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Data Management Toolkit @ UNH

This toolkit provides information to help researchers develop data management plans and effectively manage their research data.

Data Documentation

Data must be documented to be used properly by you, your colleagues, and other researchers in the future.  Data documentation (also known as metadata) enables one to understand your data in detail and will enable other researchers to find, use and properly cite your data.

It is critical to begin to document your data at the very beginning of your research project, even before data collection begins; doing so will make data documentation easier and reduce the likelihood that you will forget aspects of your data later in the research project.

Following are some general aspects to document about your project and data, regardless of your discipline.  At minimum, store this documentation in a readme.txt file or the equivalent, together with the data. One can also reference a published article which may contain this and additional information.

Title

Name of the dataset or research project that produced it

Creator

Names and addresses of the organization or people who created the data

Identifier

Number used to identify the data, even if it is just an internal project reference number

Subject

Keywords or phrases describing the subject or content of the data

Funders

Organizations or agencies who funded the research

Rights

Any known intellectual property rights held for the data

Language

Language(s) of the intellectual content of the resource, when applicable

Dates

Key dates associated with the data, including: project start and end date; release date; time period covered by the data; and other dates associated with the data lifespan, e.g., maintenance cycle, update schedule

Location

Where the data relates to a physical location, record information about its spatial coverage

Methodology

How the data was generated, including equipment or software used, experimental protocol, other things one might include in a lab notebook

Data processing

Along the way, record any information on how the data has been altered or processed

File Formats

Format(s) of the data, e.g. FITS, SPSS, HTML, JPEG, and any software required to read the data

Variable list

List of variables in the data files, when applicable

Code lists

Explanation of codes or abbreviations used in either the file names or the variables in the data files (e.g. '999 indicates a missing value in the data')

Versions

Date/time stamp for each file, and use a separate ID for each version (see file organization)

Metadata Standards

Researchers can choose among various metadata standards, often tailored to a particular file format or discipline.  One such standard is DDI (the Data Documentation Initiative), designed to document numeric data files.

Metadata Standards provide specific data fields or elements to be used in describing data for a particular use. Some research fields have predefined metadata standards, such as those listed below.

For more discipline-specific metadata standards check out the RDA Metadata Directory.  

More about Data Documentation and Metadata