The Touristic Network app, built in the
Information on every ski resort area is collected from a variety of sources to guarantee high-accuracy. Converging all these datasets could be problematic, for various reasons. In some cases, the same information could be contained in the various datasets. The effect is that merging the datasets could potentially cause ambiguous duplications. Additionally, dealing with a diversity of data formats may cause complications.
The Η2020 project SLIPO remedies these situations by providing the SLIPO Workbench, a complete software suite for handling the linking and integration of Big POI (Points of Interest) data assets. The SLIPO Workbench supports the entire lifecycle of POI integration (transformation, linking, fusion, and enrichment), by transferring the data integration problem to the Linked Data domain. In this process, datasets are first transformed into RDF (via TripleGeo), interlinked (via LIMES), fused (via FAGI) and enriched (via DEER) in a simple to use and cost-effective manner that delivers POI assets of increased coverage, completeness, quality, and timeliness. SLIPO Workbench reduces the effort, time, and cost to integrate POI data at a world-scale.
In the context of QROWD, the SLIPO Workbench is being tested and evaluated based on its efficacy and the user-friendliness of the process. Combining the different POIs located within and around the ski resorts offers a nice challenge to SLIPO. This is because the different datasets contain a diversity of geometry (points, lines, and polygons), adding complexity to the interlinking process. We expect this application to mark the beginning of a fruitful cooperation between the SLIPO and QROWD Horizon 2020 projects.