Linked crowdsourced data - Enabling location analytics in the linking open data cloud

Abstract

Geospatial datasets in the Linking Open Data (LOD) Cloud are rather of static nature and mainly consist of information such as a name, geo coordinates, an address, or opening hours. There is no linked dataset providing dynamic information about the “popularity” of certain places or the “Visiting frequency” of users in specific contextual situations. This type of information within the LOD Cloud, however, would enable a variety of new applications based on semantically enriched location analytics. In this paper, we present Linked Crowdsourced Data as a dataset, which links real user location preferences (e.g., check-ins, ratings, or comments) as well as specific context situations (e.g., weather conditions, holiday information, or measured networks) collected via crowdsourcing to static location data. We showcase the applicability of this dataset for location analytics use cases through a map visualization and highlight its added value with exemplary SPARQL queries that allow for location requests depending on historic context information.