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Research data management: Metadata

Research data management covers the planning, collecting, organising, managing, storage, security, backing up, preserving, and sharing your data.

What is metadata

Types of metadata

Usually, metadata are standards-based and serve a particular purpose in data processing and machine-to-machine interoperability. Metadata may be stored as XML, in an accompanying document, a set of data fields in a repository, or a README file.  Three broad categories of metadata are:

  • Descriptive - common fields such as title, author, abstract, keywords which help users to discover online sources through searching and browsing.
  • Administrative - This type helps manage the dataset. It includes rights management, access control, use requirements, technical data on file creation and quality control, file formats, software/hardware for access and use, and any information relevant to archiving and preservation.
  • Structural - how different components of a set of associated data relate to one another, such as tables in a database, that chapter 1 comes before chapter 2 in a book, or that file x is the JPEG format of the archival TIFF image file z.

Three types of metadata - descriptive, administrative and structural

Tip

'The metadata accompanying your data should be written for a user 20 years into the future ... Prepare the metadata for a user who is unfamiliar with your project, methods, or observations.'

Oak Ridge National Laboratory, Distributed Active Archive Center

Metadata schemas

Metadata is usually structured according to existing standards or 'schemas'. The most common metadata schema is probably Dublin Core, developed in 1995. Simple Dublin Core involves 15 elements, all of which are optional and repeatable, and which can appear in any order:

  • Title
  • Subject
  • Format
  • Date
  • Source  
  • Identifier
  • Type
  • Description
  • Language
  • Rights
  • Publisher
  • Relation
  • Creator
  • Contributor
  • Coverage
 
Appropriate metadata will also facilitate depositing your data into a repository at the end of the project. See access/sharing/data description.

Standards and schemas

The following list of standards and schemas is not exhaustive, but will provide some guidance about the appropriate schemas and standards in current use in some disciplines.

 

+ Generic Standards

+ Discipline Standards

+ Discipline Schema

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