Research Data Management: Research Data

According to the U.S. Federal Government's Office of Management and Budget (OMB) Circular A-110 (36.d.2.i Property Standards; Intangible property; definition),  Research data means "the recorded factual material commonly accepted in the scientific community as necessary to validate research findings." It also excluded the following: 

• Preliminary analyses; drafts of scientific papers; plans for future research; peer reviews;communications with colleagues
• Physical objects, such as laboratory samples 
• 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 
• Personnel and medical information, and similar information, the disclosure of which would constitute a unwarranted invasion of personal privacy.

What are some examples of research data? 

• Text documents, spreadsheets
• Survey questionnaries, transcripts of interviews, codebooks
• Audio and video recordings
• Still Images, Moving images 
• Models, games, simulations
• Spectrographic data, genome sequence, electron microscopy data
• Remote sencing, geospatial data
• Laboratory notebooks, log books
• Algorithms, scripts

If you have questions about data curation and preservation at UH Manoa email:

• Hejin Shin, Data Services Librarian, hejins@hawaii.edu

Planning the Research

• What data will be collected?
• What format will the data be in?
• How long should the data be stored?
• Is there potential for the data to be re-used in other inquiries?
• How large will the datasets be?
• Who owns the data?

Create a Data Management Plan

• What metadata or standardized tags will you use?
• How will you share the data while your research is in progress?
• What documentation is needed to keep the data accessible throughout the project and after?

Collect Data and Documentation

Back up data and documentation in at least three places, e.g. hard drive, thumb drive, and web space

Analyze data

• Back up data and documentation
• Leave your original data intact using copies to perform analyses
• Include algorithms, formulae, and methods in your documentation (use a scripting software such as R to document your analyses)

Prepare Data For Sharing

• Datasets should be in file formats compatible with repository support
• Metadata (tags) added to enable discovery

Archiving and Preservation

• Add to metadata, include published research associated with data

Publish/Share Data

• Select a repository and submit data into the repository.

Ask a Science Librarian
Email: sciref@hawaii.edu
 

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