20.500.12556/RUL-189415 MRM3 machine readable ML model metadata As the complexity and number of machine learning (ML) models grows, well-documented ML models are essential for developers and companies to use or adapt them to their specific use cases. Model metadata, already present in unstructured format as model cards in online repositories such as Hugging Face, could be more structured and machine readable while also incorporating environmental impact metrics such as energy consumption and carbon footprint. Our work extends the existing State of the Art by defining a structured schema for ML model metadata focusing on machine-readable format and support for integration into a knowledge graph (KG) for better organization and querying, enabling a wider set of use cases. Furthermore, we present an example wireless localization model metadata dataset consisting of 22 models trained on 4 datasets, integrated into a Neo4j-based KG with 113 nodes and 199 relations. knowledge graphs ontology taxonomy model metadata neo4j machine learning grafi znanja ontologija taksonomija strojno učenje metapodatki true false true Angleški jezik Slovenski jezik Neznano 2026-10-06 15:03:46 2026-10-06 15:03:49 2026-10-07 04:27:16 0000-00-00 00:00:00 2025 0 0 Podatek za številčenje strani ("Pages 741 - 746") je naveden na pristajalni strani prispevka (glej zgoraj izvorni URL). (Datum opombe: 6. 10. 2026) Str. 741-746 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004.8 10.1145/3711875.3736685 251097347 251089411 3711875.3736685.pdf 3711875.3736685.pdf 1 745DFF45EC13A913B96FE971B35A56B1 5ba11d23382718cf62de610fbc813d7a0d8ff61bd36b43fb2cca703778f35e27 e5d61561-c187-11f1-8bc5-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=249929 https://dl.acm.org/doi/10.1145/3711875.3736685 1 40befe4b-c186-11f1-8bc5-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=249928 Fakulteta za računalništvo in informatiko 0 0 0