Thomas C. Wilson
Professor, Associate Dean
What are Research Data?
The Office of Management and Budget, Circular A-110, defines data as:
...recorded factual material commonly accepted in the scientific community as necessary to validate research findings, but not any of the following: preliminary analyses, drafts of scientific papers, plans for future research, peer reviews, or communications with colleagues. This "recorded" material excludes physical objects (e.g., laboratory samples).
Research data also do not include: (A) Trade secrets, commercial information, materials necessary to be held confidential by a researcher until they are published, or similar information which is protected under law; and (B) Personnel and medical information and similar information the disclosure of which would constitute a clearly unwarranted invasion of personal privacy, such as information that could be used to identify a particular person in a research study.
In the Humanities and related disciplines, data could be text, text corpora, audio, image, or video.
Academic departments and individual disciplines may add other designations.
Important UA Links
This guide provides an introduction to resources in the University for Data Management Plan creation and execution. Use the tabs above or the links below to find information on the following topics:
UA Office for Research Links:
- Office for Sponsored Programs - Data Management Plan Guidance
- Data Ownership and Retention Policy
- Research Using a Limited Data Set
- Protection of Human Research Participants' Privacy and Confidentiality
Research Data Management and Curation
What is this?
In a nutshell, data management and curation entails structured processes to ensure that the data used and generated by research activities are well-described, documented, findable, retrievable, understandable, and preserved for some period of time.
Why should I be interested in this?
Effective data management results in no lost or corrupted data, easier identification and handling of data during projects and after, and more time for research activities. In addition, increasingly external funders require data management (and sharing) plans so that funded research can serve as foundations for future research and previous investments can continue to yield dividends.
Data Life Cycle Models
There are many ways to visualize the life cycle of data. Here are three prominent models: