Listen to Sarah and Deblekha talk about metadata
Thinking Critically About Metadata
Thinking critically about metadata is similar to how you would approach any other communication or transmission of information. It is important to start with why you are doing this work, rather than just jumping to the how.
Metadata describes people and objects and other things and our biases and concerns will also end up expressed in our metadata.
For example, if you are collecting information about people there can be implications for those people. Once information is collected it can be stored, shared, deleted, and compromised. So too can your metadata. Your metadata also needs to accurately describe, so it needs to be chosen carefully.
To continue with this example, if you are collecting information about gender, the first question to ask is: is it appropriate or necessary to collect at all? If it is necessary then this is where your metadata practices will come into use.
What vocabulary or choices will you make to indicate gender? Are they ones that are respectful to the people involved?
This introduces the need for controlled vocabulary in some circumstances, and not in others. Controlled vocabulary provides a consistent way to describe data. Examples of controlled vocabularies include subject headings, thesauri, ontologies, and taxonomies. In a gender question on a form you could limit the options to the controlled vocabulary options in a dropdown menu, or you could include a free text field so people could type their own words for their gender. Both of these choices have implications for your data and metadata as well as for the people involved.
In order to be useful, most metadata usually needs to be standardized to some degree. 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. A key component of metadata is the schema. Metadata schemas are the overall structure for the metadata. It describes how the metadata is set up, and usually addresses standards for common components of metadata like dates, names, and places. There are also discipline-specific schemas used to address specific elements needed by a discipline.
Always keep the users’ perspective in mind.
Pick a scheme that is going to make sense for the users who will access and use your data, as well as those users managing and preserving your data.
Adopt or Adapt?
Generally you should be able to find a metadata schema and standard to suit your needs. When you find one, use it. If you find one that is close to your needs, but not quite, you can customize it by adding new fields to extend it, or shorten it by removing fields you will never need to make it suit your needs.
There are many types of metadata standards/schemas. Some are generic, while others are domain-specific. Generic ones such as Dublin Core tend to be easy to use and widely adopted, but often need to be expanded in order to cover more specific information. Domain-specific schemas have a much richer vocabulary and structure, but tend to be highly specialized and only understandable by users in that area.