Penn State Data Management Plan Tutorial

2.2 The Importance of Standards in Metadata

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In documenting your data with metadata, it is important to adhere to standards - standard vocabularies, standard schemas, etc. Organizing your data using a standards-based approach helps ensure interoperability between systems, which also enhances discovery of, and access to, data. To Ben Goldman, metadata is an essential tool for managing collections, and adherence to common standards is vital to making the data reusable. He shares some of his experiences with trying to decipher old data in the video below.


Link to YouTube video.

One common standard or schema followed in many repositories is the Dublin Core Metadata Element Set, which has 15 metadata fields (e.g., creator, title, subject, rights, description, etc.). Your research community may already have metadata standards that it follows. A useful list of disciplinary standards to consult is at the Digital Curation Centre (DCC) website. Another way to find out more about metadata standards for your research data is to consult the data repositories that your data might be suitable for. Two registries of repositories, in particular, are worthwhile checking out:

  • DataBib is searchable catalog / registry / directory /bibliography of research data repositories.”
  • DataCite Repositories List - Working document listing data repositories.

You might also consult the metadata librarian at your institution's library to find out more about what standards to apply to your data. Ultimately, an exploration of these standards can provide insight into what kind of information about your data is important to document.

Dr. Alfred Traverse, Curator of the Penn State Herbarium, has extensive experience in managing large of collections of specimens with varying levels of metadata. In the video below, he describes two specimens from the Herbarium's collection, how they were preserved, and their recorded metadata. It is a good illustration of how metadata standards change over time. Standards evolve much as data collection practices do.


Link to YouTube video.