MLentory Technical Design Document
MLentory (https://mlentory.zbmed.de/) is centered around information on ML models, how to harmonize that data, and how to make it available and searchable on an FDO (FAIR Digital Object) registry. Our goal is to build a system that extracts ML (Machine Learning) model information from different platforms, normalizes that data in a common format, stores it, and shares it in a FDO registry to facilitate Information Retrieval and comparison/recommendation systems. This TDD will help new contributors understand and old ones remember what decisions were made on the system's design, the motivation behind them, and their impact. The document focuses on the design of the ETL pipeline to collect, transform, and store extracted information. Funding. MLentory FDO registry is part of the NFDI4DataScience consortium, funded by the Deutsche Forschungsgemeinschaft (DFG —German Research Foundation) under the grant number 460234259. This work was supported by the de.NBI Cloud within the German Network for Bioinformatics Infrastructure (de.NBI) and ELIXIR-DE (Forschungszentrum Jülich and W-de.NBI-001, W-de.NBI-004, W-de.NBI-008, W-de.NBI-010, W-de.NBI-013, W-de.NBI-014, W-de.NBI-016, W-de.NBI-022).
Institutions
- ZB MED - Information Centre for Life Sciences (DE)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-05-26
- DOI
- https://doi.org/10.5281/zenodo.16943738
- Primary Topic
- Geochemistry and Geologic Mapping
- Type
- article
- Field-Weighted Citation Impact
- 0.00