MRM3 : machine readable ML model metadata

Čop, Andrej (avtor), Bertalanič, Blaž (avtor), Grobelnik, Marko (avtor), Fortuna, Carolina (avtor)

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.

• Jezik: Angleški jezik
• Ključne besede: knowledge graphs, ontology, taxonomy, model metadata, neo4j, machine learning
• Tipologija: 1.08 - Objavljeni znanstveni prispevek na konferenci
• Organizacija: FRI - Fakulteta za računalništvo in informatiko
• Status publikacije: Objavljeno
• Različica publikacije: Objavljena publikacija
• Leto izida: 2025
• Št. strani: Str. 741-746
• PID: 20.500.12556/RUL-189415
• UDK: 004.8
• DOI: 10.1145/3711875.3736685
• COBISS.SI-ID: 251097347

Opomba

Podatek za številčenje strani ("Pages 741 - 746") je naveden na pristajalni strani prispevka (glej zgoraj izvorni URL). (Datum opombe: 6. 10. 2026)

• Datum objave v RUL: 06.10.2026

Gradivo je del monografije

• Naslov: MobiSys '25 : proceedings of the 23rd ACM International Conference on Mobile Systems, Applications, and Services
• Kraj izida: New York
• Založnik: The Association for Computing Machinery
• Leto izida: 2025
• ISBN: 979-8-4007-1453-5
• COBISS.SI-ID: 251089411

Licence

• Licenca: CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
• Povezava: http://creativecommons.org/licenses/by/4.0/deed.sl
• Opis: To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

• Jezik: Slovenski jezik
• Ključne besede: grafi znanja, ontologija, taksonomija, strojno učenje, metapodatki

Projekti

• Financer: ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
• Številka projekta: P2-0016
• Naslov: Komunikacijska omrežja in storitve

• Financer: EC - European Commission
• Program financ.: HE
• Številka projekta: 101096456
• Naslov: An Artificial Intelligent Aided Unified Network for Secure Beyond 5G Long Term Evolution
• Akronim: NANCY