Data Management
Revision as of 15:14, 10 February 2015 by Ssweeney (talk | contribs) (→Working with Projects and Data)
What is a Data Management Plan?
A data management plan is a written assessment of how project or research data will be collected, organized, shared, maintained, and preserved.
Why Manage Your Data?
- Fulfill requirements
- Improve project efficiency
- Organize large sets of data
- Preservation
- Reuse
- Promote research
How Do I Create a DMP?
- Establish data management goals
- Consult funding agency guidelines (NSF, NEH, IMLS)
- Review checklists of recommended data management topics
- Use a data management planning tool, like DMPTool or DMPonline (UK)
Managing Your Data
- Analyze the data (what kind(s) of data? how much data? who needs your data? how will it be used in the future?)
- Organize the data (decide on file naming conventions, directory structures, metadata standards, data formats)
- Decide how the data can be accessed (where will it be stored? what will be shared? how will it be shared? when will it be shared?)
- Who is responsible for your data?
Working with Projects and Data
Data Interviews
- Invite project representatives to answer data management questions using the DSG template in the DMPTool
- Ask them to keep track of questions that are difficult to answer
- Meet with project reps to discuss difficult questions and provide guidance for difficult data management areas
DMPTool
- What questions do we want to ask?
- How do we want to organize the questions?
- What is the end result?
Possible DM Questions
- Data and Project Materials
- What kinds of data? (genres, file formats)
- How much?
- Who is the audience for your data?
- How might your data be reused?
- What will will be needed to reuse your data?
- Organization and Standards
- How are your files named?
- How is your file directory structured?
- Are you using a metadata standard?
- What data formats?
- How are you documenting your data? (wiki, codebook)
- Data access, sharing, and re-use policies
- What do you plan to share?
- How will users access the shared data?
- When will users have access?
- Can data be redistributed?
- Can other works be derived from your data?
- Are there ethical or legal restrictions on access and use?
- How will restrictions be handled?
- How will you guarantee safe, untampered data?
- Where is your data stored?
- What is the life span of your stored data?
- Roles and responsibilities?
- Who is responsible for metadata and documentation?
- Who secures the data?
- Who ensures data is backed up and not corrupted?