Published May 28, 2026
| Version 2.0.0
Dataset
Open
SciNoBo Field of Science Taxonomy
Authors/Creators
-
1.
Institute for Language and Speech Processing
-
2.
Athena Research and Innovation Center In Information Communication & Knowledge Technologies
- 3. Institute of Language and Speech Processing (ILSP)
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4.
OpenAIRE Non-Profit Civil Partnership
Description
The taxonomy has 6 Levels (L1-L6). The levels from L1-L3 are static and stem from the OECD and ScienceMetrix taxonomy. The rest of the levels are algorithmically constructed utilizing publication-to-publication and venue-to-venue citation graphs as well as clustering and topic modelling algorithms. The resulting L5s are topics stemming from topic modelling. We utilize open-source LLMs and more specifically Llama3 to automatically assign a scientific name to each L5 topic.
For more information please visit:
- Github Repository: https://github.com/iNoBo/scinobo-fos-taxonomy
- Version 1 interactive viewer: Markmap URL
- Version 2 interactive viewer: Markmap URL
Files
fos_taxonomy_v0.1.1.json
Files
(70.8 MB)
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Additional details
Funding
Software
- Repository URL
- https://github.com/iNoBo/scinobo-fos-taxonomy
- Programming language
- Python
- Development Status
- Active
References
- Kotitsas S, Pappas D, Manola N and Papageorgiou H (2023) SCINOBO: a novel system classifying scholarly communication in a dynamically constructed hierarchical Field-of-Science taxonomy. Front. Res. Metr. Anal. 8:1149834. doi: 10.3389/frma.2023.1149834
- Nikolaos Gialitsis, Sotiris Kotitsas, and Haris Papageorgiou. 2022. SciNoBo: A Hierarchical Multi-Label Classifier of Scientific Publications. In Companion Proceedings of the Web Conference 2022 (WWW '22). Association for Computing Machinery, New York, NY, USA, 800–809. https://doi.org/10.1145/3487553.3524677