial investment required to overcome the challenges I have discussed in this article.

On a final note, it is obviously the case that I am employed by a company, IBM, which provides products and services that address those challenges. I hope that you have noticed that I have not mentioned a single one of those products or services by name in this article, nor provided any links to them. And whilst IBM are involved in some of the cities that I have mentioned, we are not involved in all of them.

I have written this article as a stakeholder in our cities – I live in one – and as an engineer; not as a salesman. I am absolutely convinced that making city information more widely available and usable is crucial to addressing what Professor Geoffrey West described as “the greatest challenges that the planet has faced since humans became social“. As a professional engineer of information systems I believe that we must be fully cognisant of the work involved in doing so properly; and as a practical optimist, I believe that it is possible to do so in affordable, manageable steps that create real value and the opportunity to change our cities for the better. I hope that I have managed to persuade you to agree.

The new architecture of Smart Cities

(Photo of the National Centre for the Performing Arts in Beijing by Trey Ratcliff)

I’ve been preparing this week for the next stage of work on Birmingham’s Smart City Commission; our task on the Commission is to develop a strategic vision for Birmingham as a Smart City and a roadmap for achieving it.

In doing so I’ve been considering an interesting and important question:

What makes a city a “Smart City” as opposed to a city where some “smart things” happen?

Three obvious criteria for answering that question stand out:

1. Smart Cities are led from the top – they have a strong and visionary leader championing the Smart agenda across the city. The Mayors of Rio and Barcelona are famously showing such leadership; and in the UK, so too are, amongst others, Dave Smith, CEO of Sunderland City Council, and Sir Albert Bore, Birmingham’s elected Council Leader, and a founder of the Eurocities movement.

2. Smart Cities have a stakeholder forum – they have drawn together a community of city stakeholders across the city. Those stakeholders have not only created a compelling vision for a Smart City; they have committed to taking an ongoing role coordinating a programme to deliver it. This is the challenge we have been given in Birmingham’s Smart City Commission; and I’ve previously written about how such a responsibility could be carried out.

3. Smart Cities invest in technology infrastructure – they are deploying the required information and communication technology (ICT) platforms across the city; and doing so in such a way as to support the integration of information and activity across city systems. (There are, of course, many other infrastructures that are important to the future of cities; but in “Smart Cities” we are particularly concerned with the role of technology, as I argued in a recent article on this blog).

It’s also important, though, to consider what is different about the structure and organisation of city systems in a Smart City. How does a city such as Birmingham decide which technology infrastructures are required? Which organisations will make use of them, and how? How can they be designed and delivered so that they effectively serve individuals, communities and businesses in the city? What other structures and processes are required to achieve this progress in a Smart City?

Designing Smart Cities

In order to design the infrastructures and systems of Smart Cities well, we need to design them in context – that is, with an understanding of the environment in which they will exist, and the other elements of that environment with which they will interact.

The figure below – “Components of a Smart City Architecture” – is one way of describing the context for Smart City systems and infrastructures. It contains six layers which I’ll discuss further below: “Goals”; “People”; “Ecosystem”; “Soft Infrastructures”; “City Systems” and “Hard Infrastructures”.

(I’m very aware that this diagram is not a particularly good visual representation of a Smart City, by the way. It doesn’t emphasise the centricity of people, for example, and it is not aesthetically pleasing. I’m simply using it as a conceptual map at this stage. I welcome any suggestions for re-casting and improving it!)

(Components of a Smart City architecture)

Goals, People and Ecosystem

Every Smart City initiative is based on a set of goals; often they focus on sustainability, inclusivity and the creation of social and economic growth. Boyd Cohen, who writes frequently on the subject of Smart Cities for Fast Company, published an excellent article surveying and analysing the goals that cities have expressed in their Smart initiatives and providing a model for considering them.

Ultimately, such goals will only be achieved through a Smart City strategy if that strategy results in changes to city systems and infrastructures that make a difference to individuals within the city – whether they are residents, workers or visitors. The art of user-centric, or citizen-centric, service design is a rich subject in its own right, and I don’t intend to address it directly here. However, I am very much concerned with the wider context within which that design takes place, and in particular the role that communities play.

I do not believe that a Smart City strategy that concerns itself only with citizens, city systems and hard infrastructures will result in citizen-centric design; it is only be co-creating soft infrastructures with city communities that such an approach can be systematically encouraged across a city.

In “How Smarter Cities Get Started” I wrote some time ago about the importance of engaging city communities in identifying the goals of Smart City initiatives and setting out the strategy to achieve them. I’ve also written previously about the importance of designing Smart City infrastructures so that they enable innovation within city communities.

Communities are living, breathing manifestations of city life, of course, not structures to be engineered. They are vital elements of the city’s ecosystem: they provide support; they are expressions of social life; they represent shared interests and capabilities; and they can play a role communicating between city institutions and individual citizens. They include families and social networks; neighbourhood, cultural and faith groups; charities and the voluntary sector; public sector organisations such as Schools and Universities, in addition to local government; and private sector organisations such as service providers, retailers and employers.

The challenge for the architects and designers of Smart Cities is to create infrastructures and services that can become part of the fabric and life of this ecosystem of communities and people. To do so effectively is to engage in a process of co-creative dialogue with them.

Soft Infrastructures

In the process of understanding how communities and individuals might interact with and experience a Smart City, elements of “soft infrastructure” are created – in the first place, conversations and trust. If the process of conversations is continued and takes place broadly, then that process and the city’s communities can become part of a Smart City’s soft infrastructure.

A variety of soft infrastructures play a vital role in the Smart City agenda, from the stakeholder forum that creates and carries out a Smart City strategy; to the “hackdays” and competitions that make Open Data initiatives successful; to neighbourhood planning dialogues such as that conducted in Vancouver as part of the “Carbon Talks” programme. They also include the organisations and interest groups who support city communities – such as Sustainable Enterprise Strategies in Sunderland who provide support to small businesses and social enterprises in the city’s most deprived communities or the Social Media Cafe in Birmingham which brings together citizens from all walks of life who are interested in creating community value online.

Some soft infrastructural elements are more formal. For example, governance processes for measuring both overall progress and the performance of individual city systems against Smart City objectives; frameworks for procurement criteria that encourage and enable individual buying decisions across the city to contribute towards Smart City goals; and standards and principles for integration and interoperability across city systems. All of these are elements of a Smart City architecture that any Smart City strategy should seek to put in place.

(Photo of the Athens Olympic Sports Complex from Space by the NASA Goddard Space Flight Center)

City systems

Whilst individual city systems are not my focus in this article, they are clearly significant elements of the Smart City context. In a previous article I discussed how the optimisation of such systems as energy, water and transportation can contribute significantly to Smarter City objectives.

More importantly, these systems literally provide life support for cities – they feed, transport, educate and provide healthcare for citizens as well as supporting communities and businesses. So we must treat them with real respect.

A key element of any design process is taking into account those factors that act as constraints on the designer. Existing city systems are a rich source of constraints for Smart City design: their physical infrastructures may be decades old and expensive or impossible to extend; and their operation is often contracted to service providers and subject to strict performance criteria. These constraints – unless they can be changed – play a major role in shaping a Smart City strategy.

Hard Infrastructures

The field of Smart Cities originated in the possibilities that new technology platforms offer to transform city systems. Those platforms include networks such as 4G and broadband; communication tools such as telephony, social media and video conferencing; computational resources such as Cloud Computing; information repositories to support Open Data or Urban Observatories; and analytic and modelling tools that can provide deep insight into the behaviour of city systems.

These technology platforms are not exempt from the principles I’ve described in this article: to be effective, they need to be designed in context. By engaging with city ecosystems and the organizations, communities and individuals in them to properly understand their needs, challenges and opportunities, technology platforms can be designed to support them.

I’ve made an analogy before between technology platforms and urban highways. It’s much harder to design an urban highway in a way that supports and enables the communities it passes through, than it is to simply design one that allows traffic to get from one place to another – and that in overlooking those communities, runs the risk of physically cutting them apart.

Technology platforms rarely have such directly adverse effects – though when badly mis-applied, they can do. However, it is certainly possible to design them poorly, so that they do not deliver value, or are simply left unused. These outcomes are most likely when the design process is insular; by contrast, the process of co-creating the design of a Smart City technology infrastructure with the communities of a city can even result in the creation of a portfolio of technology-enabled city services with the potential to generate revenue. Those future revenues in return support the case for making an investment in the platform in the first place.

And some common patterns are emerging in the technology capabilities that can provide value in city communities. I’ve referred to these before as the “innovation boundary” of a city. They include the basic connectivity that provides access to information systems; digital marketplace platforms that can support new business models; and local currencies that reinforce regional economic synergies.

These technology capabilities operate within the physical context of a city: its buildings, spaces, and the networks that support transport and utilities. The Demos report on the “Tech City” cluster of technology start-up businesses in London offers an interesting commentary on the needs of a community of entrepreneurs – needs that span those domains. They include: access to technology, the ability to attract venture capital investment, office space from which to run their businesses; and proximity to the food, retail, accommodation and entertainment facilities that make the area attractive to the talented professionals they need to hire.

In a recent conversation, Tim Stonor, Managing Director of Space Syntax, offered this commentary on a presentation given by UN Habitat Director General Joan Clos at the “Urban Planning for City Leaders” conference last week:

“The place to start is with the street network. Without this you can’t lay pipes, or run trams. It’s the foundations of urbanism and, without foundations, you’re building on sand. Yes, we can have subways that cut across/beneath the street network, and data packets that travel through the airwaves over the tops of buildings, but if these aren’t serving human interactions in effectively laid out street networks, then they are to little avail.”

Tim’s point on human interactions, I think, brings us nicely back full circle to thinking again about people and the relationships between them. Tim’s further comments on the presentation can be found on Storify.

A New Architecture?

At some point in the process of writing this article, I realised I had strayed onto provocative ground – this, perhaps, is why it’s taken me longer than usual to write.

As you can see, my job title contains the word “architect”. Strictly, I’m an Information Technology Architect, or “IT Architect” – I’ve spent my career “architecting” IT solutions such as e-commerce sites, mobile web apps, analytics systems and so on. Most recently I’ve been working in that capacity with Sunderland on their City Cloud.

I’m very aware that a strong view exists amongst Architects who create buildings and plan cities that IT professionals shouldn’t be describing ourselves in this way. Indeed, some (although I’d say a minority) of my colleagues agree, and call themselves designers or engineers instead.

Personally, I feel comfortable referring to my work as “architecture”. Many “IT solutions” – or more broadly, “IT-enabled business solutions” – are complex socio-technical systems. They are complex in an engineering sense, often extremely so; but they incorporate financial, social, operational, psychological and artistic components too; and they are designed in the context of the human, social, business, political and physical environments in which they will be used.

(Entrance to the Apple Store on Fifth Avenue, New York, photographed by Lambert Wolterbeek Muller)

So when we are designing a technology solution in a Smart City context – or indeed in any physical context – we are concerned with physical space; with transport networks; with city systems; and with human interactions. All of these are related to the more obvious concerns of information technology such as user interfaces, software applications, data stores, network infrastructure, data centres, laptops and workstations, wi-fi routers and mobile connectivity.

It seems to me that whilst the responsibilities and skills of “IT Architects” and Architects are not the same, they are applied within the same context, and cannot be separated from each other in that context. So in Smart Cities we should not treat “architecture” and “IT architecture” as separable activities.

In “Notes on the Synthesis of Form”, a work which laid the groundwork for his invention of the “design patterns” now widely adopted by IT professionals, the town planner Christopher Alexander remarked of architecture:

At the same time that problems increase in quantity, complexity and difficulty, they also change faster than before. New materials are developed all the time, social patterns alter quickly, the culture itself is changing faster than it has ever changed before.”

– Christopher Alexander, Notes on the Synthesis of Form, Harvard University Press, 1964

What else are the technologies incorporated in Smart City solutions but these “new materials” from which Architects can construct cities and buildings?

At the very least, it is inarguably the case that technologies such as the internet, social media and smartphones are intimately related to the significant changes taking place today in our culture and social patterns.

I’ve blogged many times about the emerging technologies that are making ever more sophisticated and intimate connections between the IT world and the physical world – in particular, in the article “Four avatars of the metropolis: technologies that will change our cities“. The new proximity of those two worlds is what has led to the “Smart Cities” movement; in a way it’s simply another example of the disruptions of industries such as publishing and music that we’ve seen caused by the internet. And if these two worlds are merging, then perhaps our professions need at least to work more closely together.

Already we’re seeing evidence of the need to do so: many city leaders and urbanists I’ve spoken to have described the problems caused by the separation of economic and spatial strategies in cities; or of the need for a better evidence-base for planning and decision making – such as the one that IBM’s Smarter Cities Challenge team in Birmingham are helping the City Council to create. In response, we are starting to see technology experts taking part in some city and regional master-planning exercises.

Over the last few years this convergence of technology concerns with the many disciplines within urbanism has given me the opportunity to work with individuals from professions I would never previously have interacted with. It has been an honour and a pleasure to do so.

In a similar vein, I have quite deliberately posted links to this article in communities with wide and varied membership, and that I hope will include people who will disagree with me – perhaps strongly – and be kind enough to share their thoughts.

I’d like to thank the following people for their contributions in various discussions that have shaped this article:

How cities can exploit the Information Revolution

(This post was first published as part of the “Growth Factory” report from the thinktank TLG Lab).

(Graphic of New York’s ethnic diversity from Eric Fischer)

Cities and regions in the UK face ever-increasing economic, social and environmental challenges. They compete for investment in what is now a single global economy. Demographics are changing with more than 90% of the population now living in urban areas, and where the number of people aged over 65 will double to 19 million by 2050. The resources we consume are becoming more expensive, with cities especially vulnerable to disruptions in supply.

The concept of “Smarter systems” has captured the imagination of experts as an approach to turn these challenges into opportunities for more sustainable economic and social growth; particularly in cities, where most of us live and work. Smarter systems – in cities, transportation, government and industry –can analyse the vast amounts of data being generated around us to help make more informed decisions, operate more efficiently or even predict the future.

These systems enable city planners around the world to design urban environments that promote safety, community vitality and economic growth. They can bring real-time information together from city transportation, social media, emergency services and leisure facilities to better enable cities, such as Rio de Janeiro, to manage major public events. They can enable transport systems to better manage traffic flow and reduce congestion, as in Singapore. They can stimulate economic growth by enabling small businesses to better compete for business in collaboration with regional trading partners, in systems such as that operated by the University of Warwick.

Government policies such as Open Data, personal care budgets and open public services will dramatically increase the information available to citizens to help them take well-informed decisions. This information will be rich, complex and associated with caveats and conditions. Making it usable by the broad population is an immense challenge which will not be addressed by technology alone. Data needs not only to be made available, but understandable so that it can inform better decision-making.

Where does Smarter city data come from?

Raw data for Smarter systems is derived from three sources: the city’s inhabitants, existing IT systems and readings from the physical environment.

Information from people has become more accessible with the continued spread of connected mobile devices, such as smartphones. Open Street Map, for example, provides a global mapping information service sourced from the activities of volunteers with portable satellite navigation devices. However, the quality and availability of crowd-sourced information depends on the availability and resources of volunteers, who cannot be held accountable for whether information is accurate, complete or up-to-date.

It is also important to understand data ownership and the associated privacy concerns. There is a difference between data freely and knowingly contributed by an individual for a specific purpose and information created as a side-effect of their activity – for example, the record of a person’s movements created by the GPS sensor in their smartphone.

The Open Data movement, supported by central government, will dramatically increase the availability of data from public systems. For example, efforts are underway to make NHS healthcare data available, with appropriate security measures, to Life Sciences organisations to reinforce the UK’s pre-eminent position in drug discovery research. However, the infrastructure required to make large volumes of data widely and rapidly available in a usable form will not be created for free. Until their cost is included in future government procurements – or until commercial systems of funding are created – then much data will likely only be made open on a more limited “best efforts” basis.

Furthermore, not all city data is held by public bodies. Many transportation and utility systems are owned and operated by the private sector, and it is not generally established what information they should make available, and how. Many Smarter city systems that use data from such sources are private partnerships rather than open systems.

Meanwhile, certain kinds of data are becoming far more accessible through the advancing ability of computer systems to understand human language. IBM’s Watson computer demonstrated this recently by competing and winning against world champions in the American television quiz show, Jeopardy! Wellpoint is using this kind of technology to draw insight from medical information held in similar forms. Its aim is to better tackle diseases such as cancer by empowering physicians to rapidly evaluate potential diagnoses and explore the latest supporting medical evidence. Similar technology can draw insight from case notes in social care systems, as Medway Youth Trust is doing, or from the reports of engineers maintaining roads, sewers, and other city systems.

An early “mashup” application using open data from Chicago’s police force

Information is also becoming more readily available from the physical environment. In Galway Bay, a network of underwater microphones is connected to a system that can identify and locate the sounds of dolphins and porpoises. Their location provides a dynamic indication of which parts of the Bay have the cleanest water. That information is made available to companies in the Bay to allow them to control their discharges of water; and to the fishing and leisure industries who are dependent on marine life. This Open Data approach is being used by cities across the world such as Dublin, Chicago and London as a resource for citizens and businesses.

Whilst advances in technology have lowered the cost of generating information from physical environments, challenges remain. From the perspective of a mobile telephone user, much of the UK has signal coverage. However, telephones are used one metre or more above ground level; at ground level, where many parts of our transport and utility infrastructures are located, coverage is much poorer. Additionally, mobile transmitters and receivers are relatively expensive and power-hungry. Cheaper, lower power technologies are needed to improve coverage, such as the “Weightless” standard being developed to use transmission bandwidth no-longer needed by analogue television.

Using and combining data appropriately

In order to make information from multiple sources available appropriately and usefully, several issues need to be tackled.

When computer systems are used to analyse information and take decisions, then the data formats and protocols used by those systems need to be matched. Information as simple as locations and dates may need to be converted between formats. At an engineering level, the protocols used to transmit data across cities using wired or wireless communications behave differently and require systems that integrate them.

The meaning of information from related sources also needs to be understood and adapted to context. Citizens who go shopping in wheelchairs need to know how to get between car-parks and shops with lifts, accessible public toilets and cash points. However, the computer systems of the organisations who own those facilities will encode the information separately, in ways that support their efficient management, not that support journey-planning between them.

The City of Portland in Oregon has gone further in a project to understand how information from systems across the city is related. They are now able to better predict the impact that key decisions will have on the entire city, years in advance.

Privacy and ownership of data may affect its subsequent use, often with terms and conditions in place for governing its access. Furthermore, safeguards are required to ensure that sensitive information cannot be inferred from a combination of sources. For example the location of a safe house or shelter being identified from building usage, building ownership and /or information concerning taxi journeys by the employees of particular council agencies.

The human dimension

Smarter systems will only succeed in improving cities if there is wide consumer engagement. To be of value, information will likely need to be timely and presented in a manner appropriate to consumer context. Individual behaviour will only change where personal value is derived as a result of new information being presented – a saving in time or money, or access to something of value to their family.

(Photo of traffic in Dhaka, Bangladesh, from Joisey Showa)

Many cities are experimenting with technologies that predict the future build up of traffic, by comparing real-time measurements to databases of past patterns of traffic flow. In Stockholm, this information is used by a road-use charging system that supports variable pricing. In California, commuters in a pilot project were given personalised predictions of their commuting time each day. Both systems encourage individuals to make choices based on new information.

Utility providers are exploring how information from smart meters can encourage water and energy users to change behaviour. A recent study in Dubuque, Iowa, showed that when householders were shown how their water usage compared to the average for their neighbours, they became better at conserving water – by fixing leaks, or using domestic appliances more efficiently. Skills across artistic and engineering disciplines are helping us understand how this type of information can be communicated more effectively. Many people will not want to study figures and charts on a smart meter or website; instead “ambient” information sources may be more effective – such as a glow-globe that changes colour from green to orange to red depending on household electricity use.

Systems that improve the sustainability of cities could also affect economic development. Lowering congestion through Smarter transportation schemes can improve productivity by reducing time lost by workers delayed by traffic. By making information and educational resources widely available, Smarter systems could improve access to opportunity across city communities. A city with vibrant communities of well-informed citizens may appear a more forward-looking and attractive place to live for educated professionals and, in turn, for businesses considering relocation. New York has improved its attractiveness since the 1970s by lowering the fear of crime. One of its tools is a “real-time crime centre” that brings information together from across the city in order to better react to crime and public order incidents. The system can even help to prevent crime by intelligently deploying police resources to the areas most likely to experience incidents based on past patterns of activity – on days with similar weather, transportation conditions or public events.

Success in delivering against these broader objectives is much more likely to be achieved where the cities themselves are more clearly accountable for them.

So where do we start?

Investments in Smarter systems often cut across organisations and budgets and many have objectives that are macro-economic, social and environmental, as well as financial. As such, they challenge existing accounting mechanisms. Whilst central government and the financial markets offer new investment solutions such as ethical funds, social impact bonds and city deals, so far these have not been used to fund the majority of Smarter solutions – many of which are supported by research programmes. The Technology Strategy Board’s investment in areas such as “Future Cities” and the “Connected Digital Economy” will provide a tremendous boost, but there is much to be done to assist cities in using new investment sources to fund Smarter initiatives – or to develop sustainable commercial or social-enterprise business models to deliver them.

Although progress can be driven by strong leadership, the issues of governance and fragmented budgets will need to be overcome if we are to take full advantage of the benefits technology can bring.

We live in an era of major global challenges – well described in the recent “People and the Planet” report by the Royal Society. At the same time, we have access to powerful new technologies and ideas to address them, such as those proposed by the 100 Academics who contributed essays to the book “The New Optimists”. When we focus those resources on cities, we focus on the structures in which we can have the greatest impact on the most people.

Already many forward-looking cities in the UK such as Sunderland and Birmingham are joining others around the world by investing in Smarter systems. If we can meet the technical, organisational and investment challenges, we will not only provide citizens, businesses and agencies with new choices and exciting opportunities; we’ll also position the UK economy to succeed as the Information Revolution gathers pace.

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