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Metadata for Researchers

Why use a Standard?

"In order to be useful, metadata needs to be standardized. This includes agreeing on language, spelling, date format, etc. If everyone uses a different standard, it can be very difficult to compare data to other data" (UNC Libraries.  Metadata Standards).

 

Why Bother?

 

Using a metadata standard, aka, schema, is a straightforward way to ensure that your data:

 

  • can be easily indexed and found by other researchers.
     
  • will be comparable to other research data in your field.
     
  • are unambiguous and sufficiently detailed.
     
  • are labelled with consistent terminology when referring to the same things.
     
  • are formatted consistently, e.g., date formats, name order.

 

Which Standard Should I Use?

Characteristics a Metadata Standard
 

"There are many general and domain-specific metadata standards. Dataset documentation should be provided in one of these standard, machine readable, openly-accessible formats to enable the effective exchange of information between users and systems. These standards are often based on language-independent data formats such as XML, RDF, and JSON.

Dataset documentation may also include a controlled vocabulary, which is a standardized list of terminology for describing information. Examples of controlled vocabularies include the Library of Congress Subject Headings (LCSH), NASA’s Global Change Master Directory(GCMD) Keywords and X̱wi7x̱wa Names for BC First Nations, developed by X̱wi7x̱wa Library at UBC.  (DMP Assistant. Portage Template: Documentation & Metadata)."

 

Choosing a Standard

 

Many disciplines have adopted a particular metadata standard or a small number of commonly adopted standards.  See Standards by Discipline in the box below.  

Note: there are standards that are considered "general," and have been adopted by multiple disciplines.  Several of the most common of these are:

 

If your discipline has not adopted a particular standard and/or you cannot find one that suits your needs, see Creating your own Standard.

Resources

Helpful Resources

 

From DCC (Digital Curation Centre), UK:
 

  • Disciplinary Metadata: provides links to information about a wide array of "disciplinary metadata standards, including profiles, tools to implement the standards, and use cases of data repositories currently implementing them."
     
  • List of Metadata Standards - A - Z list; relevant discipline easily inferred by name of standard.
     
  • List of Metadata Tools. 

 

How to implement the metadata standard "Data Documentation Initiative (DDI)"?  By Van Wettere, Niek. Vrije Universiteit Brussel

 

Metadata for Data Management: A Tutorial: Standards/Schema.  From UNC Libraries

 

Metadata Standards & Ontologies.  From How to FAIR

 

Metadata and Describing Data.  From Cornell University

 

Organize (your data files).  Excellent advice on file naming & hierarchies from UBC Library.

 

Standards - "A registry of terminology artefacts, models/formats, reporting guidelines, and identifier schemas."  From Fairshairing.org