Knowledge Graphs (KGs) that publish RDF data modelled using ontologies in a wide range of domains have populated the Web. The SHACL language is a W3C recommendation that has been endowed to encode a set of either value or model data restrictions that aim at validating KG data, ensuring data quality. Developing shapes is a complex and time consuming task that is not feasible to achieve manually. This article presents two resources that aim at generating automatically SHACL shapes for a set of ontologies: (1) Astrea-KG, a KG that publishes a set of mappings that encode the equivalent conceptual restrictions among ontology constraint patterns and SHACL constraint patterns, and (2) Astrea, a tool that automatically generates SHACL shapes from a set of ontologies by executing the mappings from the Astrea-KG. These two resources are openly available at Zenodo, GitHub, and a web application. In contrast to other proposals, these resources cover a large number of SHACL restrictions producing both value and model data restrictions, whereas other proposals consider only a limited number of restrictions or focus only on value or model restrictions.
Demand Response (DR) gains increasing attention as a core building block of smart grids. Advanced ICT systems have been made available in the last decades and have been employed already in commercial energy markets. As more and more hardware and software solutions are flooding the market, the need for interoperability among systems has become a necessity. Building upon OpenADR, a well-known standard for DR, this work presents its semantic enrichment towards transforming it into an ontology (publicly available), which ultimately enables semantic interoperability among various DR stakeholders and systems and other semantic-related features like data validation, reusing terms and integration with other standard ontologies. Following the Linked Open Terms methodology, a detailed description of the main OpenADR services is presented, encoded in OWL, along with needed extensions that derive from other well-known ontologies. By introducing an OpenADR ontology, the adoption and deployment of OpenADR in both research and industrial implementations is expected to expand, ultimately promoting significantly semantic interoperability in DR systems.
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