Creating a Data Management Plan
Kristin Briney, PhD
Data Services Librarian
This Session Will Answer
• Why am I being asked to create a DMP?
• What are the key parts of a DMP?
• How do I translate m...
You Will Leave With
• An understanding of the main parts of a data
management plan
• Knowledge of where to find resources ...
WHY AM I BEING ASKED TO CREATE
A DATA MANAGEMENT PLAN?
Why Data? Why Now?
• Data are DIGITAL
– Easy to copy and share
– Difficult to preserve
• Data are COMPUTABLE
– New avenues...
Many Funders Require DMPs
• NSF
• NEH
• NIH
• NOAA
• NASA
• …even more funders will require DMPs soon!
– White House OSTP ...
The Funder Perspective
• Data is a scholarly resource
– Data sharing akin to scholarly publishing
• Barriers to sharing ar...
DMPs Help You Too!
• Don’t loose data
• Find data more easily
• Easier to analyze organized, documented data
• Avoid accus...
For each minute of planning at
beginning of a project, you will save
10 minutes of headache later
DMPs Help You Too!
A data management plan will make conducting
research easier for you…
…So if you are required to create ...
WHAT ARE THE KEY PARTS OF A
DATA MANAGEMENT PLAN?
Actual NSF DMP Requirements
• The types of data, samples, physical
collections, software, curriculum materials, and other
...
Key Questions
1. What data will I create?
2. What standards will I use to document the
data?
3. How will I protect private...
Be Aware
• Actual requirements vary by funder and
division
• Look up your requirements before you write
your DMP
HOW DO I TRANSLATE MY RESEARCH
TO EACH OF THESE PARTS?
1. WHAT TYPES OF DATA WILL I
CREATE?
What Are Data?
• “Research data is defined as the recorded
factual material commonly accepted in the
scientific community ...
What Are Data?
• Observational
– Sensor data, telemetry, survey data, sample
data, images
• Experimental
– Gene sequences,...
What Not To Share
• Laboratory notebooks
• Preliminary analyses
• Drafts of scientific papers
• Plans for future research
...
No Data?
• Still need a data management plan
• Plans with no data and no sharing will likely be
examined more closely
– Ca...
Exercise
• Conduct a quick inventory of the data you will
acquire
– What data will you collect?
– Is your data unique?
– H...
2. WHAT STANDARDS WILL I USE TO
DOCUMENT THE DATA?
What would someone unfamiliar
with your data need in order to find,
evaluate, understand, and reuse
them?
Documentation
• Consider the difference in documenting for
– someone inside your lab
– someone outside your lab but in you...
Documentation
Methods
• How the data were
gathered
• How the data should be
interpreted
• What you did
– Limitations on wh...
Methods
• Examples of methods to document
– Code
– Survey
– Codebook
– Data dictionary
– Anything that lets someone reprod...
Metadata
• Look for a metadata scheme before you collect
the data!
– Lots of metadata schemas available
– Easier to record...
Metadata Example: Dublin Core
• Contributor
– Jane Collaborator
• Creator
– Kristin Briney
• Date
– 2013 Apr 15
• Descript...
Exercise
• What methods information do you need to
preserve?
• What metadata standard will you use for your
data? -OR- Who...
3. HOW WILL I PROTECT
PRIVATE/SECURE/CONFIDENTIAL DATA?
Security Issues
• Does your data fall under the following?
– HIPAA
• Health information
– FERPA
• Student information
– FI...
Security Issues
• Secure storage
• Controlled access
• De-identification of personal information
• Security training
Security Questions
• Access permissions
– Who is allowed to access the data?
• Sharing
– Am I required to share? Can I act...
UWM Security Resources
• UWM Information Security Office
– Visit: https://www4.uwm.edu/itsecurity/
– Email: infosec@uwm.ed...
Exercise
• Do any regulations apply to your data?
• If so, who is allowed to access your secure
data? Who will be responsi...
4. HOW WILL I ARCHIVE AND
PRESERVE THE DATA?
Archiving Is Not Storage
• Storage is keeping files to access
• Archiving is about preservation
– Data should be readable ...
Side Note
• If federally funded, you are required to retain
your data “for a period of three years from the
date of submis...
File Formats
• Easy way to ensure long-term usability
• Use open file formats
– Open and standardized
– Well documented
– ...
Other Preservation Concerns
• Obsolescence
– Preserve software along with data
• Deterioration
– Keep more than 1 copy to ...
Find a Trustworthy Partner
• Find outside help
– Servers come and go, so do labs
• Off campus
– Disciplinary data reposito...
Exercise
• What open file formats will you use to help
preserve your data?
• If there isn’t an adequate open format, what
...
5. HOW WILL I PROVIDE ACCESS TO
AND ALLOW REUSE OF THE DATA?
Why Share?
• Get more credit for your work
– In “studies that created gene expression
microarray data, we found that studi...
Why Share?
• Make your funder happy
• Helps you find and use your data later
• Disprove misconduct or fraud accusations
• ...
Audience
• Who is the audience for this data?
– Coworkers?
– Disciplinary/institutional colleague?
– Researchers in allied...
Ways To Provide Access
• Hands-off options preferable
– Journal
– Disciplinary repository
• Embargoes may be possible here...
Exercise
• Who is the audience for your data?
• Which way will you provide access?
RESOURCES
Resources
• Data Services Librarian
– briney@uwm.edu
• Data management information
– dataplan.uwm.edu
• UWM Information Se...
Thank You
• This presentation is available on Slideshare
– http://www.slideshare.net/kbriney
• The content of this present...
Questions?
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Creating a Data Management Plan

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This talk walks through the parts of a data management plan and how to build a management plan for a research project.

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Creating a Data Management Plan

  1. 1. Creating a Data Management Plan Kristin Briney, PhD Data Services Librarian
  2. 2. This Session Will Answer • Why am I being asked to create a DMP? • What are the key parts of a DMP? • How do I translate my research to each of these parts?
  3. 3. You Will Leave With • An understanding of the main parts of a data management plan • Knowledge of where to find resources and assistance  Rough outline of your data management plan
  4. 4. WHY AM I BEING ASKED TO CREATE A DATA MANAGEMENT PLAN?
  5. 5. Why Data? Why Now? • Data are DIGITAL – Easy to copy and share – Difficult to preserve • Data are COMPUTABLE – New avenues of research like data mining • Data represent a FINANCIAL INVESTMENT – Poor research funding climate – Can no longer ignore data as a scholarly product
  6. 6. Many Funders Require DMPs • NSF • NEH • NIH • NOAA • NASA • …even more funders will require DMPs soon! – White House OSTP Public Access memo
  7. 7. The Funder Perspective • Data is a scholarly resource – Data sharing akin to scholarly publishing • Barriers to sharing are – Organization – Documentation – Long-term management and preservation  Hence data management plans
  8. 8. DMPs Help You Too! • Don’t loose data • Find data more easily • Easier to analyze organized, documented data • Avoid accusations of fraud & misconduct • Get credit for your data • Don’t drown in irrelevant data!
  9. 9. For each minute of planning at beginning of a project, you will save 10 minutes of headache later
  10. 10. DMPs Help You Too! A data management plan will make conducting research easier for you… …So if you are required to create a DMP, why not use it to improve your practices?
  11. 11. WHAT ARE THE KEY PARTS OF A DATA MANAGEMENT PLAN?
  12. 12. Actual NSF DMP Requirements • The types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project • The standards to be used for data and metadata format and content • Policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements • Policies and provisions for re-use, re-distribution, and the production of derivatives • Plans for archiving data, samples, and other research products, and for preservation of access to them http://www.nsf.gov/pubs/policydocs/pappguide/nsf13001/gpg_2.jsp#dmp
  13. 13. Key Questions 1. What data will I create? 2. What standards will I use to document the data? 3. How will I protect private/secure/confidential data? 4. How will I archive and preserve the data? 5. How will I provide access to and allow reuse of the data?
  14. 14. Be Aware • Actual requirements vary by funder and division • Look up your requirements before you write your DMP
  15. 15. HOW DO I TRANSLATE MY RESEARCH TO EACH OF THESE PARTS?
  16. 16. 1. WHAT TYPES OF DATA WILL I CREATE?
  17. 17. What Are Data? • “Research data is defined as the recorded factual material commonly accepted in the scientific community as necessary to validate research findings” – OMB Circular A-110 http://www.whitehouse.gov/omb/circulars_a110
  18. 18. What Are Data? • Observational – Sensor data, telemetry, survey data, sample data, images • Experimental – Gene sequences, chromatograms, toroid magnetic field data • Simulation – Climate models, economic models • Derived or compiled – Text and data mining, compiled database, 3D models, data gathered from public documents
  19. 19. What Not To Share • Laboratory notebooks • Preliminary analyses • Drafts of scientific papers • Plans for future research • Peer reviews or communications with colleagues • Physical Samples
  20. 20. No Data? • Still need a data management plan • Plans with no data and no sharing will likely be examined more closely – Carefully explain situation if you are in this position
  21. 21. Exercise • Conduct a quick inventory of the data you will acquire – What data will you collect? – Is your data unique? – How big will the data be? – How fast will the data grow?
  22. 22. 2. WHAT STANDARDS WILL I USE TO DOCUMENT THE DATA?
  23. 23. What would someone unfamiliar with your data need in order to find, evaluate, understand, and reuse them?
  24. 24. Documentation • Consider the difference in documenting for – someone inside your lab – someone outside your lab but in your field – someone outside your field • Audience matters!
  25. 25. Documentation Methods • How the data were gathered • How the data should be interpreted • What you did – Limitations on what you did • …build trust in your data Metadata • What you’re looking at • Who made it and when • How it got there • What it means • What you can do with it • …before you even look at the file
  26. 26. Methods • Examples of methods to document – Code – Survey – Codebook – Data dictionary – Anything that lets someone reproduce your results • Don’t forget the units!
  27. 27. Metadata • Look for a metadata scheme before you collect the data! – Lots of metadata schemas available – Easier to record metadata when collecting data than to convert later • Consult – Disciplinary repository • Repositories usually have required metadata schemas – Your peers – Subject librarian
  28. 28. Metadata Example: Dublin Core • Contributor – Jane Collaborator • Creator – Kristin Briney • Date – 2013 Apr 15 • Description – A microscopy image of cancerous breast tissues under 20x zoom. This image is my control, so it has only the standard staining describe on 2013 Feb 2 in my notebook. • Format – JPEG • Identifier – IMG00057.jpg • Relation – Same sample as images IMG00056.jpg and IMG00055.jpg • Subject – Breast cancer • Title – Cancerous breast tissue control
  29. 29. Exercise • What methods information do you need to preserve? • What metadata standard will you use for your data? -OR- Who will you contact to find a relevant standard?
  30. 30. 3. HOW WILL I PROTECT PRIVATE/SECURE/CONFIDENTIAL DATA?
  31. 31. Security Issues • Does your data fall under the following? – HIPAA • Health information – FERPA • Student information – FISMA • Government subcontractor – Human subject research, etc.  Ask for help!
  32. 32. Security Issues • Secure storage • Controlled access • De-identification of personal information • Security training
  33. 33. Security Questions • Access permissions – Who is allowed to access the data? • Sharing – Am I required to share? Can I actually share? – Despite requirements, some data can’t be shared • Responsibility – Who will make sure the data stays secure?
  34. 34. UWM Security Resources • UWM Information Security Office – Visit: https://www4.uwm.edu/itsecurity/ – Email: infosec@uwm.edu • Certificate in Information Security • HIPAA – https://www4.uwm.edu/legal/hipaa/index.cfm • FERPA – http://www4.uwm.edu/academics/ferpa.cfm
  35. 35. Exercise • Do any regulations apply to your data? • If so, who is allowed to access your secure data? Who will be responsible for data security?
  36. 36. 4. HOW WILL I ARCHIVE AND PRESERVE THE DATA?
  37. 37. Archiving Is Not Storage • Storage is keeping files to access • Archiving is about preservation – Data should be readable and usable – Data should be uncorrupted • We can’t read some digital files from 10 years ago – This is what good digital preservation solves
  38. 38. Side Note • If federally funded, you are required to retain your data “for a period of three years from the date of submission of the final expenditure report.” AT LEAST. • Better to keep on hand for at least 6 years – Recent retraction in 6-year old paper for failure to provide original data • Preservation not an abstract issue http://www.whitehouse.gov/omb/circulars_a110#53 http://retractionwatch.wordpress.com/2013/07/19/jci-paper-retracted-for-duplicated-panels-after-authors-cant-provide- original-data/
  39. 39. File Formats • Easy way to ensure long-term usability • Use open file formats – Open and standardized – Well documented – In wide use – Examples: .txt, .tiff, .csv, .dbf • Transform your data now, not later – Keep both file types
  40. 40. Other Preservation Concerns • Obsolescence – Preserve software along with data • Deterioration – Keep more than 1 copy to avoid corruption • Media – ie. Can you still read a floppy disk? – Periodically move data off outdated media
  41. 41. Find a Trustworthy Partner • Find outside help – Servers come and go, so do labs • Off campus – Disciplinary data repository – Journal that accepts data • Let someone else worry about this
  42. 42. Exercise • What open file formats will you use to help preserve your data? • If there isn’t an adequate open format, what software and hardware will you preserve?
  43. 43. 5. HOW WILL I PROVIDE ACCESS TO AND ALLOW REUSE OF THE DATA?
  44. 44. Why Share? • Get more credit for your work – In “studies that created gene expression microarray data, we found that studies that made data available in a public repository received 9% … more citations than similar studies for which the data was not made available” – “The citation boost varied with date of dataset deposition: a citation boost was most clear for papers published in 2004 and 2005, at about 30%” • Get credit for unpublishable results https://peerj.com/preprints/1/ (2013 study)
  45. 45. Why Share? • Make your funder happy • Helps you find and use your data later • Disprove misconduct or fraud accusations • Stimulate new research
  46. 46. Audience • Who is the audience for this data? – Coworkers? – Disciplinary/institutional colleague? – Researchers in allied fields? – Anyone? • Audience will determine how to share the data
  47. 47. Ways To Provide Access • Hands-off options preferable – Journal – Disciplinary repository • Embargoes may be possible here – UWM Digital Commons • Small, discrete datasets • Other options – By request – On your lab website
  48. 48. Exercise • Who is the audience for your data? • Which way will you provide access?
  49. 49. RESOURCES
  50. 50. Resources • Data Services Librarian – briney@uwm.edu • Data management information – dataplan.uwm.edu • UWM Information Security Office – infosec@uwm.edu
  51. 51. Thank You • This presentation is available on Slideshare – http://www.slideshare.net/kbriney • The content of this presentation is licensed under a Creative Commons Attribution 3.0 Unported License (CC BY) • Some content used with permission from Brad Houston and Dorothea Salo
  52. 52. Questions?
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