1. Research Data Management
Data Management Plans
Jennifer Walton
MBLWHOI Library
Research Data Management
Nova Southeastern University – Halmos College of Natural Sciences and Oceanography – Ocean Campus
16-20 November 2015
With the support of the Government of Flanders, Belgium

2. Learning Outcomes Following this session you will:
Understand the basics of a good data management plan
Be familiar with tools and resources to help create a plan
Research Data Management

3. Agenda
Overview of DMP Tools for creating DMP Practices Exercises Creating a DMP h
Research Data Management

4. What does a data management plan need to cover
What does a data management plan need to cover? Australian National Data Service
Survey of existing data: What existing data will need to be managed? Data to be created: What data will your project create? Data owners & stakeholders: Who will own the data created, and who would be interested in it? File formats: What file formats will you use for your data? Metadata: What metadata will you keep? What format or standard will you follow?
Research Data Management

5. Describe the contents of data files
Define the parameters and the units on the parameter
Explain the formats for dates, time, geographic coordinates, and other parameters
Define any coded values
Describe quality flags or qualifying values
Define missing values
Best practices

6. What does a data management plan need to cover
What does a data management plan need to cover? Australian National Data Service
Data organisation: How will you name your data files? How will you organise your data into folders? How will you manage transfers and synchronisation of data between different machines? How will you manage collaborative writing with your colleagues? How will you keep track of the different versions of your data files and documents?
Research Data Management

7. 

8. What does a data management plan need to cover
What does a data management plan need to cover? Australian National Data Service
Storage: Where will your data be stored? Who will pay for the hardware? Who will manage it?
Access & security: Who will have access to your data? If the data is sensitive, how will you protect it from unauthorised access?
Backups: This is probably the single most important item on this list. Hard drives on desktop and laptop computers fail regularly. You must have a credible backup strategy of regular backups, and of course you must then follow it. Consider including an off-site backup so that your data will not be lost if your building burns down. Rather than relying on memory, consider an automated backup process.

9. Moore 2013

10. Make 3 copies (original + external/local + external/remote)
Have them geographically distributed (local vs. remote)
Use a Hard drive (e.g. Vista backup, Mac Timeline, UNIX rsync) or Tape backup system
Cloud Storage - some examples of private sector storage resources include: (Amazon S3, Elephant Drive, Jungle Disk, Mozy, Carbonite)
Unencrypted is ideal for storing your data because it will make it most easily read by you and others in the future…but if you do need to encrypt your data because of human subjects then:
Keep passwords and keys on paper (2 copies), and in a PGP (pretty good privacy) encrypted digital file

11. Things to consider when archiving data
File formats for long term access Documentation Data Retention Policies Ownership and Privacy Maintaining the integrity of the data Periodically copy your data onto a new drive or disk (every 2-5 years) Maintain your original copy, an external copy, and an external remote copy. Use at least two forms of storage in two different locations
Research Data Management

12. What does a data management plan need to cover
What does a data management plan need to cover? Australian National Data Service
Bibliography management: What bibliography management tools will you use? How will you share references with the other members of your group? Data sharing and publishing; What data will you share with others? How will you do this? Destruction: What data will you destroy? When? How? Responsibilities: Who will be responsible for each of the items in this plan? Budget: What will this plan cost? Possible costs include hardware for backups, research assistant time for data curation, metadata creation, archiving etc. Anything else: Don't restrict yourself to the items above. Stop and think. What is missing from this list?
Research Data Management

13. Elements of a Data Plan NCSU
Roles and Responsibilities
Types of Data
Data Formats and Metadata
Access, Sharing, and Privacy
Re-use
Storage and Preservation
Costs
Research Data Management

14. Five Major Questions University of Arizona
What type of data will be produced?
What standards will be used for documentation and metadata?
What steps will be taken to protect privacy, security, confidentiality, intellectual property or other rights?
If you allow others to reuse your data, how will the data be accessed and shared?
How will the data be archived and preserved?
Research Data Management

15. Data Management Plans usually include: University of Oregon
Describe the data that your research will generate/collect.
Describe how you will annotate and/or describe the data, including the metadata standards and tools (if any) that will be employed.
How will the data be organized, stored and protected during the research project?
How will the data be shared with others, during and/or after the project?
Where and how will the data be archived/preserved for long-term?
Research Data Management

16. Checklist for a Data Management Plan Data Curation Centre
Administrative Data
Data Collection
Documentation and Metadata
Ethics and Legal Compliance
Storage and Backup
Selection and Preservation
Data Sharing
Responsibilities and Resources
Research Data Management

17. Writing a Data Plan MIT Project, experiment, and data description
Documentation, organization, and storage
Access, Sharing, and Preservation
Archiving
Research Data Management

18. Resources
Research Data Management

19. Digital Curation Centre 
Data Management Planning Tool  

20. Questions?
Research Data Management