The V in VGI: Citizens or Civic Data Sources

Volunteered geographic information (VGI), delivered via mobile and web apps, offers new potentials for civic engagement. If framed in the context of open, transparent and accountable governance then presumably VGI should advance dialogue and consultation between citizen and government. If governments perceive citizens as consumers of services then arguably such democratic intent elide when municipalities use VGI. Our empirical research shows how assumptions embedded in VGI drive the interaction between citizens and government. We created a typology that operationalises VGI as a potential act of citizenship and an instance of consumption. We then selected civic apps from Canadian cities that appeared to invoke these VGI types. We conducted interviews with developers of the apps; they were from government, private sector, and civil society. Results from qualitative semi-structured interviews indicate a blurring of consumer and citizen-centric orientations among respondents, which depended on motivations for data use, engagement and communication objectives, and sector of the respondent. Citizen engagement, an analogue for citizenship, was interpreted multiple ways. Overall, we found that government and developers may increase choice by creating consumer-friendly apps but this does not ensure VGI offers an act of civic participation. The burden is placed on the contributor to make it so. Apps and VGI could potentially further a data-driven and neoliberal government. Planners should be mindful of the dominance of a consumer-centric view even as they assume VGI invariably improves democratic participation

The Geoweb for community-based organizations: Tool development, implementation, and sustainability in an era of Google Maps

Recent advances in web-based geospatial tools (the Geoweb) show promise as low-cost and easy-to-use methods to support citizen participation. This research presents two case studies of Geoweb implementation set in community-based organizations in rural Quebec, Canada. When comparing the development and sustainability of each Geoweb tool, the implementation time frame plays a key role. Two implementation time frames are defined; a discrete, or ‘one-off’ time frame associated with lower resource requirements, and a continuous, or ongoing time frame, that has a higher total resource cost, but can fulfill a different set of goals than a discrete implementation

Data-Driven Participation: Algorithms, Cities, Citizens, and Corporate Control

In this paper, we critically explore the interplay of algorithms and civic participation in visions of a city governed by equation, sensor and tweet. We begin by discussing the rhetoric surrounding techno-enabled paths to participatory democracy. This leads to us interrogating how the city is impacted by a discourse that promises to harness social/human capital through data science. We move to a praxis level and examine the motivations of local planners to adopt and increasingly automate forms of VGI as a form of citizen engagement. We ground theory and praxis with a report on the uneven impacts of algorithmic civic participation underway in the Canadian city of Toronto

Enlisting Students to Transcribe Historical Climate and Weather Data For Research: Building Knowledge Translation Via Classroom-Based Citizen Science

DRAW (Data Rescue: Archives & Weather) is a citizen science project that asks the Canadian public to take part in transcribing millions of meteorological observations recorded between 1871 and 1963 at McGill University’s Observatory in Montreal, Quebec, which was demolished in 1963. We examine how classroom-based curricula can integrate citizen science so youth can learn more about their community via engagement with the local history of weather conditions and impacts. Conducted in March 2018, this research examined knowledge translation during a three-week course module through written reflections, classroom video footage, exit interviews, and a final group research assignment. We worked with 21 students—16- to 20-year-olds enrolled in a social science research methods course at Dawson College, a two-year collège d\u27enseignement général et professionnel (college of general and vocational education) that attracts local students and is a funded part of education in the province of Quebec. We found knowledge translation was facilitated by student engagement with their community’s history and appreciation for aiding credible scientific research. Knowledge translation suffered from attempts to include archival records that could be difficult to find, access, and read. Our work showed that citizen science, as a vehicle for community engagement and scientific literacy, requires considerable contextualization, for example, the use of frequently asked questions, tutorials, and blogs for context, and historical context to ensure knowledge translation takes place

Participatory Design for User-generated Content: Understanding the challenges and moving forward

Research on participatory design (PD) dates back to the 1970s, and has focused historically on internal organization settings. Recently, the proliferation of content-producing technologies such as social media and crowdsourcing has led to the explosion of user-generated content (UGC) that originates outside of organizations. Participative challenges in UGC differ from those in traditional organizational, as well as other distributed multi-user, settings; e.g.; open source software, multi-party systems. UGC is an interesting emerging domain and exploring PD in this context may contribute to knowledge and practices in PD itself. In this paper, we analyze the challenges and opportunities associated with PD in organization-directed UGC development, illustrate these with two UGC projects, and propose fruitful directions for future research

A Web of Expectations: Evolving Relationships in Community Participatory Geoweb Projects.

This article was first published in ACME: An International Journal for Critical Geographies in 2015, available online: http://ojs.unbc.ca/index.php/acme/article/view/1235/1030.New forms of participatory online geospatial technology have the potential to support citizen engagement in governance and community development. The mechanisms of this contribution have predominantly been cast in the literature as ‘citizens as sensors’, with individuals acting as a distributed network, feeding academics or government with data. To counter this dominant perspective, we describe our shared experiences with the development of three community-based Geospatial Web 2.0 (Geoweb) projects, where community organizations were engaged as partners, with the general aim to bring about social change in their communities through technology development and implementation. Developing Geoweb tools with community organizations was a process that saw significant evolution of project expectations and relationships. As Geoweb tool development encountered the realities of technological development and implementation in a community context, this served to reduce organizational enthusiasm and support for projects as a whole. We question the power dynamics at play between university researchers and organizations, including project financing, both during development and in the long term. How researchers managed, or perpetuated, many of the popular myths of the Geoweb, namely that it is inexpensive and easy to use (thought not to build, perhaps) impacted the success of each project and the sustainability of relationships between researcher and organization. Ultimately, this research shows the continuing gap between the promise of online geospatial technology, and the realities of its implementation at the community level.Peer-reviewe

Integrating XAI and GeoAI

While eXplainable Artificial Intelligence (XAI) has significant potential to glassbox Deep Learning, there are challenges in applying it in the domain of Geospatial Artificial Intelligence (GeoAI). A land use case study highlights these challenges, which include the difficulty of selecting reference data/models, the shortcomings of gradients to serve as explanation, the limited semantics and knowledge scope in the explanation process of GeoAI, and underlying GeoAI processes that are not amenable to XAI. We conclude with possibilities to achieve Geographical XAI (GeoXAI)