Selected facets for DataCite Repositories

What is a facet? A facet is a metadata element, usually from a controlled list, that provides counts of records in a query result with particular values for the metadata element. The DataCite JSON Response includes data on a variety of facets for each query done using the DataCite API. Repository Facets DataCite Commons uses facets on repository pages to provide an overview of repositories. For example, the Metadata Game Changers Commons page shows publication year, work types, licenses, creators and contributors, and some other facets as graphics and lists. The facets provided by DataCite can be used to 1) understand characteristics of DataCite metadata, 2) understand some aspects of repository completeness, and 3) provide overviews of repositories. Using Facets to Understand DataCite Metadata DataCite includes facets and facet values in all query results, so they are a useful tool for answering some "big picture" questions about DataCite metadata. Some of these questions were explored during 2022 in DataCite Facets: Understanding DataCite Usage using a tool called DataCite Facets. DataCite Facets and Repository Overviews DataCite facets can be used to provide overviews of any DataCite Repository and understand some characteristics of the repositories. They can also be used, in some cases, to provide insights into some aspects of repository completeness. Repository Facets and Metadata Completeness Many useful repository measures focus on completeness of the metadata, i.e., the portion of records in the repository that include some metadata element. The DataCite facet data can provide some insight into completeness, but we must keep in mind that the facet data are limited to top ten values for most facets (except for published and resourceTypes, which can be > 10). The blog DataCite Facets and Metadata Completeness describes how some facets can be used to provide insights into metadata completeness. This dataset provides selected facets downloaded using the DataCite API and associated statistics as a comma-separated-value (CSV) file. Column definitions: The dataset includes a number of columns for the selected facets: Statistic Description number The number of facet values max The number of occurrences of the most common facet value common The most common facet value total The total number of records in the top 10, i.e. the total listed in the facets homogeneity (HI) An indicator of homogeneity of the facet: maximum count / total count (0.1 = uniform, 1.0 = single item) coverage The % of all records covered by the top 10 (numbers close to 100% are good)