New forms of communal sensor data-gathering demonstrate that it is now possible to to capture large volumes of geo-referenced sensor data at great levels of detail, incorporating many different perspectives. Research by Martin Dittus aims to assess the tools and processes used by these communities, to develop means of improving the quality of the collected data, and to develop better means of extracting and presenting insight from the data.
The initial aim is to assess some key aspects of communal data-gathering practice in community groups like OpenStreetMap, Cosm, Air Quality Egg, the Smart Citizen Kit, Sensorpedia, and others.
The Dynamics and Outcomes of Communal Data-Gathering Systems
These volunteer data-gathering activities are equally a pastime of highly skilled volunteers as they are early experiments in 21st-century civics, and they may reveal a potential urban future: participative, citizen-driven data infrastructure that captures many aspects of our urban spaces.
However there still are fundamental questions about the strengths and limitations of such activities. To address them requires to assess both their social and their technical aspects:
- What motivates participation? What are the interests, needs, and abilities of participants?
- What are the processes and technologies used to gather urban sensor data? For example, how does one build a sustainable data-gathering community?
- How can we assess and improve data quality? How can we make the data useful? What information can we extract from it?