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Enabling Automatic Discovery and Querying of Web APIs at Web Scale using Linked Data Standards

Abstract : To help in making sense of the ever-increasing number of data sources available on the Web, in this article we tackle the problem of enabling automatic discovery and querying of data sources at Web scale. To pursue this goal, we suggest to (1) provision rich descriptions of data sources and query services thereof, (2) leverage the power of Web search engines to discover data sources, and (3) rely on simple, well-adopted standards that come with extensive tooling. We apply these principles to the concrete case of SPARQL micro-services that aim at querying Web APIs using SPARQL. The proposed solution leverages SPARQL Service Description, SHACL, DCAT, VoID, and Hydra to express a rich functional description that allows a software agent to decide whether a micro-service can help in carrying out a certain task. This description can be dynamically transformed into a Web page embedding rich markup data. This Web page is both a human-friendly documentation and a machine-readable description that makes it possible for humans and machines alike to discover and invoke SPARQL micro-services at Web scale, as if they were just another data source. We report on a prototype implementation that is available on-line for test purposes, and that can be effectively discovered using Google's Dataset Search engine.
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Contributor : Franck Michel <>
Submitted on : Thursday, March 7, 2019 - 5:41:36 PM
Last modification on : Tuesday, May 26, 2020 - 6:50:56 PM
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Franck Michel, Catherine Faron Zucker, Olivier Corby, Fabien Gandon. Enabling Automatic Discovery and Querying of Web APIs at Web Scale using Linked Data Standards. WWW 2019 - LDOW/LDDL Workshop of the World Wide Web Conference, May 2019, San Francisco, United States. ⟨10.1145/3308560.3317073⟩. ⟨hal-02060966⟩



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