Data Urbanism.
We refer to the process of making urban data visible, accessible and actionable as Data Urbanism.
The amount of data generated by our daily activities and interactions will increase persistently, as digital devices continue to come into our lives. And while we use those devices as a central access point to information, the data we generate on a daily basis — either directly or as a by-product of our social activities — is often associated with contextual meta-information about location, usage and people.
In other words, data gives us a valuable insight into both our social interactions and the environment that staged those interactions. Furthermore there is a strong tendency to open data sources that were once locked within government agencies. Open access to information, as well as the emergence of low-cost or free analysis web tools, allows citizens to look for patterns in government activity or to use data analysis to advocate for change.
Data Map Basics.
Data mapping matches from a source to a target so that the two may exchange data meaningfully. Common sources and targets include databases, data sets, standards, and terminologies. Unidirectional mapping goes from the source to the target. Bidirectional maps translate in both directions.
In some maps, a database can act as a translation key from one source to the next, providing additional information needed to map the information.
Cities Global Urban Transition.
Fig.01 Every death on every road in Great Britain 1999-2010.
Making Data Visible, Accessible and Actionable.
In order to bridge the gap between open data and civil society data should be made visible, accessible and actionable for a variety of audiences.
Fig. 02 Above Mapping building permits in Sofia.
Public data is often locked behind proprietary web interfaces. This prevents the re-use of data and stops citizens from exploring, interacting with and making sense of available datasets. This is the case of the Building Permits in Sofia – a public register that keeps track of all recent building permits issued by the municipality of Sofia. While the data is publicly accessible, it is impossible to download or export it in a machine readable format. The raw data is essentially locked behind a single access point – the clunky interface of the web application.
This prevents the re-use of data to create maps and visualizations; to ask questionts and search for answers in the data.
Data Visualization.
Visualizing urban data is a critical task as cities continue to dominate global concerns about climate change, economic prosperity and social equity. Interactive visualizations reveal how cities perform and how people interact with the urban environment by exposing the underlying logic of demographic processes, mobility patterns and digitalized daily transactions. In that sense they are the key to maximizing data efficiency and upgrading urban governance to a more open and agile model. As we strive for more compact, connected and coordinated urban growth, visualizing the dynamics of urban processes becomes both an integral part of city governance and an instrument for civic engagement.
Fig.03 Visualizing pollution patterns. The data is collected from various sensors deployed in 7 cities around the globe and is part of the Data Canvas initiative.
Fig.04 Moscow staying put.
Radial flows of commuters between dormitory districts in Moscow and the center provide only a quarter of all the morning moves in the agglomeration; both, centripetal and centrifugal moves inclusive, as well as forced transit through the center (“excessive indirect routes”). A large part of population moves between transport rings, doesn’t cross them and doesn’t really rush to the center. The commute from the dormitory districts to the center only represents around 10% of all the flows within the agglomeration – and these are 10% of mobile citizens (1/3) that correspond to 1/30 of total population of Moscow urban area.
The commuting patterns of Muscovites on the periphery resemble “flea jumps”. While in the Moscow Region populated areas are fully developed urban communities, dormitory districts in Moscow are just “departure” and “destination” points that hardly ever form their own “hinterlands”.
Fig.05 Airbnb New York and San Francisco, 2008-2011.
A set of maps for Airbnb.com, showing the explosive growth of the service since it started in 2008. Darker city blocks have less listings, brighter blocks have more. It’s amazing to see how quickly some areas fill in as more and more people discover they can list their apartments—and to see which areas stay dark.
Fig.06 San Francisco Emotion Map.
The San Francisco Emotion Map is the culmination of Christian Nold’s five-week residency and participatory art project that involved a total of 98 participants exploring San Francisco’s Mission District neighborhood using the Bio Mapping device he invented. During his residency at Southern Exposure, Christian Nold worked in the organization’s Mission Street storefront gallery encouraging visitors to stop by and use the devices during the weekdays and on Saturdays when he conducted intensive workshops. The project invited the public to go for a walk using the device, which records the wearer’s physiological response to their surroundings.
The results of these walks are represented on this map using colored dots and participant’s personal annotations. The San Francisco Emotion Map is a collective attempt at creating an emotional portrait of a neighborhood and envisions new tools that allow people to share and interpret their own bio data.
Fig.06 How punctual is the Deutsche Bahn.
Trains are represented as arrows, of which the overlaying colored circle denotes an estimation of the actual delay. The map can be explored in a “live-mode”, revealing all current delayed trains, or in an “historic mode”, for instance by dragging (or selecting within) the timeline at the top. A Play-button then highlights the relative movement of the trains as they are traveling, or traveled so far, through Germany. In addition, each train on the map can be selected to display more detailed information (such as the official reasons for the delay, for example).
Why Design Matters.
Public data is rarely usable by ordinary citizens in the form in which it is first released. The release is a crucial early step, but it is only one step in the process of maximizing the usefulness of public resources for the people who own them. Because data carries important information about the parts of people’s lives that are necessarily communal, it needs to be available and accessible to all. It needs to be presented in ways that illuminate the information it contains and that allow residents to interact with it and incorporate that information into their lives.
The real-time transit apps that are such a strong early example of useful open data do more than offer a raw feed of bus positions. The best of them allow riders to search arrivals on multiple lines of their choosing and adjust their commute plans accordingly. We can see the difference between great and merely adequate design in markets where multiple applications have been built based on the same data. Designs that more smoothly facilitate the tasks that people want to do are the most adopted. Conversely, valuable data that is presented in a way that is at odds with citizens’ mental models or awkward to use often doesn’t get the attention it deserves.
Conclusion.
In all cases the main challenges for generating dialogue through urban data visualizations consist of choosing the right type of visual strategy and achieving high standarts for data accuracy.
Data Urbanism suggests an iterative approach to urban planning that starts with harnessing the potential of open spatial data by enabling hands-on interaction with it and transfoming the invisible bits into a coherent exploratory mechanism.
For local governments, financial reporting is about more than simply ensuring that the numbers add up. Public officials also have to be able to communicate the data in a way that is both understandable and meaningful to target audiences, whether it’s city officials making decisions about resource allocation or voters making decisions about whether to trust their governments.
That’s the challenge for municipalities: How can local governments provide a comprehensive yet accessible medium for distributing budgetary and other financial data? And from a practical standpoint, how can city leaders make this happen with limited resources and staff capacity?
Increasingly, the solution is data visualization. By linking enterprise performance systems to tools that provide instant access to current and historic financial records, more and more governments are allowing almost anyone to view and manipulate public data via vivid pie charts and line graphs. Users can even export raw numbers or high-impact graphics for use in meetings and communications materials.
Student : Borislava Lyubenova
Tutor : Gonzalo Delacamara
