What gets measured gets done

Excited conversations around Open City Data in our office have kept returning to the past – to our own experiences and stories that have framed our understanding of data in cities more broadly over the last 12 years in practice (and 40 years of Jan Gehl’s research). Here we will share some of our thoughts based on these experiences. Our practice’s foundational values are grounded in understanding the human experience of the city, and this sensibility extends to how we approach technological changes that affect it. Open data for us and the increased salience of transparency it evokes should be understood as social change, not simply technological development. There has been a cultural and political shift in will that has created a climate for the emergence of a collaborative spirit. Innovation through mining latent values is – it could be asserted – the spirit of our time in an age of scarcity.

Smart cities, smart phones and censors will create a flood of data and measurements, however it is still what we choose to do with this data, how we apply it, how we process it and of what quality it is that will influence decision makers and create a shift in the city – not the quantity or digital nature of it.

‘Not everything that can be counted counts, and not everything that counts can be counted’                -  Albert Einstein

All over the world there is a shift by governments and organisations to try to capture alternative measures presenting a more even spread of values and interests that can be drawn on by decision makers.  From National Gross Happiness to measures of well-being, these attempt to capture changing societal values as they move away from the material towards quality of life concerns. This presents a significant challenge for statisticians but is necessary if we are to strive for socially and environmentally minded governance and escape the data ‘cage’ in which the economics of the twentieth century has left us. To continue to base decision making solely on that which is most easily measurable undermines the possibility for achieving the changes which our age demands. For instance, we believe environmental challenges require a more diverse set of responses than those offered by the currently myopically focused approach.

Open city data could offer the backbone to a new ecosystem of shared data, captured for different reasons and to alternate ends. It could sound the death knell for cities’ over-reliance on static sources of data, and provide the platform for much-needed change.

With permission of the Charles Booth Archive at the Library of the London School of Economics http://booth.lse.ac.uk/

Seeing is believing

In 1889 in London the philanthropist and social researcher Charles Booth, frustrated by the lack of data on the city’s changing demography and in particular on the city’s poor, set out to complete an extensive study of the people and places of the industrial city. Claimed to be a more lively and accurate portrait of London than even Dickens’ novels, his mixture of ethnographic, observational and spatial data filled many volumes and was expressed as a colour-coded, beautifully intricate map. This displayed the inequalities that went to form the ubiquitous paradox of the urban industrial society: ‘poverty in a land of plenty’.

Booth’s social survey caused a significant discursive shift – it served to dispel the myth that poverty was the punishment for idleness and immorality; that poverty was due to the failings of the poor themselves rather than society or the poor conditions of the city itself. Booth produced data which showed that 30% of the population lived in poverty caused by low pay, old age, sickness disability and unemployment – and that unemployment was in fact a spatial issue. This led to the urban malaise being treated as a spatial problem as well as an individual one. Areas of low-employment needed targeted injections of jobs, and so began the place based nature of urban regeneration and policy. The work proved to be revolutionary in the scientific spatial representation of society – social cartography or mapping began to interrogate the correlations between urban conditions and social phenomena. Journalistic accounts at the time reported poverty, and the places in which it was endemic – Dickens’ serialised and widely distributed novels dramatized the issues -  but picturesque narrations do little for the legislator. Social-scientific presentations, on the other hand, were more adept at forcing institutional responses. City managers ‘manage what they can measure’. This was – and still is – the bureaucrat’s remit, and this data gave the visibility necessary to spur change.  Booth and Rowntree (who conducted a social study of poverty in York) are cited in the reform of the poor law and their data is said to have inspired the Liberal government of 1906 to embark on their extensive welfare reform programme. The programme explicitly targeted children, the sick, the elderly and the un-employed  and is the basis of the modern-day welfare system.

Have we been measuring the right things?

Booth was a game changer, revolutionising the way in which data was used to feed into social policy.  Does ubiqutous data generated by mobile devices, data sensors and apps only promote a form of surveillance that can infringe on freedom of expression? Or can we use these feedback loops to ensure the city’s structures and systems can better adapt to the rapid change of the culture and lifestyle of urban living? It has been said that we will experience 100 years of social change over the next decade. Perhaps the emergence of open data as a new basis for urban decision making will respond to the uniqueness of our time in the way that Booth’s map did, with equally radical results. After all, that is precisely what we need.

Bloggers are Simon Goddard, Claire Mookerjee, Jo Posselt and Jeff Risom


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