Data · dataset · 2026
HugSelect Datasets
Listed in Teesside University Research Data Repository
HugSelect Dataset is a structured dataset supporting the development and evaluation of HugSelect, a multi-criteria decision-making (MCDM) framework for foundation model selection.
Description
It enables reproducible research on transparent, task-specific recommendation of AI foundation models. The dataset integrates heterogeneous information from Hugging Face model repositories, including: (1) raw metadata, model descriptions, and community reviews.
(2) processed representations generated through automated pipelines, where unstructured information is transformed into standardised features such as functional features and quality mappings. The dataset also includes information regarding the 3 step evaluations of the HugSelect: (3) pipeline validation data, which is used to assess the accuracy and reliability of feature extraction methods (4) a case study dataset containing task-based scenarios with reference model selections and evaluation of recommendations with the curated dataset.
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(5) evaluation results from TAM based user studies involving AI practitioners. Data is provided in structured formats (CSV/JSON) and organized into raw data, processed data, validation results, case studies, and user study. Limitations include potential noise in extracted features due to variability of LLM outputs and temporal variability due to evolving model repositories.
Links
Where it is published
- DOI doi.org/10.17632/9xbhyxr7tf.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/9xbhyxr7tf.1 | 9 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:field:430201 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Repository Studies'] |
| concepts[field].anzsrc:group:4602 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Artificial Intelligence'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |