Identifying data reuse is challenging, due to technical reasons, and, in particular, incorrect citation practices among scholars. This paper aims to propose an automatic method to track the reuse of data deposited in the archives joined to the CESSDA (Consortium of European Social Science Data Archives) infrastructure. The paper also offers an overview on the identified data to understand the characteristics of the most reused data sets.
https://doi.org/10.1108/DLP-07-2024-0112
| Artificial Intelligence |
| Research Data Curation and Management Works |
| Digital Curation and Digital Preservation Works |
| Open Access Works |
| Digital Scholarship |
