Open Data Mandates - Am I Required to Share My Data?
Some funding agencies mandate that the data produced with their funding be made openly available. This has become more common following a 2013 memo from the White House Office of Science & Technology Policy (OSTP) which directed many federal agencies to make federally funded research articles and data freely available to the public within one year of publication. (Learn more.)
The resources below will help you determine whether your data may be subject to a mandate.
NEW! April 2021: AAU-APLU Guide to Accelerate Public Access to Research Data
AAU-APLU Guide to Accelerate Public Access to Research Data
The Association of American Universities (AAU) and the Association of Public and Land-grant Universities (APLU) have collaborated and led national discussions to improve public access to data resulting from federally funded research. The current Guide to Accelerate Public Access to Research Data builds on many prior efforts and is consistent with national and global open science efforts as well as international declarations, such as the Sorbonne declaration on research data rights.
Sorbonne Declaration on Research Data Rights
Sorbonne Declaration on Research Data Rights (2020)
"On 27 January , the International Summit on Research Data Rights was held at the Sorbonne University, where the “Sorbonne Declaration” on research data rights was signed. The text affirms the willingness of universities to share data and make appropriate use of it, and calls on governments to adopt a legal framework to regulate this exchange and provide the means to implement it. The aim is to make data accessible to accelerate scientific discovery and economic development."
Public Trust in Open Data
Evaluating Existing Data
Just as with published works, we can apply evaluation models to ensure before use that existing data is accurate and fair.
ACT UP Model
Author, Currency, Truth, Unbiased, Privilege
Rationale, Authority, Date, Accuracy, Reason for writing (or in the case of data, Reason for Collecting)
Currency, Relevance, Authority, Accuracy, Purpose
- Completeness / Extent of missing data
- Data collection methods
- Data quality measures such as reliability and validity
- Availability of a contact person
Adapted from "Evaluating Data Sets," Rutgers University Libraries