Identify and use relevant metadata standards
Many times significant overlap exists among metadata content standards. You should identify those standards that include the fields needed to describe your data. In order to describe your data, you need to decide what information is required for data users to discover, use, and understand your data. The who, what, when, where, how, why, and a description of quality should be considered. The description should provide enough information so that users know what can and cannot be done with your data.
- Who: The person and/or organization responsible for collecting and processing the data. Who should be contacted if there are questions about your data?
- What: What parameters were measured or observed? What are the units of your measurements or results?
- When: A description of the temporal characteristics of your data (e.g., time support, spacing, and extent).
- Where: A description of the spatial characteristics of your data (e.g., spatial support, spacing, and extent). What is the geographic location at which the data were collected? What are the details of your field sensor deployment.
- How: What methods were used (e.g., sensors, analytical instruments, etc.). Did you collect physical samples or specimens? What analytical methods did you use to measure the properties of your samples/specimens? Is your result a field or laboratory result? Is your result an observation or a model simulation?
- Why: What is the purpose of the study or the data collection? This can help others determine whether your data is fit for their particular purpose or not.
- Quality: Describe the quality of the data, which will help others determine whether your data is fit for their purpose or not.
Considering a number of metadata content standards may help you fine-tune your metadata content needs. There may be content details or elements from multiple standards that can be added to your requirements to help users understand your data or methods. You wouldn’t know this unless you consider multiple content standards.
- If the project or grant requirements define a particular metadata standard, incorporate it into the data management plan.
- If the community has a recommended or has a most commonly used metadata standard, use it
- Consider using a metadata standard that is interoperable with many systems, repositories, and harvesters
- If the community’s preferred metadata standard is not widely interoperable, consider creating metadata using a simple but interoperable standard, e.g. Dublin Core, in addition to the main standard.
- Metadata Content Standard: A Standard that defines elements users can expect to find in metadata and the names and meaning of those elements.
- Metadata Format Standard: A Standard that defines the structures and formats used to represent or encode elements from a content standard.
The metadata standards that you use determine the communities that can easily use your data.
Beall, Jeffrey. 2007. “Metadata for Digitization Projects: Discrete Criteria for Selecting and Comparing Metadata Schemes - Reflecting further on schema selection, Jeffrey enumerates twelve points of comparison to help one decide which of the many schemas available best suits one digital project”. Against the Grain. 19 (1): 28.
Eichenlaub, N. 2010. “Metadata for Digital Resources: Implementation, Systems Design and Interoperability, by Muriel Foulonneau and Jenn Riley”. CATALOGING AND CLASSIFICATION QUARTERLY. 48 (4): 348-351.
UK Digital Curation Centre (DCC) Disciplinary Metadata Catalog http://www.dcc.ac.uk/resources/metadata-standards
Seeing Standards: A Visualization of the Metadata Universe http://jennriley.com/metadatamap/
Xu W, and M Okada. 2007. “EBM metadata based on Dublin Core better presenting validity of clinical trials”. Journal of Medical Systems. 31 (5): 337-43.
Cite this best practice:Jeff Horsburgh, Rebecca Koskela, Rebecca Lubas, Thorny Staples, DataONE (August 30, 2011) "Best Practice: Identify and use relevant metadata standards". Accessed through the Data Management Skillbuilding Hub at https://dataoneorg.github.io/Education/bestpractices/identify-and-use on May 24, 2019