FiLiPo: A Sample Driven Approach for Finding Linkage Points between RDF Knowledge Bases and Web APIs

Data integration is an important task in order to create comprehensive RDF Knowledge Bases. Many data sources are used to extend a given dataset or to correct errors in the data. Since several data providers make their data publicly available via Web APIs, they are used as a common external data source. The classical problems of data integration, i.e., how two different datasets can be mapped, remain. Furthermore, due to the heterogeneity of data structures, the integration of different datasets is a mainly manual task. In addition, Web APIs are often more restrictive than data dumps and of course slower to access due to latencies and other constraints. In this paper we present the FiLiPo (Finding Linkage Points) system to automatically find connections (i.e., linkage points) between the data of Web APIs and local Knowledge Bases. FiLiPois a sample-driven schema matching system, which modelsWeb API services as parameterized queries. These Web API services return single records which contain a view of the Web API data schema. Furthermore, our approach is able to find valid input values for Web API services automatically (e.g. IDs) and can determine combined linkage points (e.g. first and last name) despite different structures. Our results on seven real world API services with two local databases show that our linkage point detection algorithm performs well in terms of precision. FiLiPo was able to achieve a average f1 score of 0.88 while the chosen baseline only achieved 0.74.