Τhe POI data value chain includes several sectors of our economy, such as navigation, logistics, tourism and leisure, geo-marketing, advertising, etc. The current landscape in collecting and integrating POI data hinders the aforementioned economy sectors to integrate, enrich, share, re-use and fully exploit, through new added value services, their POI datasets. This translates to losses of productivity, reduced market share, reduced profits, and constraints for the development of new products.

SLIPO will reduce the effort, time and cost required to produce POI data of high quality.

Current approaches are labor-intensive and do not scale beyond domain-specific or local efforts. The industry has two pathways to reduce the complexity to feasible levels: either to focus on a specific domain or to reduce the spatial-, temporal-, and feature-space of data. In both cases, reducing semantic complexity to address scalability problems leads to loss of information and thus lost value. By tackling the challenges of large-scale POI data integration, SLIPO will enable processes and analytics that are currently infeasible or too expensive to perform.

SLIPO will allow non-expert POI producers and consumers to easily transform, interlink, fuse, enrich and assess the quality of big POI data.

The output of SLIPO will not only reduce current costs in the value chain but will also facilitate processes that are currently infeasible to pursue in terms of scale, quality, and usability.