Michigan State University campus policy, resources and best practices for research data management offered by the MSU Libraries Research Data Management Guidance service. http://www.lib.msu.edu/rdmg/

1. MSU Libraries
Research Data Management
Research Data
Management
Aaron Collie
collie@msu.edu
@aaroncollie

2. MSU Libraries
Research Data Management
Introductions
• Please tell us your
name and department
• A brief description of
your primary research
area
• What do you consider
to be your research
data
• Experience and/or
comfort level with
managing research
data?
cc http://www.flickr.com/photos/quinnanya/

3. MSU Libraries
Research Data Management
• Introduction
• Background
• The Impetus: NSF Data Management Plan Mandate
• The Effect: Policy to Practice
• The Response: Changing Data Landscape
• Fundamentals Practices
• File Organization
• Data Documentation
• Reliable Backup
• Data Publishing, Sharing, & Reuse
• Protecting Data & Responsible Reuse
• Data Lifecycle Resources
Agenda

4. MSU Libraries
Research Data Management
Volunstrordinaries!
Aaron
Collie
Hailey
Mooney
Devin Higgins Brandon
Locke
Ranti Junus Thomas
Padilla
Judy
Matthews
Tina Qin

5. MSU Libraries
Research Data Management
We teach people about RDM
Librarianship
Training
Assessment
Consultation
Ad-hoc
6-12 new clients per semester
100% satisfied / 100% would use
again
71% of new clients are referrals
60% requested additional services
15% through NFO, 14% through
website

6. MSU Libraries
Research Data Management
RDM@MSU 101
• Who: You, as the designated steward
• What: “the data”
• When: Minimum 3 years after
publ./degree
• Where: Managed networked storage
• Why: Legal, Ethical, Scholarly
• How: With fidelity and documentation
sufficient to reproduce the research

7. MSU Libraries
Research Data Management
http://retractionwatch.com/2014/01/07/doing-the-right-thing-authors-retract-brain-paper-with-systematic-human-error-in-coding/

8. MSU Libraries
Research Data Management
Jen Doty and Rob O'Reilly, “Learning to Curate @ Emory”. RDAP 2014

9. MSU Libraries
Research Data Management
Data Management. Isn’t that…
trivial?
• Not so much. Data is a primary output of research; it is
very expensive to produce high quality data. Data may
be collected in nanoseconds, but it takes the expert
application of research protocol and design to generate
data.
CC-BY-SA-3.0 Rob Lavinsky CC-BY-SA-3.0 Rob

10. MSU Libraries
Research Data Management
Even more consequential, data is the input
of a process that generates higher orders of
understanding.
Wisdom
Knowledge
Information
Data
Understanding is
hierarchical!
Russell Ackoff

11. MSU Libraries
Research Data Management
This is the engine of the academic
industry…

12. MSU Libraries
Research Data Management

13. MSU Libraries
Research Data Management
So, things can get a little messy.

14. MSU Libraries
Research Data Management
The scientific method “is often
misrepresented as a fixed
sequence of steps,” rather than
being seen for what it truly is,
“a highly variable and creative
process” (AAAS 2000:18).
Gauch, Hugh G. Scientific Method in Practice. New York: Cambridge University Press, 2010. Print. (Emphasis added)

15. MSU Libraries
Research Data Management

16. MSU Libraries
Research Data Management
The Research Depth Chart
Scientific Method
Research Design
Research Method
Research Tasks
MoreSpecificMoreGeneric

17. MSU Libraries
Research Data Management
Problem
Identification
Study Concept
Literature
Review
Environmental
Scan
Funding &
Proposal
Research
Design
Research
Methodology
Research
Workflow
Hypothesis
Formation
Design
Validation
Research
Activity
Data
Management
Data
Organization
Data
Storage
Data
Description
Data Sharing
Scholarly
Communication
Report
Findings
Publish
Peer Review

18. MSU Libraries
Research Data Management
Problem
Identification
Study Concept
Literature
Review
Environmental
Scan
Funding &
Proposal
Research
Design
Research
Methodology
Research
Workflow
Hypothesis
Formation
Design
Validation
Research
Activity
Data
Management
Data
Organization
Data
Storage
Data
Description
Data Sharing
Scholarly
Communication
Report
Findings
Publish
Peer Review

19. MSU Libraries
Research Data Management
• Introduction
• Background
• The Impetus: NSF Data Management Plan Mandate
• The Effect: Policy to Practice
• The Response: Changing Data Landscape
• Fundamentals Practices
• File Organization
• Data Documentation
• Reliable Backup
• Data Publishing, Sharing, & Reuse
• Protecting Data & Responsible Reuse
• Data Lifecycle Resources
Agenda

20. MSU Libraries
Research Data Management
Data Management
• The process of
planning for and
implementing a
system of care for
your research data
before, during, and
after a research
project in order to
ensure a (re)usable
resource.

21. MSU Libraries
Research Data Management
So why are we here?
Good science!
Government and Research
Funder Mandates

22. MSU Libraries
Research Data Management
But why are we really here?
• Impetus: NSF has mandated that all grant applications
submitted after January 18th, 2011 must include a
supplemental “Data Management Plan”
• Effect: The original NSF mandate has had a domino
effect, and many funders now require or state guidelines
for data management of grant funded research
• Response: Data management has not traditionally
received a full treatment in (many) graduate and doctoral
curricula; intervention is necessary

23. MSU Libraries
Research Data Management
Positive reinforcement….
• National Science Foundation Data
Management Plan mandate (January 18,
2011)
• Presidential Memorandum on Managing
Government Records (August 24, 2012)
– Managing Government Records Directive: All
permanent electronic records in Federal
agencies will be managed electronically to the
fullest extent possible for eventual transfer
and accessioning by NARA in an electronic
format.

24. MSU Libraries
Research Data Management
Positive reinforcement… (cont.)
• White House policy memo (February 22,
2013)
– Increasing Access to the Results of Federally Funded Scientific
Research: Federal agencies with more than $100M in R&D
expenditures must develop plans to make the published results
of federally funded research freely available to the public within
one year of publication.
• OSTP policy memo (March 20, 2014)
– Improving the Management of and Access to Scientific
Collections: directs each Federal agency that owns, maintains,
or otherwise financially supports permanent scientific collections
to develop a draft scientific-collections management and access
policy within six months.

25. MSU Libraries
Research Data Management
Positive reinforcement… (cont. w/
teeth!)
• AHRQ = “…all AHRQ-funded researchers will be
required to include a data management plan for
sharing final research data in digital format, or state
why data sharing is not possible.
• NASA = This plan extends NASA’s culture of open
data access to all NASA-funded research.”
• USDA = Phased approach beginning with DMP
• More: http://www.arl.org/focus-areas/public-access-
policies/federally-funded-research/2696-white-house-
directive-on-public-access-to-federally-funded-
research-and-data#agency-policies

26. MSU Libraries
Research Data Management
Funder Policies
NASA “promotes the full and open sharing of all data”
“requires that data…be submitted to and archived by
designated national data centers.”
“expects the timely release and sharing of final research data"
"IMLS encourages sharing of research data."
“…should describe how the project team will manage and
disseminate data generated by the project”

27. MSU Libraries
Research Data Management
 Policies for re-use, re-distribution, and creation of
derivatives
 Plans for archiving data, samples, and other research
outcomes, maintaining access
 Types of data, samples, physical collections, software
generated
• Standards for data and metadata format and content
• Access and sharing policies, with stipulations for
privacy, confidentiality, security, intellectual property, or
other rights or requirements

28. MSU Libraries
Research Data Management
• NSF will not evaluate any proposal
missing a DMP
• PI may state that project will not generate
data
• DMP is reviewed as part of intellectual
merit or broader impacts of application, or
both
• Costs to implement DMP may be included
in proposal’s budget
• May be up to two pages long

29. MSU Libraries
Research Data Management
• Investigators seeking $500,000 or more in direct costs in any year
should include a description of how final research data will be
shared, or explain why data sharing is not possible.
• The precise content of the data-sharing plan will vary, depending on
the data being collected and how the investigator is planning to
share the data.
• More stringent data management and sharing requirements may be
required in specific NIH Funding Opportunity Announcements.
Principal Investigators must discuss how these requirements will be
met in their Data Sharing Plans.

30. MSU Libraries
Research Data Management
 Roles and responsibilities
 Expected Data
 Period of data retention
• Data formats and dissemination
• Data storage and preservation of access

31. MSU Libraries
Research Data Management
Local Policy
University Research Council Best Practices:
https://rio.msu.edu/research-data
Research Data: Management, Control, and
Access
– To assure that research data are appropriately
recorded, archived for a reasonable period of
time, and available for review under the
appropriate circumstances.
• Ownership = MSU
• “Stewardship” = You
• Period of Retention = 3 years
• Transfer of Responsibility = Written Request

32. MSU Libraries
Research Data Management
Broader Response: Changing
Data Landscapes
• Data Management Competencies
– Standards & Best Practices
– Discipline Specific Discourse
• Data sharing and open data
– Data sets as publications
– Data journals
– Citations for data (e.g., used in secondary
analysis)
– Data as supplementary materials to traditional
articles
– Data repositories and archives

33. MSU Libraries
Research Data Management
Curation responsibilities (Carlson, The Chronicle, 2006)
“Data from Big Science is … easier to handle, understand and archive.
Small Science is horribly heterogeneous and far more vast. In time Small
Science will generate 2-3 times more data than Big Science.”
big science
data
small science data
institution?
domain?
MacColl, John (2010). The Role of libraries in data curation. RLG Partnership Annual Meeting, Chicago. June 2010

34. MSU Libraries
Research Data Management
What’s in it for me?
• Better organization = less headaches
– Course management
– Bibliographic management
– File management
– Research
• Career advancement
– Publish datasets and list on your CV
– Data management is an “unnamed practice” –
name it for yourself and your students!

35. MSU Libraries
Research Data Management
Data Sharing Impacts
• Reinforces open
scientific inquiry
• Encourages diversity
of analysis and opinion
• Promotes new
research, testing of
new or alternative
hypotheses and
methods of analysis
• Supports studies on
data collection
methods and
measurement
Cc http://www.flickr.com/photos/pinchof_10/

36. MSU Libraries
Research Data Management
Data Sharing Impacts
• Facilitates education
of new researchers
• Enables exploration
of topics not
envisioned by initial
investigators
• Permits creation of
new datasets by
combining data from
multiple sources

37. MSU Libraries
Research Data Management
• Introduction
• Background
• The Impetus: NSF Data Management Plan Mandate
• The Effect: Policy to Practice
• The Response: Changing Data Landscape
• Fundamentals Practices
• File Organization
• Data Documentation
• Reliable Backup
• Data Publishing, Sharing, & Reuse
• Protecting Data & Responsible Reuse
• Data Lifecycle Resources
Agenda

38. MSU Libraries
Research Data Management
Research Data Management
Fundamentals
• Documentation
• File Organization
• Storage & Backup
• Data Publishing, Sharing,
& Reuse
• Protecting Data
& Responsible Reuse

39. MSU Libraries
Research Data Management
Documentation Practices:
Overview
• Researchers benefit from proper
documentation to decipher or reuse their
datasets – even prior to thinking about
sharing
• Think “downstream”

40. MSU Libraries
Research Data Management
Documentation Practices: Overview
1. At minimum create a
README file that you can
use to document your
project
2. Utilize standards for
describing data including
Metadata Standards
3. If applicable, use in-line
code commentary to
explain code
(cc) Will Scullin

41. MSU Libraries
Research Data Management
Create a README file
• At minimum, store documentation in
readme.txt file or equivalent, with data
– What data consists of
– How it was collected
– Restrictions to distribution or use
– Other descriptive information

42. MSU Libraries
Research Data Management
• “Data about data”
• Standardized way of describing data
• Explains who, what, where, when of data
creation and methods of use
• Data more easily found
• Data more easily compared to other data sets
Use Metadata Standards

43. MSU Libraries
Research Data Management
Use Metadata Standards
Basic project metadata:
• Title • Language • File Formats
• Creator • Dates • File Structure
• Identifier • Location • Variable List
• Subject • Methodology • Code Lists
• Funders • Data Processing • Versions
• Rights • Sources • Checksums
• Access
Information
• List of File Names

44. MSU Libraries
Research Data Management
Use Metadata Standards
• Dublin Core: Commonly-used descriptive
metadata format facilitates dataset discovery
across the Web.
• Data Documentation Initiative (DDI): Defines
metadata content, presentation, transport, and
preservation for the social and behavioral
sciences.
• ISO 19115:2003: Describes geographic data such
as maps and charts.
• More
examples:http://www.lib.msu.edu/about/diginfo/coll
ect.jsp

45. MSU Libraries
Research Data Management
Use In-Line Code Commentary
Example of R code commentary
# Cumulative normal density
pnorm(c(-1.96,0,1.96))
• If applicable, in-line code commentary helps
explain code

46. MSU Libraries
Research Data Management
File Organization Practices:
Overview
1. Design a file plan
for your research
project
2. Use file naming
conventions that
work for your project
3. Choose file formats
to maximize
usefulness
“When I was a
freshmen I named
my assignments
Paper Paperr
Paperrr Paperrrr”
-Undergrad

47. MSU Libraries
Research Data Management
Design a File Plan
• File structure is the framework
• Classification system makes it easier to
locate folders/files
• Benefits:
– Simple organization intuitive to team
members and colleagues
– Reduces duplicate copies in personal drives
and e-mail attachments

48. MSU Libraries
Research Data Management
Design a File Plan
Choose a sortable directory hierarchy
• Example 1: Investigator, Process, Date
Collie
TEI_Encoding
20110117
• Example 2: Instrument, Date, Sample
Usability Survey
2012043
sample_1

49. MSU Libraries
Research Data Management
Design a File Plan
Example documentation of Directory Hierarchy:
/[Project]/[Grant Number]/[Event]/[Investigator/Date]

50. MSU Libraries
Research Data Management
Use File Naming Conventions
– Enable better access/retrieval of files
– Create logical sequences for file sorting
– More easily identify what you’re searching for

51. MSU Libraries
Research Data Management
• Meaningful but short—255 character limit
• Use alphanumeric characters
– Example: abc123
• Capital letters or underscores differentiate
between words
• Surname first followed by initials of first name
Use File Naming Conventions

52. MSU Libraries
Research Data Management
• Year-month-day format for dates, with or
without hyphens
Example 1: 2006-03-13
Example 2: 20060313
• Decide on a simple versioning method
Example: file_v001
Use File Naming Conventions

53. MSU Libraries
Research Data Management
• To create consistent file names, specify a
template such as:
[investigator]_[descriptor]_[YYYYMMDD].[ex
t]
Use File Naming Conventions
This Not This
sharpeW_krillMicrograph_backscatter3_20110117.tif KrillData2011.tif
This Not This
borgesJ_collocation_20080414.xml Borges_Textbase.xml

54. MSU Libraries
Research Data Management
Choose Appropriate File Formats
• Non-proprietary
• Open, documented standard
• Common usage by research community
• Standard representation (ASCII, Unicode)
• Unencrypted
• Uncompressed

55. MSU Libraries
Research Data Management
Choose Appropriate File Formats
Format Genre Optimal Standards
TEXT .txt; .odt; .xml; .html
AUDIO .flac; .wav,
VIDEO .mp2/.mp4; .mkv
IMAGE .tif; .png; .svg; .jpg
DATA .sql; .csv

56. MSU Libraries
Research Data Management
Storage & Backup Practices
1. Avoid single points of
failure
2. Ensure data redundancy &
replication
3. Understand common
types of storage
(cc) George Ornbo
Data at significant risk of loss without storage
and backup plan

57. MSU Libraries
Research Data Management
Avoid Single Points of Failure
A single point of failure occurs when it
would only take one event to destroy all
data on a device
• Use managed networked storage when
possible
• Move data off of portable media
• Never rely on one copy of data
• Do not rely on CD or DVD copies to be
readable
• Be wary of software lifespans

58. MSU Libraries
Research Data Management
Ensure Data Redundancy
• Effective data storage plan provides for 3
copies:
– Primary authoritative copy
– Secondary local backup
– Tertiary remote backup
• Geographically distribute and secure
– Local vs. remote, depending on needed recovery
time
• Personal computer, external hard drives,
departmental, or university servers may be
used

59. MSU Libraries
Research Data Management
Ensure Data Redundancy
• Cloud storage
– Amazon s3
– Google
– MS Azure
– DuraCloud
– Rackspace
– Glacier
Note that many enterprise
cloud storage services
include a charge for in/out of
data transfers
$$$

60. MSU Libraries
Research Data Management
Understand Common Types of
Storage
• Optical Media
• Portable Flash Media
• Commercial Hard Drives
• Commercial NAS
• Cloud Storage
• Enterprise Network Storage
• Trusted Archival Storage

61. MSU Libraries
Research Data Management
Understand Common Types of
Storage
• Features of storage types:
• Portable data transfers
• Short-term storage
• Project term storage
• Networked data transfer
• Long-term storage
• Reliable backup option

62. MSU Libraries
Research Data Management
Understand Common Types of
StoragePortable
Data
Transfer
Short
Term
Storage
Project
Term
Storage
Networked
Data Transfer
Long
Term
Storage
Reliable
Backup
Option
Optical Media ✔ ✗ ✗ ✗ ✗ ✗
Portable Flash
Media
✔ ✔ ✗ ✗ ✗ ✗
Commercial Hard
Drives
✔ ✔ ✔ ✗ ✗ ✗
Commercial NAS ✗ ✔ ✔ ✔ ✗ ✗
Cloud Storage ✗ ✔ ✔ ✔ ✗ ✗
Enterprise Network
Storage
✗ ✔ ✔ ✔ ✔ ✔
Trusted Archival
Storage
✗ ✗ ✗ ✔ ✔ ✔

63. MSU Libraries
Research Data Management
Understand Common Types of
Storage
Media Storage @ MSU
Optical Media MSU Computer Store—Sells Optical Media and hardware accessories
UAHC Media Storage Service—Offers physical lock-box like storage for MSU
Flash Media MSU Computer Store—Sells Optical Media and hardware accessories
UAHC Media Storage Service—Offers physical lock-box like storage for MSU
Commercial Hard
Drives
MSU Computer Store—Sells Optical Media and hardware accessories.
UAHC Media Storage Service—Offers physical lock-box like storage for MSU
Enterprise Cloud
Storage
Angel—Free. Ideal for collaboration; not storage space. Phase out 2015
Desire2Learn—Free. Ideal for collaboration; not storage space. Replaces Angel
GoogleApps—Free. Ideal for collaboration; not intended as storage space
Enterprise
Network Storage
AFS Space—Free to 1GB, add’l space can be purchased w/dept. account
IT Services Individual, Mid-Tier and Enterprise Storage—Fee based
HPCC Home or Research—Free up to 1TB. Fee based additions available
Trusted Archival
Storage
Disciplinary Repositories – Disciplinary repositories offer archival services for
pertinent research data.

64. MSU Libraries
Research Data Management
Data Publishing, Sharing, Reuse
1. Time-intensive, with potentially
high return on investment
2. Publish data in several data
publication venues to more
broadly share results of research
Research datasets on par with peer-reviewed
journal articles as first-class scholarly contributions

65. MSU Libraries
Research Data Management
Sharing & Publishing Data
• Data preparation for sharing and publication
is a time-intensive process
• Potential positive outcomes:
• Increased research impact and citations
• Enable additional scientific inquiry
• Opportunities for co-authorship and
collaboration
• Enhance your grant proposal’s
competitiveness

66. MSU Libraries
Research Data Management
Data Publication Venues
• Multiple ways to publish research data
• Faculty or project website
• Journal supplementary materials
• Disciplinary data repository (data archive)
• Varying levels of support for indexing, access
controls, and long-term curation

67. MSU Libraries
Research Data Management
Data Publication Venues
• Disciplinary Data Repository
• Securely share data, ensure long-term access
• High visibility
• Often offer persistent citations
• Availability varies across domains
• Databib.org directory

68. MSU Libraries
Research Data Management
Data Publication Venues
• Disciplinary Data Repository
• Securely share data, ensure long-term access
• High visibility
• Often offer persistent citations
• Availability varies across domains
• Databib.org directory

69. MSU Libraries
Research Data Management
Protecting Data & Responsible Reuse
1. Consider how to protect
data and intellectual
property rights while
encouraging reuse
2. Keep in mind ethical
concerns when sharing
data
(cc) Will Scullin

70. MSU Libraries
Research Data Management
Intellectual Property
• IP refers to exclusive rights of creators of
works
• Individual data cannot be protected by US
copyright
• Organization of data such as database,
creative work produced by data, and research
instruments used may be protected
©

71. MSU Libraries
Research Data Management
Intellectual Property
• Principal investigator’s institution holds IP
rights
• Provide clearly stated license for producing
derivatives, reusing, and redistributing
datasets
• License under Creative Commons
• State if any restrictions or embargos on use
• Provide example of how work should be cited
to encourage proper attribution on reuse
• Document any IP / copyright issues

72. MSU Libraries
Research Data Management
Ethics & Data Sharing
• Keep in mind the following ethical concerns
when sharing your data:
• Privacy
• Confidentiality
• Security and integrity of the data
• For data involving human subjects, obtain
written permission or consent stating how the
data may be reused

73. MSU Libraries
Research Data Management
Best Practices = High Impact Data
• File organization ensures easier access and
retrieval of data
• Documentation makes datasets accessible
and intelligible to users
• Storage and backup safeguards data
• Data publishing and sharing encourages the
most widespread reuse of data
• Data protection ensures responsible reuse

74. MSU Libraries
Research Data Management
• Introduction
• Background
• The Impetus: NSF Data Management Plan Mandate
• The Effect: Policy to Practice
• The Response: Changing Data Landscape
• Fundamentals Practices
• File Organization
• Data Documentation
• Reliable Backup
• Data Publishing, Sharing, & Reuse
• Protecting Data & Responsible Reuse
• Data Lifecycle Resources
Agenda

75. MSU Libraries
Research Data Management
http://www.lib.msu.edu/rdmg

76. MSU Libraries
Research Data Management
Contact
Aaron Collie
collie@msu.edu
@aaroncollie
http://www.lib.msu.edu/rdmg