Public participatory historical GIS. Issue 3 (3rd July 2019)

• Record Type: Journal Article
• Authors: Lafreniere, Don; Weidner, Luke; Trepal, Daniel; Scarlett, Sarah Fayen; Arnold, John; Pastel, Robert; Williams, Ryan
• Is Part Of: Historical methods. Volume 52:Issue 3(2019)
• Page Start: 132
• Page End: 149
• Publication Date: 2019-07-03
• Subjects: Historical GIS -- public history -- crowdsourcing -- public participatory GIS -- spatial storytelling; Social sciences -- Periodicals; Onderzoeksmethoden; Electronic journals; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 300.5
• DOI: 10.1080/01615440.2019.1567418
• Languages: English
• ISSNs: 0161-5440

Abstract

Abstract: Building historical geographic information system (HGIS) datasets is time consuming and very expensive, especially when built at the scales that permit analysis of the lived experiences of individuals or the morphology of buildings or streets. Further, these datasets are often built exclusively in the academy, with little input from the contemporary communities they represent. In this paper, we review the use of the public in crowdsourcing historical data creation, and using the Keweenaw Time Traveler set in Michigan's Copper Country as a case study, we call for a new approach to HGIS scholarship that includes a robust public partnership to building HGIS datasets. The creation of a public participatory HGIS approach to HGIS scholarship can increase efficiencies of, public relevance in, and extend the reach of, HGIS projects beyond the academy. We have established a set of best practices that include, incorporating the public in the HGIS interface design, providing immediate public data access, contextualization of spatial data in space-time, comprehensive public history outreach in person and online, and creating affordances for the public to contribute their own historical spatial knowledge through spatial storytelling. Together, these activities can promote the long-term sustainability and success of historical data crowdsourcing projects.