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Crowdsourcing: A Geographic Approach to Public Engagement, The Programmable City Working Paper 6
Lauriault, Tracey P.; Mooney, Peter
In this paper we examine three geographic crowdsourcing models, namely: volunteered geographic information (VGI), citizen science (CS) and participatory mapping (PM) (Goodchild, 2007; Audubon Society, 1900; and Peluso, 1995). We argue that these geographic knowledge producing practices can be adopted by governments to keep databases up to date (Budhathoki et al., 2008), to gain insight about natural resources (Conrad and Hilchey, 2011), to better understand the socio-economy of the people it governs (Johnston and Sieber, 2013) and as a form of data-based public engagement. The paper will be useful to governments and public agencies considering using geographic crowdsourcing in the future. We begin by defining VGI, CS, PM and crowdsourcing. Two typologies are then offered as methods to conceptualize these practices and the Kitchin (2014) data assemblage framework is proposed as a method by which state actors can critically examine their data infrastructures. A selection of exemplary VGI, CS and PM from Canada and the Republic of Ireland are discussed and the paper concludes with some high level recommendations for administrations considering a geographic approach to crowdsourcing.
Keyword(s): Geography; NIRSA-National Institute for Regional and Spatial Analysis; crowsourcing; mapping; geography; cartography; participatory mapping; volunteered geographic inforamtion; VGI; community mapping
Publication Date:
2014
Type: Conference item
Peer-Reviewed: No
Institution: Maynooth University
Citation(s): Lauriault, Tracey P. and Mooney, Peter (2014) Crowdsourcing: A Geographic Approach to Public Engagement, The Programmable City Working Paper 6. In: Internet Politics and Policy Conference, 2014, Oxford Internet Institute.
Publisher(s): Programmable City
File Format(s): other
Related Link(s): http://mural.maynoothuniversity.ie/5681/1/LauriaultMooney_ProgrammableCity_Crowdsourcing_WorkingPaper6_Nov2014.pdf
First Indexed: 2020-01-31 06:24:10 Last Updated: 2020-04-02 06:58:07