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Scalable Linking of Integration of Big POI Data
POIs are the content of any application, service, and product even remotely related to our physical surroundings. From navigation applications, to social networks, to tourism, and logistics, we use POIs to search, communicate, decide, and plan our actions. The Big Data assets for POIs and the evolved POI value chain introduced opportunities for growth, but also complexity, intensifying the challenges relating to their quality-assured integration, enrichment, and data sharing. POI data are by nature semantically diverse and spatiotemporally evolving, representing different entities and associations depending on their geographical, temporal, and thematic context. Pioneered by the FP7 project GeoKnow, linked data technologies have been applied to effectively extract the maximum possible value from open, crowdsourced and proprietary Big Data sources. Validated in the domains of tourism and logistics, these technologies have proven their benefit as a cost-effective and scalable foundation for the quality-assured integration, enrichment, and sharing of generic-purpose geospatial data In SLIPO, we argue that linked data technologies can address the limitations, gaps and challenges of the current landscape in integrating, enriching, and sharing POI data. Our goal is to transfer the research output generated by our work in project GeoKnow, to the specific challenge of POI data, introducing validated and cost-effective innovations across their value chain.