A quick post about non-unique ROR Organization names. 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!

This post was first published on the DataCite blog on September 27, 2019. Since Wilkenson et al., 2016 introduced the FAIR Principles, discussions and implementation guidelines have been published in almost every possible context.

Last summer John Chodaki challenged me to develop something fun for a Metadata2020 presentation during the FORCE18 meeting in Montreal. I have always enjoyed games, so a collaborative game that could engage teams in the metadata creation process seemed like a natural candidate. There were many metadata geeks and lots of ideas about what such a game would look like.

In my last blog I introduced Metadata Archeology with a description of digging around in Crossref metadata for affiliations associated with authors of work published in the Dryad Data Repository. I showed how the Crossref Participation Reports could be used for an initial survey of Crossref metadata like satellite images are being used in the GlobalXplorer project to find ancient sites in Peru.

One of the interesting challenges encountered in the migration of Dryad metadata technology into the California Digital Library is the identification of organizations associated with the research data archived in the Dryad Repository. This information is not included in the original Dryad metadata, so digging around for it, i.e. “metadata archeology”, is required.

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.

I recently introduced a simple metric for measuring metadata collection completeness with respect to elements in the CrossRef Participation Reports. The suggestion of this metric immediately led to speculation about relationships between collection size and completeness. Small collections include fewer records – are they more likely to be complete? Publishers with large collections have more resources – do they have more complete metadata?

All scientific communities have been linking research together for many years using references to related work in articles. Recently these communities are exploring options for linking to datasets and software. As part of this effort, the CodeMeta Project recently proposed a vocabulary for metadata for code based on schema.org.

Over the last several years CrossRef has grown into one of the largest and most significant metadata repositories in the world. It contains over 100,000,000 registered content items and offers many services to help members and other users take advantage of that content. In addition to managing registered content, CrossRef makes links between resources. It is the connective tissue for the web of scholarly communications.

California Digital Library (CDL) and Dryad recently announced a partnership to address researcher needs and to “move the needle” on digital data adoption throughout the scholarly research community by working together to understand and respond to researcher needs for high-quality scientific data publishing infrastructures.

High-quality metadata can help users discover data and other resources in many ways. Good titles, abstracts, and keywords, along with spatial and temporal extents, go a long way with many search strategies. Adding schema.org metadata to landing pages can also help. A second discovery strategy, more like browsing, comes into play once someone finds something interesting.