%0 Conference Paper %1 slipo2019 %A Athanasiou, Spiros %A Giorgos, Giannopoulos %A Damien, Graux %A Nikos, Karagiannakis %A Jens, Lehmann %A Ngonga Ngomo, Axel-Cyrille %A Kostas, Patroumpas %A Sherif, Mohamed Ahmed %A Skoutas, Dimitrios %B International Conference on Extending Database Technology 2019, EDBT19 %D 2019 %K 2019 deer dice group\_aksw lehmann limes ngonga sherif simba slipo %T Big POI data integration with Linked Data technologies %U http://svn.aksw.org/papers/2019/EDBT_SLIPO/public.pdf %X Point of Interest (POI) data constitute the cornerstone of any application, service or product even remotely related to our physical surroundings. From navigation applications to social networks, tourism, and logistics, we use POI data to search, communicate, decide and plan our actions. POIs are semantically diverse and spatio-temporally evolving entities, having geographical, temporal and thematic relations. Currently, integrating POI data to increase their coverage, timeliness, accuracy and value is a resource-intensive and mostly manual process, with no specialized software available to address the specific challenges of this task. In this paper, we present an integrated toolkit for transforming, linking, fusing and enriching POI data, and extracting additional value from them. In particular, we demonstrate how Linked Data technologies can address the limitations, gaps and challenges of the current landscape in Big POI data integration. We have built a prototype application that enables users to define, manage and execute scalable POI data integration workflows built on top of state-of-the-art software for geospatial Linked Data. The application abstracts and hides away the underlying complexity, automates quality-assured integration, scales efficiently for world-scale integration tasks and lowers the entry barrier for end-users. Validated against real-world POI datasets in several application domains, our system has shown great potential to address the requirements and needs of cross-sector, cross-border and cross-lingual integration of Big POI data.

@inproceedings{slipo2019, abstract = {Point of Interest (POI) data constitute the cornerstone of any application, service or product even remotely related to our physical surroundings. From navigation applications to social networks, tourism, and logistics, we use POI data to search, communicate, decide and plan our actions. POIs are semantically diverse and spatio-temporally evolving entities, having geographical, temporal and thematic relations. Currently, integrating POI data to increase their coverage, timeliness, accuracy and value is a resource-intensive and mostly manual process, with no specialized software available to address the specific challenges of this task. In this paper, we present an integrated toolkit for transforming, linking, fusing and enriching POI data, and extracting additional value from them. In particular, we demonstrate how Linked Data technologies can address the limitations, gaps and challenges of the current landscape in Big POI data integration. We have built a prototype application that enables users to define, manage and execute scalable POI data integration workflows built on top of state-of-the-art software for geospatial Linked Data. The application abstracts and hides away the underlying complexity, automates quality-assured integration, scales efficiently for world-scale integration tasks and lowers the entry barrier for end-users. Validated against real-world POI datasets in several application domains, our system has shown great potential to address the requirements and needs of cross-sector, cross-border and cross-lingual integration of Big POI data.}, added-at = {2024-03-04T14:13:36.000+0100}, author = {Athanasiou, Spiros and Giorgos, Giannopoulos and Damien, Graux and Nikos, Karagiannakis and Jens, Lehmann and {Ngonga Ngomo}, Axel-Cyrille and Kostas, Patroumpas and Sherif, {Mohamed Ahmed} and Skoutas, Dimitrios}, bdsk-url-1 = {http://svn.aksw.org/papers/2019/EDBT\_SLIPO/public.pdf}, biburl = {https://www.bibsonomy.org/bibtex/2fa2105951c207595d645b7cb4596f083/aksw}, booktitle = {International Conference on Extending Database Technology 2019, EDBT19}, interhash = {9a6b75ca6270675010441414ff285c8f}, intrahash = {fa2105951c207595d645b7cb4596f083}, keywords = {2019 deer dice group\_aksw lehmann limes ngonga sherif simba slipo}, timestamp = {2024-03-04T14:13:36.000+0100}, title = {Big {POI} data integration with Linked Data technologies}, url = {http://svn.aksw.org/papers/2019/EDBT_SLIPO/public.pdf}, year = 2019 }