Abstract
The value of data in supporting citizen participation in processes of place-making and community building is widely recognised. While the open data movement now permits citizens to acquire governmental data relating to their communities, little to no effort is made to ensure that these datasets are accessible and interpretable by non-professionals. Through a series of community engagements spanning an 18-month period, we co-designed Data:In Place, an open source web tool which supports citizens in accessing, interpreting and making sense of open data. Leveraging visual map-based querying, citizens can access official statistics about their community, interrogate the data, and map their own data sources to create data visualisations. Reflecting on the participatory design process and the designed technology, we provide a framing to make open data work for civic advocacy.
Highlights
From life-logging to smart city management, data is at the centre of our worlds, communities, and research
We present findings from the research team’s field-notes and observations at community meetings, focus groups, interviews and feedback sessions with different stakeholders - two local government workers (LG), six charity workers (CW) and eight community volunteers (CV) from a range of roles
When we presented one of the charity workers (CW2) involved in the planning group with the data they had requested, they were concerned with the lack of context: “Should be street names or post codes for people to understand where the data is coming from.”
Summary
From life-logging to smart city management, data is at the centre of our worlds, communities, and research. While the technology to generate and store such vast quantities of data is ubiquitous, what remains a significant challenge is how to use that data for the common good. The development of the open data movement has begun to overcome the first obstacle to using data for the common good, namely enabling people other than those who generated it to access and use it. The effective use of big data requires the professional skills of the data scientist. These include skills of being able to access, interpret, and make sense of data in ways that make it valuable, actionable information for others [22] and data science skills are in high demand
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