1. Data Management Planning
Jake Carlson
Purdue University Libraries
Ron Nakao
Stanford University Libraries

2. What will be Covered An introduction to terms and concepts.
An understanding of the purpose of data management planning.
Coverage of some of the elements of data management planning and how they may relate to each other.
Case studies from Purdue and Stanford.

3. What is Data Management?
“In the context of research and scholarship, "Data Management" refers to the storage, access and preservation of data produced from a given investigation. Data management is practices through the entire lifecycle of the data…”
Texas A&M, Research Data Management Lib Guide

4. What is a DMP? A formal document. Describes:
what data will be produced
how each type of data will be managed
how each type of data will be shared
how each type of data will be archived
who will take responsibility for these actions
DMP Resources and Examples:
From a higher element / perspective – good data management for good research
Insert a slide here

5. DMP Requirement (NSF)
Data - samples, physical collections, software, curriculum materials, and other materials;
Standards - for data and metadata formats and content;
Policies for access and sharing – incl. IP, protection of privacy/confidentiality, security, etc.;
Policies for re-use – including provisions for re-distribution, and the production of derivatives;
Archiving - data, samples, and other research products, and for preservation of access.

6. DMP Tool https://dmp.cdlib.org/ DMP Tool is for:
Create ready to use data management plans for specific funding agencies.
Meet funder requirements for data management plans.
Get step-by-step instructions and guidance for your data management plan as you build it.
In many cases, get data management advice and resources for your specific institution.

7. https://dmponline.dcc.ac.uk/
DMP Online is for:
The process of writing a DMP enables you to get the most of your research. It helps you to:
make informed decisions about how to create, manage and share your data
anticipate and avoid problems e.g. data loss or duplication
organise your data so you can find and understand it when needed
improve the visibility of your research for more citations and impact
ensure that you have the necessary resources, skills and support in place.

8. DMP Consulting

9. Why Manage Data? Because you have to: Because you want to:
Meet grant requirements
Because you want to:
Increase the visibility of your research
Simplify your life / Save time
Protect yourself

10. Effective Data Management Planning
Is a process, not an event
Probably requires more thought than it is given in developing the grant
Probably requires more than 2 pages
Should be informed by disciplinary and local cultures and environments
Should be driven by goals and objectives
Must be implemented to be successful
My thoughts and opinions, your mileage may vary.

11. Other DMP Elements (ICPSR)
Responsibility - who does what, when?
Audience – identifying the potential secondary users of the data
Selection and retention periods –
what criteria will be used?
how long will data be retained and/or archived?
when will data be transferred to a 3rd party for curation?
Quality Assurance
Ethics & Legal Requirements
Budget & Financial Aspects

12. DMP Purpose Proposal Development & DMPs
Data Collection & File Creation
Preparing Data for Sharing
Project
Start-Up
Data
Analysis
Depositing
Data
Graphically important

13. Guidance Across the Lifecycle
Preparing Data
for Sharing
> Address disclosure
risk limitation
> Determine file
formats to deposit
> Contact archive for
advice

14. Data Management Planning
Case Study on
Data Management Planning

15. Libraries sponsored research center.
Established in 2006 to focus on issues associated with curating data sets for present and future research use.
Working in partnership with domain scientists and IT personnel to address the real world data needs of a research community.

16. Background Research “Unpacking” the NSF requirements
Review of the content of existing data management plans
Review of existing guides on creating a DMP
Review of the information gathered from our Data Curation Profiles work, and other faculty-librarian collaborations

17. The Data Curation Profile is not designed to produce a Data Management Plan, however it could be used as a foundation to develop a more specific tool
Examination of DCP questions in light of DMP requirements
IASSIST 2011

18. Interviews Working with OVPR, four proposals were selected:
Engineering Education
Agronomy
Physics / Electrical & Computer Engineering
Pharmacy
Interviews are conducted:
Multiple faculty / Multiple interviews
Sponsored Programs personnel and Subject Librarians also attend interviews
Nov Working in collaboration with the Associate VP for Research, the Libraries identify four projects for testing the "DCP for DMP" tool. Project #1 - Engineering Education, #2 - Agronomy, #3 - Electrical / Computing Engineering, #4 - Pharmacy (this project is already been submitted to the NSF - but will likely need a DMP in the future). The project Pis (more than one PI exists for some of the projects) are contacted by the Associate VP for Research to recruit them for this study.
Nov All researchers contact agree to participate. The interview worksheet is sent out for Pis to complete in preparation of the interview. Completed worksheets show that the section on metadata and preservation are the most difficult for researchers to respond to.
Nov - Dec Interviews are conducted. Some researchers are further ahead in developing their grant than others, making some of the interviews more challenging than others. It's decided to postpone the Eng Ed interview until the proposal is better fleshed out. Both Pis are inetrviewed for projects with two Pis.
Proposal coordinators attend and participate in the interviews to varying degrees. Subject librarians attend the Agronomy, Pharmacy and Eng Ed interviews / meeting.
Carlson
IASSIST 2011

19. Challenges Metadata & Preservation
Hard for researchers to define, or their understanding may not be fully accurate.
Archive = an old copy and/or a back-up copy
Generally outside researcher’s current practices.
Disciplinary standards or solutions may not be known, or may not exist.

20. DMP Self-Assessment Questionnaire

21. Guides
IASSIST 2011

22. PURR

23. Nano HUB

24. PURR - Planning

25. PURR – Active Data

26. Publishing & Curation Abstract Cite this Work Tags Citations
Supporting Docs
Versions
Reviews
Questions

27. Stanford Case Study Stanford Data Management Services
Faculty collaboration example (HCMST)
Stanford Digital Repository (SDR)

28. Data Management Services

29. Plan Determine Funder Requirement Create a Data Management Plan
DMPTool list
Preparation
Create a Data Management Plan
DMPTool
Decide How to Share
Licensing (CC, ODC)
Other Issues (IP, IRB)

30. Manage Organize Your Data Back Up Your Data
Names, Formats, Metadata, Versioning, Documentation, Knowledge Transfer Plan
Back Up Your Data
Storage, Backup & Recovery Services
Acquire & Analyze Data
Social Science Data, Geographical Data

31. Preserve Select Data for Archiving Assign Metadata
Questions to consider
Assign Metadata
Deposit Data in a Repository
Stanford Digital Repository (SDR)
Subject-Specific Repositories

32. Case Study
Collaborating with Professor Michael Rosenfeld on Data Management Plan & Its Implementation
DMP (later in Exercise)
“Painless” creation of Metadata
Quick turnaround for public data sharing
<data.stanford.edu>
Long-term Preservation
ICPSR
Stanford Digital Repository (SDR)

33. <data.stanford.edu> Metadata
Title Citation Abstract, Principal Investigator, Funding Agency, Bibliographic Citation, Contact Description Introduction, Acknowledgements Methodology Universe, Unit of Analysis, Type of data collection, Time span, Time of data collection, Geographic coverage, Smallest geographic unit, Sample description, Sample response rate, Weights Documentation Document file(s), Web site or document download link(s) Data Download Link(s) Data file(s) Notes Errata, Data Notes News News Coverage

34. data.stanford.edu

35. Data entry form

36. Lessons from Case Study
Quick development, enhancement, and data availability (Drupal)
Active PI involvement & metadata creation
Ownership & “freshness” of PI’s data page
Easy referral by PI (customized URL), usage stats, and contact lists provided ongoing value for PI

37. Archiving HCMST: ICPSR

38. Stanford Digital Repository (SDR)
The SDR is a service supporting long-term management of scholarly information resources at Stanford.
Deposit in the SDR enables faculty, students, researchers to promote and protect the products of their work.
Librarians use the SDR to preserve and share scholarly collections of enduring value to the larger Stanford community.
Through robust preservation and security measures, the repository maintains appropriate access to deposited content from persistent web links while protecting against data loss and corruption.

39. Stanford’s Digital Library Infrastructure
Diagram courtesy of Hannah Frost, Services Manager, Stanford Digital Repository

40. Thanks!
Any Questions?