Difference between revisions of "Data Management"
| Line 65: | Line 65: | ||
====From the ODH DMP Tool==== | ====From the ODH DMP Tool==== | ||
| − | ''' | + | '''Introduction (One Page)''' |
| − | + | Thank you for taking the time to fill out the data management plan tool. Remember that data management is an ongoing process that should be continued through the life of the project. Short term plans address the needs of a project during its active period, and long-term plans address the needs of a project beyond. | |
| − | |||
Responsibilities | Responsibilities | ||
* Who will be responsible for data management and for monitoring the data management plan? | * Who will be responsible for data management and for monitoring the data management plan? | ||
Revision as of 15:38, 27 May 2015
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?
From the ODH DMP Tool
Introduction (One Page)
Thank you for taking the time to fill out the data management plan tool. Remember that data management is an ongoing process that should be continued through the life of the project. Short term plans address the needs of a project during its active period, and long-term plans address the needs of a project beyond. Responsibilities
- Who will be responsible for data management and for monitoring the data management plan?
- How will adherence to this data management plan be checked or demonstrated?
Project Plan Timelines
- Short term plans address the needs of a project during its active period.
- Long term plans address the needs of a project during its active period and beyond (archiving, etc?)
Roles & Responsibilities (Page One)
Explain how the responsibilities regarding the management of your data will be delegated. Try to include time allocations, project management of technical aspects, training requirements, and contributions of non-project staff - individuals should be named where possible. Remember that those responsible for long-term decisions about your data will likely be the people we work with when managing your data in the DRS.
- Who secures the data?
- Who ensures data is backed up and not corrupted?
- Who is responsible for metadata and documentation?
Roles & Responsibilities (Page Two)
- What process is in place for transferring responsibility for the data once the project is no longer active, or when there are personnel changes?
- Who is responsible for metadata and documentation?
- Who secures the data?
- Who ensures data is backed up and not corrupted?
Data and Data Retention Period Expectations
Give a short description of the data, including amount (estimated amount or known amount) and content. Data types could include XML spreadsheets, interview transcripts, text files, historical documents, diaries, field notes, geospatial data, citations, software code, algorithms, etc. Identify your methods for collecting data. [More about data retention and the period of data retention]. Explain the policies that may restrict the distribution of your data, and describe how you will make sure that access to data is made available in a timely manner.
- What data will be generated in the research?
- What data types will you be creating or capturing?
- How will you capture or create the data?
- If you will be using existing data, state that fact and include where you got it. If you have multiple data sets with different origins, what is the relationship between the data you are collecting and the existing data?
- What data will be preserved and shared?
- Where (physically) and on what media will you store the data during the project’s lifetime?
- How will you back-up the data during the project's lifetime and how regularly will back-ups be made?
- How long will the original data collector/creator/principal investigator retain the right to use the data before opening it up to wider use?
- Explain details of any embargo periods for political, commercial, patent or publisher reasons.
Sensitive Data and Secure Access
- If the project will be collecting data of a sensitive nature, note here and reflect upon it in subsequent sections.
- Will you be collecting data that is sensitive, or could be considered sensitive? For example, are you collecting personally identifying information, like names and social security numbers. [Consider consulting NU policies].
- How will you manage data with sensitive information?
- Are there ethical and privacy issues? If so, how will these be resolved?
- What have you done to comply with Northeastern's data obligations, such as the IRB's protocol?
- IRB: http://www.northeastern.edu/research/hsrp/irb
- Office of Institutional Research: http://www.northeastern.edu/oir
- Northeastern's Policy on Confidentiality of University Records and Information: http://www.northeastern.edu/policies/pdfs/Policy_on_Confidentiality_of_University_Records_and_Information.pdf
Data Formats and Dissemination
Describe the format of your data. Consider the following:
File Formats (One Page)
- Which file formats will you or do you already use for your data, and why?
- What transformations (to more shareable formats) will be necessary to prepare data for preservation and data sharing?
Metadata (One Page)
- What contextual details (metadata) are needed to make the data you capture or collect meaningful? How would you describe your data to another researcher getting ready to use it?
- How is your metadata stored? For example, XML or Excel?
- If you are actively creating your data, how will you create or capture your metadata?
- Which metadata standards will you use and why have you chosen them? (e.g. MODS, Dublin Core, or TEI).
Sharing (Page One)
- How will you make the data available? Will you provide an API, or downloadable zip files? Will it be via a website, or other system? Include the resources needed to make the data available: hardware, software, types of expertise, etc.
- When will you make the data available? Are there deadlines you need to meet?
- What other types of information should be shared regarding the data? Will other users need to know how it was generated, or how you decided to organize it, or what algorithms were used to analyze it?
Sharing (Page Two)
- What is the process by which others will gain access to your data? Will it be available for open download, or behind an account system, or other systems?
- Will any permission restrictions need to be placed on the data?
Data Storage and Preservation of Access
Describe your long-term strategy for storing, archiving and preserving the data you will generate or use. Consider the following:
- What is the long-term strategy for maintaining, curating and archiving the data?
- Which archive/repository/database have you identified as a place to deposit data?
- What procedures does your intended long-term data storage facility have in place for preservation and backup?
- How long will/should data be kept beyond the life of the project?
- What data will be preserved for the long-term?
- On what basis will data be selected for long-term preservation?
- What metadata/documentation will be submitted alongside the data or created on deposit/transformation in order to make the data reusable?
- What related information will be deposited?