FiLiPo: A Sample Driven Approach for Finding Linkage Points between RDF Data and APIs (Extended Version)

TL;DR

FiLiPo is an automated system that finds linkage points between RDF knowledge bases and web APIs, enabling efficient data integration by modeling APIs as parameterized queries and automatically identifying valid inputs.

Contribution

The paper introduces FiLiPo, a novel sample-driven schema matching system that automates the discovery of linkage points between RDF data and APIs, outperforming existing methods.

Findings

FiLiPo achieves high precision and recall in linking RDF data with APIs.

It successfully models APIs as parameterized queries for better integration.

Outperforms current state-of-the-art systems in linkage accuracy.

Abstract

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. Since several data providers make their data publicly available only via Web APIs they also must be included in the integration process. However, APIs often come with limitations in terms of access frequencies and speed due to latencies and other constraints. On the other hand, APIs always provide access to the latest data. So far, integrating APIs has been mainly a manual task due to the heterogeneity of API responses. To tackle this problem we present in this paper the FiLiPo (Finding Linkage Points) system which automatically finds connections (i.e., linkage points) between data provided by APIs and local knowledge bases. FiLiPo is an open source sample-driven schema matching system that models API services as parameterized queries. Furthermore, our approach is able to find valid input values for APIs automatically (e.g. IDs) and can determine valid alignments between KBs and APIs. Our results on ten pairs of KBs and APIs show that FiLiPo performs well in terms of precision and recall and outperforms the current state-of-the-art system.