affiliation – InfoDoc MicroVeille

Authors : Hanna Hottenrott, Michael E. Rose, Cornelia Lawson

This study provides the first systematic, international, large-scale evidence on the extent and nature of multiple institutional affiliations on journal publications. Studying more than 15 million authors and 22 million articles from 40 countries we document that: In 2019, almost one in three articles was (co-)authored by authors with multiple affiliations and the share of authors with multiple affiliations increased from around 10% to 16% since 1996.

The growth of multiple affiliations is prevalent in all fields and it is stronger in high impact journals. About 60% of multiple affiliations are between institutions from within the academic sector.

International co-affiliations, which account for about a quarter of multiple affiliations, most often involve institutions from the United States, China, Germany and the United Kingdom, suggesting a core-periphery network. Network analysis also reveals a number communities of countries that are more likely to share affiliations.

We discuss potential causes and show that the timing of the rise in multiple affiliations can be linked to the introduction of more competitive funding structures such as “excellence initiatives” in a number of countries. We discuss implications for science and science policy.

URL : The rise of multiple institutional affiliations in academia

DOI : https://doi.org/10.1002/asi.24472

Author/Auteur : Niek Van Wettere

This article aims to evaluate how and to what extent metadata of datasets indexed in DataCite offer clear human- or machine-readable information that enables the research data to be linked to a particular research institution.

Two main pathways are explored. First, researchers can encode their affiliation information at the moment of data submission. This can be done by means of free-text metadata fields or via the inclusion of identifiers such as GRID/ROR and ORCID. Second, affiliation information can be traced indirectly through linking between a dataset and associated publications, given that the metadata of publications is often more explicit about affiliation information than the metadata of datasets.

Both pathways of affiliation information encoding are evaluated on the basis of metadata pertaining to datasets created at the five Flemish universities. It is shown that good practices such as encoding of affiliation information in a dedicated metadata field or inclusion of ORCID in the metadata are on the rise, but could be expanded further.

Finally, the establishment of links between datasets and related publications is often lacking in dataset metadata, although there are important differences between data repositories, as is also demonstrated in a more data-intensive follow-up analysis based on random samples of metadata records.

It is important that data repositories address this issue by providing a metadata field clearly dedicated to associated publications, prominently displayed on the landing page of the dataset.

URL : Affiliation Information in DataCite Dataset Metadata: a Flemish Case Study

DOI : http://doi.org/10.5334/dsj-2021-013