What Metadata will be used? Are you using a |
Guidance Be prepared to identify a relevant standard. Best approach is If you need help selecting a Metadata standard consult a librarian. |
Metadata is Data about Data”. It enables discovery systems, citation systems (i.e. any computerized system) “understand” what specifically it is dealing with. It makes your data, publications, learning objects, (etc) 'independently understandable'.
Basic Metadata Elements generally include:
Metadata that describes basic characteristics of the data, includes:
Who created the data
What the data file contains
When the data were generated
Where the data were generated
Why the data were generated
How the data were generated
Metadata is made up of a number of elements which can be categorised into the different functions they support. A metadata standard will normally support a number of defined functions, and will specify elements which make these possible. A metadata standard may support some or all of the following functions:
Well-structured metadata supports the long-term discovery and preservation of your research data. It allows the aggregation and simultaneous searching of research data from tens or hundreds or thousands of researchers. This is why domain-specific repositories typically require highly structured metadata - in the form of Metadata Standards - with your data submissions: it enables highly granular searches on their aggregated content.
Using established metadata standards will help make your data discoverable, citable, and ready-to-use by others.
Metadata that adheres to the F.A.I.R. Principles enables machines - like Search Engines - to understand enough about your Data. This in turn makes your data:
Metadata that adheres to Discipline Specific Metadata Standards (see below) makes identifying appropriate resources easier.
Together with Persistent Identifiers (PIDs) - such as digital object identifiers (DOIs) and researcher identifiers (ORCID iDs) - Metadata enables others learn about your data, make use of it and identify it with either (1) your publications, or (2) other research that has used your data. This in turn improves your impact.
Metadata standards often start as schemas developed by a particular user community in response to a particular need. They enable the best possible description of a resource type for their needs and often gain wide acceptance. Maintenance by nationally or internationally recognised centres of excellence, such as the Library of Congress, or support from a professional body, increases both visibility and take-up so that they become a community's standard schema.
Many disciplines have established metadata standards. Some data repositories have their own standards. One of the standards listed below might be exactly what you need to document your data. If there is not a standard already in place for your data, there are several general purpose schemas that you can adapt to your needs. If you need additional help with metadata you can contact the Scholarly Communications Librarian for assistance.
Metadata Concept Map by Amanda Tarbet is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.
In addition to using a metadata standard, you may wish to use ontologies or controlled vocabularies to create your metadata, particularly for subject terms. Ontologies are shared vocabularies that are used to describe components of a particular discipline and the relationships among these components. Ontologies make it easier for others to understand your data. Controlled vocabularies are lists of predefined, authorized terms. The fundamental difference between an ontology and a controlled vocabulary is the level of abstraction and relationships among concepts. It is up to you to choose which vocabulary to use.
Some examples of ontologies and controlled vocabularies include:
The UK's Digital Curation Centre (DCC) maintains a useful inventory of discipline-specific metadata standards. More generally major standards include:
Additonal Standards: