The University Libraries will host workshops on using ORCID, an international researcher ID service starting Fall 2016. Stay tuned for more details.
The DMPTool will be unavailable on Wednesday, 25 January 2017, 6:00–7:00pm (CST). During this period users will not be able to log in or have access to their work. We apologize for the inconvenience.
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.
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:
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.