2026-10-28 –, Naturalis 02
The DOI registration agency DataCite maintains the largest collection of metadata about research data and is uniquely positioned to facilitate activities like data discovery and scientometric research. However, previous research has highlighted that DataCite metadata is often incomplete.
In this session, you will learn whether this problem can be addressed by improving metadata flows from disciplinary research data repositories to DataCite through optimized schema crosswalks.
The DOI registration agency DataCite maintains the largest collection of metadata about research data and is uniquely positioned to facilitate activities like data discovery and scientometric research. However, previous research has highlighted that DataCite metadata is often incomplete.
In this session, you will learn whether this problem can be addressed by improving metadata flows from disciplinary research data repositories to DataCite through optimized schema crosswalks.
Eight disciplinary research data repositories from the social sciences and the geosciences were selected for the study. The analysis covers how disciplinary research data repositories simultaneously use disciplinary metadata schemas and the DataCite Metadata Schema, and how two metadata records describing the same dataset compare.
The results show that considerable improvements are possible by optimizing crosswalks to the DataCite Metadata Schema. However, the parallel use of disciplinary and multidisciplinary metadata records at research data repositories is complex. For example, discpline matters, even for multidisciplinary metadata: some elements in the Datacite Metadata Schema are more applicable to certain disciplines; this has a significant effect on the completeness of DataCite metadata.
A temporal analysis also highlights that metadata workflows are diverse, and in some cases, suboptimal crosswalks are likely not the cause of incomplete DataCite metadata.
Comparing the disciplinary metadata schemas and the DataCite Metadata Schema on a structural level reveals that most differences between the disciplinary metadata schemas and the DataCite Metadata Schema are the result of different approaches to modelling statements about datasets, not the lack of opportunity to express them.
However, the element sets of both disciplinary metadata schemas and the DataCite Metadata Schema could be extended to describe datasets in more detail.
These observations demonstrate that disciplinary and multidisciplinary metadata schemas serve distinct purposes. Disciplinary repositories should take full advantage of the opportunities both options provide, because the most complete set of statements about datasets can be achieved by combining both disciplinary and multidisciplinary metadata schemas.
Dorothea Strecker is a researcher in the research group Information Management at the Berlin School of Library and Information Science, Humboldt-Universität zu Berlin.
Her main research interests are open research information, information infrastructures and metadata for research data.
She is a member of the re3data Working Group, the DataCite Metadata Working Group and the ScholCommLab.