Looking for New Year’s metadata resolutions? How about: Stop using sentences that include the words “minimum metadata” without specifying a use case. Sentences that include the words “minimum metadata” come up frequently in metadata discussions, usually in the context of what a data provider wants to provide or, even more common, in the context of what should be expected of them.

DataCite subject metadata can play an important role in dataset classification and discovery, but these elements are uncommon in the repository and need some improvements. Establishing metrics for completeness and quality is an important first step in the improvement process.

Non-unique organizations and acronyms can cause problems in ROR searches. Use supporting information if you have it to get better results. If not, beware of theses gotchas.

Let’s recognize leaders in the adoption of organizational identifiers in DataCite metadata. They are making tracks for us to follow!

Adopting organizational identifiers (RORs) in existing metadata may not be as hard as we think for DataCite members that only have a few affiliations in their metadata. However, even in these cases, some challenges remain.

Many groups are interested in augmenting their affiliation metadata with RORs and it seems that a list of organization names is the right input to that process... Alas, we know that affiliations are a swamp filled with gotcha's. It turns out that an unexpected (really?) number of organization names resolve to multiple RORs. Actually, almost 800 of them!

Clear and specific community recommendations for FAIR metadata in multiple dialects are rare and necessary for measuring progress towards evaluating and improving metadata in many repositories. We propose an initial set of concepts and an evaluation of the DataCite metadata collection for essential metadata elements that support Findability.

Join the community playing The Metadata Game!

The DataCite metadata model includes rich information about over 18 million items with DOIs. The schema includes at least four elements that describe organizations: publisher, creator, contributor, and fundingReference. Each of these elements has interesting characteristics. Let’s explore them!

Identifying good examples of consistent affiliation information providers within the Crossref community and automating the identification of organizations are important steps towards the goal of assigning identifiers (e.g. RORs) to these organizations.

I recently introduced a simple visualization of data from the CrossRef Participation Reports that provides quantitative insight into how completeness of CrossRef metadata collections with respect to eleven key metadata elements has changed between the backfile and the current record collections.