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5 results for “SHACL shapes”
Design of an Ontology-Driven Constraint Tester (ODCT) and Application to SAREF & Smart Energy Appliances: Datasets, SHACL Shapes, Demo Video of Web Application, and Detailed Performance Reports
<h2>Description</h2> <p>This repository presents the resources used for validating the compliance of <strong>smart energy appliances</strong> against the <strong>Smart Appliances REFerence (SAREF)</strong> ontology and its extension <strong>SAREF4ENER</strong>, as part of the <strong>Ontology-Driven Constraint Tester (ODCT)</strong> project. The ODCT tool is specifically designed to ensure <strong>semantic interoperability</strong> and adherence to standardized ontological frameworks, which are crucial for integrating smart devices into modern energy management systems.</p> <h2>ODCT Overview</h2> <p>The <strong>Ontology-Driven Constraint Tester (ODCT)</strong> is a robust framework created to validate datasets against ontologies defined by <strong>SAREF</strong> and <strong>SAREF4ENER</strong>, both established under ETSI SmartM2M. This tool has been applied to the <strong>Flexible Start use case</strong> from the <strong>Joint Research Centre’s (JRC) Code of Conduct for Energy Smart Appliances</strong>. The ODCT tool ensures that smart devices like energy-efficient washing machines, thermostats, and connected lighting operate in compliance with established ontologies, thereby enhancing their <strong>interoperability</strong> within energy management systems and smart grids.</p> <h2>Repository Contents</h2> <p>This repository contains essential resources used in the ODCT compliance testing process:</p> <ul> <li> <p><strong>Compliant Dataset</strong>: This dataset represents a fully compliant scenario where no errors are present in the smart energy appliances’ profiles, demonstrating the ODCT’s accuracy under ideal conditions.</p> </li> <li> <p><strong>Modified Datasets</strong>: These datasets introduce various types of errors to showcase ODCT’s ability to handle diverse compliance scenarios:</p> <ol> <li><strong>Modified Dataset 1</strong>: Introduces type mismatches and spelling errors in key attributes.</li> <li><strong>Modified Dataset 2</strong>: Contains extraneous properties and missing required properties, including details about energy consumption and efficiency class.</li> <li><strong>Modified Dataset 3</strong>: Includes both extraneous and missing properties, and additional priority levels for energy profiles.</li> </ol> </li> <li> <p><strong>SHACL Shapes</strong>: The SHACL shapes used in the compliance testing for both SAREF and SAREF4ENER ontologies are included in this repository to allow reproducibility of the validation process.</p> </li> </ul> <ul> <li> <p><strong>Error Detection Results and Performance Reports</strong>: After conducting compliance tests using ODCT we got the Results and Performance Reports, the repository includes comprehensive reports detailing the results. These reports highlight the types of errors detected and provide a performance analysis of the tool under various scenarios.</p> </li> <li> <p><strong>Demonstration Video</strong>: A video is provided to guide users through the <strong>ODCT web application</strong>, showcasing how the tool detects errors and generates detailed compliance reports based on smart energy appliance datasets.</p> </li> </ul> <h2>Background</h2> <p>The integration of smart energy appliances into modern power grids is key to improving <strong>energy management</strong> and supporting <strong>sustainability goals</strong> like the <strong>European Green Deal</strong>. However, ensuring that these devices communicate effectively and conform to <strong>standardized protocols</strong> is a challenge. The <strong>ODCT</strong> tool addresses this challenge by providing a rigorous, ontology-based validation framework that is both <strong>protocol-agnostic</strong> and <strong>technology-flexible</strong>.</p> <p>This work is grounded in the broader context of <strong>global warming</strong> and the need for <strong>energy efficiency</strong> and <strong>demand-side flexibility</strong> in energy systems. By ensuring compliance with <strong>SAREF</strong> and <strong>SAREF4ENER</strong>, ODCT supports the EU’s ambitions for <strong>carbon neutrality</strong> by 2050, contributing to a connected, efficient, and sustainable energy ecosystem.</p> <h2>Methodology</h2> <p>ODCT uses a structured methodology that involves:</p> <ol> <li><strong>Generating relevant datasets</strong> for validation.</li> <li><strong>Defining SHACL shape constraints</strong> based on ontologies.</li> <li><strong>Developing a user-friendly web application</strong> to facilitate compliance testing.</li> <li><strong>Performing compliance tests</strong> that validate datasets against SHACL shapes, ensuring interoperability and adherence to energy management standards.</li> </ol> <h2>Why It Matters</h2> <p>Researchers and developers working on smart energy appliances will benefit from ODCT by:</p> <ul> <li>Ensuring their devices meet standardized ontological requirements for <strong>interoperability</strong>.</li> <li>Reducing <strong>compliance issues</strong> in the development phase, leading to smoother integration into energy management systems.</li> <li>Supporting the <strong>sustainability efforts</strong> by enhancing device communication in <strong>smart grids</strong>.</li> </ul> <p>This repository showcases the potential of ODCT in fostering <strong>data accuracy</strong>, <strong>semantic interoperability</strong>, and <strong>compliance</strong> with essential energy standards. It offers comprehensive resources for furthering research and development in the field of smart energy appliances and energy management.</p>
Automatically Extracted SHACL Shapes for WikiData, DBpedia, YAGO-4, and LUBM & Associated Coverage Statistics
<p>The uploaded datasets contain <strong>automatically extracted </strong>SHACL shapes for the following datasets:</p> <ul> <li>WikiData (the truthy dump from September 2021 filtered by removing non-English strings) [1]</li> <li>DBpedia [2]</li> <li>YAGO-4 [3] </li> <li>LUBM (scale factor 500) [4]</li> </ul> <p>The validating shapes for these datasets are generated by a program that parses the corresponding RDF files (in `.nt` format). The extracted shapes encode various SHACL constraints, e.g., sh:minCount, sh:path, sh:class, sh:datatype etc. For each shape we encode coverage in terms of number of entities satisfying such shape, this information is encoded using the <a href="http://vocab.deri.ie/void#entities">void:entities</a> predicate. </p> <p>We have provided as executable Jar file the program we developed to extract these SHACL shapes.<br> More details about the datasets used to extract these shapes and <em>how to run the Jar</em> are available on our GitHub repository <a href="https://github.com/dkw-aau/qse">https://github.com/dkw-aau/qse</a>.</p> <p>Read more about our Quality Shapes Extraction (QSE) tool on our website <a href="https://relweb.cs.aau.dk/qse/">https://relweb.cs.aau.dk/qse/</a></p> <p>[1] Vrandečić, Denny, and Markus Krötzsch. "Wikidata: a free collaborative knowledgebase." Communications of the ACM 57.10 (2014): 78-85.</p> <p>[2] Auer, Sören, et al. "Dbpedia: A nucleus for a web of open data." The semantic web. Springer, Berlin, Heidelberg, 2007. 722-735.</p> <p>[3] Pellissier Tanon, Thomas, Gerhard Weikum, and Fabian Suchanek. "Yago 4: A reason-able knowledge base." European Semantic Web Conference. Springer, Cham, 2020.</p> <p>[4] Guo, Yuanbo, Zhengxiang Pan, and Jeff Heflin. "LUBM: A benchmark for OWL knowledge base systems." Journal of Web Semantics 3.2-3 (2005): 158-182.</p>
Astrea: automatic generation of SHACL shapes from ontologies
<p> This resource is Astrea-KG, a Knowledge Graph that publishes a set of mappings that encode the equivalent conceptual restrictions among ontology constraint patterns and SHACL constraints patterns.</p>
Efficient Validation of SHACL Shapes with Reasoning
<p>This dataset comprises the experimental data used in our paper, "Efficient Validation of SHACL Shapes with Reasoning".</p> <p>By making these datasets publicly available, we aim to facilitate other researchers in reproducing our experimental results or conducting further research based on our work.</p>
DBpedia SHACL shapes
<p>SHACL Shapes extracted from the DBpedia ontology.</p>
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