Semantic Web resources and Machine Learning systems - Knowledge Graph (SWeMLS-KG)

This resource is part of our submission to ESWC 2023 resource track, which includes: Datasets:<br> - Folder "pattern" - a set of SWeMLS patterns represented based on OPMW and P-Plan ontology,<br> - Folder "shapes" - a set of SHACL constraints to check the conformance of SWeML Systems against SWeMLS patterns as well as a set of SHACL-AF rules to generate links between system components,<br> - File "swemls-ontology.ttl" - an ontology to represent Semantic Web resources and Machine Learning systems (SWeMLS),<br> - File "swemls-instances.ttl" - a set of triples representing the extracted metadata from 476 SWeML systems and papers,<br> - File "swemls-kg.ttl" - an integrated and validated KG containing all above files, including enrichment from SHACL-AF rules using "swemls-toolkit" [2]. These resources are produced based on the result of the Systematic Mapping Study (SMS) reported in [1]. The latest SNAPSHOT-version of the resource can be accessed through our resource landing page: https://w3id.org/semsys/sites/swemls-kg/ [1] Breit, A., Waltersdorfer, L., Ekaputra, J.F., Sabou, M., Ekelhart, A., Iana, A., Paulheim, H., Portisch, J., Revenko, A., Ten Teije, A., van Harmelen, F.: Combining Machine Learning and Semantic Web -A Systematic Mapping Study (under review). ACM CSUR (2022)<br> [2] Source code of swemls-toolkit is available at: https://github.com/semanticsystems/swemls-toolkit