DataCite is an international organization responsible for the DOIs (Digital Object Identifiers) issued for research datasets.  For each DOI issued, DataCite requires the data publisher to create and submit to DataCite descriptive metadata that can aid resource discovery.  These metadata elements, divided into mandatory and option ones, are specified in a document that is periodically updated by DataCite, the most recent version of which is the DataCite Metadata Kernel, v2.2.

In July 2012, Silvio Peroni and I revised and expanded the DataCite Ontology, as described in an earlier blog post, and then used it to map include all the mandatory and optional DataCite metadata terms from the DataCite Metadata Kernel, v2.2 to RDF, as described in the previous blog post.

To facilitate the creation of metadata compliant with the DataCite Metadata Kernel v2.2, Tanya Gray and I have separately created a DataCite Metadata Input Form, by adapting the metadata input system that she had previously created to permit entry of MIIDI metadata (Minimal Information to record an Infectious Disease Investigation).

The DataCite Metadata Input Form is freely available on the Web at http://www.miidi.org/datacite.  Backed by an XML model that is interpreted by XForms and Orbeon Forms to create the displayed Web form dynamically, this form contains an input field for each of the DataCite metadata elements, both the main terms and their sub-terms, in numerical order.  Where appropriate, each element contains a drop-down menu that permits the user to choose one from the list of allowed input values specified by the DataCite Metadata Kernel v2.2, as shown in the following screen shot:

Screen shot of the initial metadata entry fields in the DataCite Metadata Entry Form

The entered DataCite metadata are saved as an XML file on the user’s local hard drive, with a name and directory location of the user’s choosing.   Optionally, the metadata can also be saved in other formats including HTML, PDF and Kipling XML (a subset of the NLM Journal Publishing DTD version 3.0 that is the input format for Annotum, a publishing system based on the WordPress blogging platform).  Additionally, the metadata can also be converted to RDF using an XSLT transformation based on the mapping of the DataCite Metadata Kernel, v2.2 to RDF described in the previous blog post.

We commend use of this service to researchers wishing to create DataCite metadata to accompany datasets sent to data repositories, and to repository creators wishing to create or supplement DataCite metadata for a newly submitted dataset they will archive and publish, to send to DataCite when registering a DOI for that dataset.

Our system uses a server-client software system that is more fully described here.  Because of this, there is a possibility that our server could potentially suffer from usage overload that might lead to unacceptably slow response times.  We have not experienced such slow response times while testing, but would like to hear from users both about any performance issues experienced, and about suggestions for improvement.

David Shotton              ([email protected])

Tanya Gray                  ([email protected])