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Recent publications surrounding Volunteered Geographic Information (VGI) broadly represent the belief among some in the academic community that non-scientists can be engaged in and benefit from spatial data analysis (Connors et al., 2011; Flanagin & Metzger, 2008; Goodchild, 2007a, 2010), a field previously reserved exclusively for academics. Focus on VGI represents a paradigm shift from viewing science as having a single authority (the scientist) to a model where authority is relative and expressed contextually. Abundance, repetition, and the collective assessment of data (as well as the ability to correct) convey credibility to information that would not necessarily exist otherwise (Connors et al., 2011). In this sense, a non-scientist plays a role in validating data collected by others, and collectively assessing data quality (Craglia, 2007).
The concept of Web 2.0 incorporates bi-directional collaborations in which users collectively collate spatial data, stored in a central cloud repository and accessible by anyone for whatever purpose deemed worthy. The Web 2.0 paradigm is represented widely through web projects such as Wikimapia, OpenStreetMap, and even Google Earth. Within the context of these volunteered GISystems (VGIS), users contribute information to develop a collective knowledge base. Recent advances in mobile technology have furthered the applicability of Web 2.0 projects, enabling easier access to the information, and even allowing for novel uses of crowd-sourced information (Rosenberg, 2011). Sui (2008) extends the paradigm to include “the wikification of GIS”, a notion which he defines as being the shift in perception that only people who are specifically trained to “do GIS” should interact with spatial data and perform analysis. It is upon this notion, specifically, that VGIS endeavors to enhance the role of the user in the collection and analysis of spatial data.
The use of volunteered information for disease surveillance draws upon themes in the participatory GIS (PGIS) literature in suggesting that GIS technologies can operate in concert with volunteered information and local knowledge (Boroushaki & Malczewski, 2010b; Connors et al., 2011; Elwood, 2010; Flanagin & Metzger, 2008). The key distinction between classical PGIS methods and VGIS involves the role of the scientist. We refer here to McCall’s (2005) discussion of good governance through improving dialogue, legitimizing and using local knowledge, the redistribution of resources access and rights, and new skills training in geospatial methods. These concepts support the idea that a PGIS or VGIS approach can contribute to the adoption of new technologies for disease surveillance.