Abstract
In this paper, we demonstrate DataSpecer, a tool for effortless management of data specifications based on a domain ontology. Using DataSpecer, the users can generate technical artifacts such as data schemas, e.g., in JSON Schema or XML Schema, and human-readable documentation for a specific dataset based on the provided ontology while maintaining the semantic mapping from the generated artifacts to the ontology. This significantly eases the task of developing data specifications and keeping the corresponding technical artifacts consistent in the process. The tool is based on a previously studied model-driven development (MDD) approach [5] that divides data modeling into layers. This approach was already partially implemented in the tools XCase [2] and eXolutio [3], however, only for XML Schemas and only based on a manually created model, not on an existing domain ontology. Our current tool provides support for the implementation of artifact generators for any target format, including human-readable documentation, and supports domain ontologies as the starting point of the MDD. The tool is already in use in Czechia with the Semantic Government Vocabulary (SGOV) [4] serving as the domain ontology.
This work was partially supported by the Charles University grant SVV 260588.
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Stenchlák, Š., Nečaský, M., Škoda, P., Klímek, J. (2022). DataSpecer: A Model-Driven Approach to Managing Data Specifications. In: Groth, P., et al. The Semantic Web: ESWC 2022 Satellite Events. ESWC 2022. Lecture Notes in Computer Science, vol 13384. Springer, Cham. https://doi.org/10.1007/978-3-031-11609-4_10
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