Metadata is structured information that describes, explains, locates, or otherwise makes it easier to retrieve, use, or manage an information resource. Metadata is often called data about data or information about information. It ensures that the context for how your data was created, analyzed and stored, is clear, detailed and therefore, reproducible.
National Information Standards Organization, 2004

Biomedical Metadata

Good metadata enables you to understand, use, and share your own data now and in the future and helps other researchers discover, access, use, repurpose, and cite your data in the long term. It also facilitates long-term archival preservation of the data. Types of documentation to capture biomedical data include:

  • Reagent Metadata: Information about the clinical samples, biological reagents (e.g., cell lines, antibodies, siRNAs), chemical reagents (e.g., drugs), etc. used to generate the data.
  • Technical Metadata: Information automatically generated by research instruments and associated software.
  • Experimental Metadata: Information about the experimental conditions (e.g., assay type, time points), the experimental protocol, and the equipment used to generate the data.
  • Analytical Metadata: Information about data analysis methods, including software name and version, quality control parameters, and output file type details.
  • Dataset Level Metadata: Information about the objectives of the research project, participating investigators, relevant publications, and funding sources.
     

When to Record Metadata

Many fields within the biomedical science community are developing standards for what metadata to collect across different data types. Whenever possible, it is best to consult community standards before you begin collecting research data. It is easiest and most efficient to record metadata during the research process while the data still are active. This also ensures that the metadata record is complete and accurate.

Your metadata will likely come from several sources during your research:

  • Technical Metadata: Generated from research instruments and software used.
  • Additional Metadata: Most metadata will be collected manually. Consider using an existing schema or templates to make the process standardized and easier.
     

How to Record Metadata

Experimental and data analysis metadata should be stored alongside your research data. This documentation can be maintained in a variety of forms.

  • README: A README File is a text file located in a project-related folder that describes the contents and structure of the folder and/or a dataset so that a researcher can locate the information they need.
  • Data Dictionary: Also known as a codebook, a data dictionary defines and describes the elements of a dataset so that it can be understood and used at a later date.
  • Protocol: A protocol describes the procedure(s) or method(s) used in the implementation of a research project or experiment. If you need to maintain protocols, we strongly recommend a tool like protocols.io. Learn more about protocols.io for HMS/HSDM/HSPH researchers.
  • Lab Notebook: For research groups that use them, lab notebooks are often the primary record of the research process. They are used to document hypotheses, experiments, analyses, and interpretations of experiments. Electronic Lab Notebooks offer several advantages over traditional paper notebooks. Find an ELN solution for LMA groups.
     

Metadata Standards & Guidance

Where possible, employ one or multiple established metadata standards, or schemas, that are widely used within your discipline. If you are storing your data in a repository, you also must comply with its metadata requirements.

Quick help links

  • FAIRsharing (informational resource on data standards, databases, and data policies)
  • National Information Standards Organization (NISO)'s Understanding Metadata (2017)

Subject-Specific Guidance

Additional Medical Metadata Standards