Research Fields
Each dataset in Scholar Data is assigned a research field, which is used to normalize D-index and S-index scores so they remain comparable across disciplines. The idea is that a dataset in a field with low data sharing rates and inconsistent citation practices should not be penalized relative to one in a field where sharing and citation is common practice. This page describes how a research fields are assigned.
Classification System
Research fields in Scholar Data follow the OpenAlex topics and domains taxonomy, a four-level hierarchy of 4,516 topics grouped into 252 subfields, 26 fields, and 4 top-level domains. Scholar Data uses the subfield level for normalization, as our analysis shows that it best captures the variation in data sharing practices across research communities.
How Fields Are Assigned
Field assignments come from two sources:
- OpenAlex: where a dataset is indexed in OpenAlex, its topic and subfield classification are used directly.
- Custom classifier: for datasets not indexed in OpenAlex, a custom topic classifier maps dataset metadata (title, description, and keywords) to the OpenAlex taxonomy. More details are available in the GitHub repository of the classifier code.
Note: A small number of datasets with non-Latin script metadata are not classified and remain unassigned.
Coverage
| Source | Fields Assigned |
|---|---|
| DataCite | 48,992,829 |
| EMDB | 51,645 |
| Total | 49,044,474 |
Incorrect Field Assignment?
Field assignments are automated and may occasionally be inaccurate, particularly for interdisciplinary datasets. In the future, we will implement a process for users to suggest a correction.