Cluster Analysis of Open Research Data: A Case for Replication Metadata

Research data are often released upon journal publication to enable result verification and reproducibility. For that reason, research dissemination infrastructures typically support diverse datasets coming from numerous disciplines, tabular program code audio-visual files. Metadata, or about data, is critical making outputs adequately documented FAIR. Aiming contribute the discussions on development of metadata for outputs, I conducted an exploratory analysis determine how cluster based what researchers organically deposit together. use content over 40,000 Harvard Dataverse repository as my sample analysis. find majority clusters formed by single-type datasets, while in rest sample, no meaningful can be identified. interpretation, standard employed DataCite, a leading organization documenting scholarly record, map existing resource types results. About 65% described with (such Dataset, Software orReport), would require aggregate types. Though DataCite supports type such Collection, argue significant number particular those containing both files (about 20% sample), more accurately Replication type. Such particularly useful facilitating