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Metadata Creation

Brief guide that explores the topic of metadata: What are metadata? What kinds of metadata are there? What is the process of creating metadata?

Tools of metadata creation

  • Schema

A metadata schema is a list of elements or defined data points that are used to capture information about a resource. Some of these data points might include a title, an identifier, a creator name, or a date.

  • Standards

Standards are the tools that tell us how to populate each of the data elements within a schema.  There are three types of standards:

  • Content standards

Content standards describe the use of each element or what pieces of types of information go where.  They also give guidance on how to best record or transcribe that information: Where should that information be coming from? What is the best source of information? Which elements should require the use of data values standards and, if so, which value standards should be used?

  • Data value standards

Data value standards are lists of standardized subject terms, genre terms, names, etc.  Examples of data value standards include controlled vocabularies like Library of Congress Subject Headings and other discipline-specific thesauri, and encoding or formatting standards like ISO 8601 which prescribes how dates ought to be represented.

  • Data structure standards

Data structure standards (XML, RDF, etc.)  exist to tell us how to encode and structure the metadata record so as to ensure its machine readability. It is important to note that there are two primary users of metadata: humans and machines. Any metadata you create must be intelligible to both.

  • Best practices

Best practices guide or prescribe the selection and use of a particular metadata schema, which subset of elements within that schema will be used to comprise a metadata profile for use in describing a certain class or collection of objects.  Best practices also serve to: 1) better define or clarify the use of each metadata element within the context of a given project or organization; and 2) more decisively recommend the use of particular content, data value, and/or data structure standards. 

Quality of metadata

When creating or evaluating metadata it is important to ask:

  • Accuracy: Is the data recorded correct and factual?
  • Completeness: Has all relevant data been recorded in full?
  • Consistency: Has data been entered consistently? Is the same set of metadata elements being used to describe all of the resources in your collection? Is data being entered in the same format?
  • Interoperability: Is your data machine readable? Can your metadata be easily migrated to and understood by another system? Can it be aggregated with other metadata sets or collections?
  • Inclusivity: Is your data inclusive, non-derogatory, and free of bias and harmful language? Are terms used appropriate to the resource being described? Do terms and descriptive information align with how the creator(s) and/or users of a resource might describe it?
  • Ethical considerations: Does your data contain personal, identifying or otherwise sensitive information? Do you have rights to record or publish information contained in your data? Are contributors to the data and/or any resources cited therein credited?