Research Data Management (RDM)

Grateful acknowledgement to the University of Pennsylvania Penn Libraries for their permission to use and modify their template: Data Management Resources

Keep a file with information about your project in the same folder as your other files. A rule of thumb is to write as much information as necessary to understand your data.

Project Level

• Title: Name of the dataset or research project that produced it
• Creator: Names and addresses of the organizations or people who created the data; preferred format for personal names is surname first (e.g., Smith, Jane).
• Identifier: Unique number used to identify the data, even if it is just an internal project reference number
• Date: 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, such as maintenance cycle, update schedule; preferred format is yyyy-mm-dd, or yyyy.mm.dd-yyyy.mm.dd for a range
• Method: How the data were generated, listing equipment and software used (including model and version numbers), formulae, algorithms, experimental protocols, and other things one might include in a lab notebook
• Processing: How the data have been altered or processed (e.g., normalized)
• Source: Citations to data derived from other sources, including details of where the source data is held and how it was accessed
• Funder: Organizations or agencies who funded the research

File Level

• Subject: Keywords or phrases describing the subject or content of the data
• Place: All applicable physical locations
• Language: All languages used in the dataset
• Variable list: All variables in the data files, where applicable
• Code list: 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')

Technical Description

• File inventory: All files associated with the project, including extensions (e.g. 'NWPalaceTR.WRL', 'stone.mov')
• File Formats: Formats of the data, e.g., FITS, SPSS, HTML, JPEG, etc.
• File structure: Organization of the data file(s) and layout of the variables, where applicable
• Version: Unique date/time stamp and identifier for each version
• Checksum: A digest value computed for each file that can be used to detect changes; if a recomputed digest differs from the stored digest, the file must have changed
• Necessary software: Names of any special-purpose software packages required to create, view, analyze, or otherwise use the data

Access

• Rights: Any known intellectual property rights, statutory rights, licenses, or restrictions on use of the data
• Access information: Where and how your data can be accessed by other researchers

Grateful acknowledgement to the University of Pennsylvania Penn Libraries for their permission to use and modify their template: Data Management Resources