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Data Services

Data Management Services assists Brandon researchers with the organization, management, and curation of research data to enhance its preservation and access now and into the future

DMPs and Metadata 

 

What Metadata will be used?  Are you using a
Metadata Standard?  

Guidance

Be prepared to identify a relevant standard.  Best approach is
to identify  the Metadata standard based upon any discipline
standards for Metadata.  More about this is discussed below. 

If you need help selecting a Metadata standard consult a librarian.

What is Metadata?
 

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:

  • Title
  • Creator
  • Date Created
  • Format    e.g., plain text (.txt), comma-separated values (.csv), geo-referenced TIFF (.tif, .tfw).  Are you using an open format. 
  • Subject
  • Unique Identifier (ideally, a Digital Object Identifier, or DOI)
  • Description of the specific data resource
  • Coverage (spatial or temporal)
  • Publishing Organization
  • Type of Resource
  • Rights/Licensing/Ethics approval
  • Funding/Granting Agency

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:

  • Descriptive Metadata enables identification, location and retrieval of information resources by users, often including the use of controlled vocabularies for classification and indexing and links to related resources.
     
  • Technical  / Structural Metadata describes the technical processes used to produce, or required to use a digital object.  It is generally used in machine processing, describes relationships among various parts of a resource, such as chapters in a book.
     
  • Administrative Metadata is used to manage administrative aspects of the digital object such as intellectual property rights and acquisition. Administrative Metadata also documents information concerning the creation, alteration and version control of the metadata itself. This is sometimes known as meta-metadata. 

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.

Why use Metadata?
 

Using established metadata standards will help make your data discoverablecitable, 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:

  • Findable: 
    Machine-readable metadata are essential for automatic discovery of datasets and services
     
  • Accessible:  
    Once the user finds the required data, she/he needs to know how can they be accessed, possibly including authentication and authorization.
     
  • Interoperable:  
    The data usually need to be integrated with other data. In addition, the data need to interoperate with applications or workflows for analysis, storage, and processing.
     
  • Reusable: 
    The ultimate goal of FAIR is to optimise the reuse of data. To achieve this, metadata and data should be well-described so that they can be replicated and/or combined in different settings.


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
 

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.

Ontologies 
 

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:

Locating Relevant Metadata Standards 
 

The UK's Digital Curation Centre (DCC) maintains a useful inventory of discipline-specific metadata standards.  More generally major standards include: 

Additonal Standards: