This document outlines a training course on research data management (RDM) that covers the importance of planning, documentation, and sharing research data. It highlights federal mandates for RDM, including the requirements set by organizations like the NSF and NIH for data management plans. Additionally, it discusses the roles and responsibilities of researchers in managing data to ensure integrity, facilitate discovery, and enhance the visibility of their research.

1. Managing Research Data
Part 1
Planning Working
Finalizing
Sharing
Data
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WHY – WHAT– WHO – WHEN & HOW

2. WHY manage data -
WHAT research data are-
WHO manages research data -
WHEN & HOW data management is done -
Planning Working
Finalizing
Sharing
Data
Managing Research Data
This work is licensed under a Creative Commons
Attribution 4.0 International License.

3. This two-part course is a collaboration between CU Libraries/
Information Services and the Office of Research Compliance &
Training. The purpose of this course is to familiarize you with the
various aspects of research data management (RDM) by taking
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Managing Research Data
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Managing Research Data
This course will guide you through these areas, offering in-depth
details on each of them. Please refer to the top navigation to keep
track of which area you are currently exploring.
• Why RDM is both recommended and required
• What research data are
• Who is responsible for RDM
• When RDM activities occur
• How you can carry out RDM activities
Part 1:
Part 2:

4. Learning objectives:
At the end of this training you will be able to:
• Define & identify research data
• Understand the demands of responsible conduct of research with
regard to research data management
• Understand the reasons behind the federal mandates of research data
management
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Managing Research Data
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Managing Research Data

5. Links to many of the references and
policies referred to in this course can be
found on the final slides.
Have Fun!
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Managing Research Data
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Managing Research Data

6. Why should you care about
Research Data Management?
WHY –WHAT – WHO – WHEN & HOW
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Managing Research Data

7. WHY –WHAT – WHO – WHEN & HOW
Managing research data:
SAVES TIME
Taking time to plan for your expected data, back them up, and document
them in detail saves time otherwise lost in searching for, recovering, and
deciphering data in the future
SIMPLIFIES YOUR LIFE
Managing your data, by adopting an organization scheme, developing a
description standard, and creating a preservation plan avoids future
confusion and turmoil
INCREASES RESEARCH EFFICIENCY
By saving time and avoiding confusion you will be more efficient! Manage
your data for the future and you will be able to more easily find, access,
understand, and use your data
ENSURES RESEARCH INTEGRITY
Good research data management makes it more feasible to fulfill the
commitments of responsible research
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Managing Research Data

8. Up to 80% of data lost within 20 years of
publication:
http://www.nature.com/news/scientists-losing-data-at-a-rapid-rate-1.14416
516 ecology papers
published between
1991 and 2011
The chance of data
being accessible fell by
17% per year
Vines, T. H. et al. Curr. Biol.
http://dx.doi.org/10.1016/j.cub.
2013.11.014 (2013)
8
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Managing Research Data

9. When you engage in research at Columbia
University you must:
• Be ethical in the conduct of the research
• Abide by regulations and policies
• Be responsible stewards of the research dollars and other resources
• Share the results of your research for the good of society
Managing data is a critical responsibility
for all researchers
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Managing Research Data

10. • Increases visibility
• Facilitates discovery
• Satisfies funder & journal requirements
• Reinforces open scientific inquiry
• Establishes priority & enables citation
• Speeds research
Adapted from: https://libraries.mit.edu/guides/subjects/data-management/
why.html & http://researchdata.wisc.edu/share-your-data/data-access-2/10
WHY –WHAT – WHO – WHEN & HOW
Managing research data enables
sharing, which:
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Managing Research Data

11. Sharing enables breakthroughs
that lead to economic
development:
http://www.whitehouse.gov/sites/default/files/microsites/ostp/
ostp_public_access_memo_2013.pdf11
WHY –WHAT – WHO – WHEN & HOW
“Scientific research supported by the Federal Government
catalyzes innovative breakthroughs that drive our economy. The
results of that research become the grist for new insights and are
assets for progress in areas such as health, energy, the
environment, agriculture, and national security.”
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Managing Research Data

12. “…a research
project's success is
measured … also by
the data it makes
available to the
wider community.”
“It is obvious that
making data widely
available is an
essential element of
scientific research.”
12
WHY –WHAT – WHO – WHEN & HOW
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Managing Research Data

13. The directive to make federally funded research data openly
accessible “is integrally tied to and supports the mission of
higher education to produce, preserve, and share scholarship. It
therefore provides the community with an opportunity to
marshal its resources to improve the interoperability of research
support systems and maximize the value of research funding.”
Association of Research Libraries (ARL) on the Office of Science &
Technology Policy memorandum “Increasing Access to the Results of
Federally Funded Scientific Research”
13
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Managing Research Data

14. • Funders
– Federal agencies
– Foundations
• Journals
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Managing Research Data
Data sharing is required by:

15. National Science Foundation (NSF):
https://www.nsf.gov/eng/general/dmp.jsp15
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Managing Research Data
“Beginning January 18, 2011, proposals submitted to NSF must
include a supplementary document of no more than two pages
labeled "Data Management Plan" (DMP) . This supplementary
document should describe how the proposal will conform to
NSF policy on the dissemination and sharing of research results.
Proposals that do not include a DMP will not be able to be
submitted.”

16. National Institutes of Health (NIH):
1 http://grants.nih.gov/grants/policy/data_sharing/
2 http://grants.nih.gov/grants/guide/notice-files/NOT-OD-03-032.html16
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Managing Research Data
“Data sharing is essential for expedited translation of research
results into knowledge, products and procedures to improve
human health.”1
“…all investigator-initiated applications with direct costs greater
than $500,000 in any single year will be expected to address
data sharing in their application”2

17. “The Office of Science and Technology Policy (OSTP) hereby
directs each Federal agency with over $44 million in annual
conduct of research and development expenditures to develop a
plan to support increased public access to the results of research
funded by the Federal Government.”
“…digitally formatted scientific data resulting from unclassified
research supported wholly or in part by Federal funding should
be stored and publicly accessible to search, retrieve, and
analyze.” (2013)
http://www.whitehouse.gov/sites/default/files/microsites/ostp/
ostp_public_access_memo_2013.pdf17
WHY –WHAT – WHO – WHEN & HOW
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Managing Research Data
…and not just them! More federal
agencies will be requiring public
access to data:

18. http://www.nature.com/srep/policies/index.html
http://http://www.aeaweb.org/aer/data.php
Journal Sharing Policies:
“It is the policy of the American Economic Review to
publish papers only if the data used in the analysis are
clearly and precisely documented and are readily available
to any researcher for purposes of replication. Authors of
accepted papers that contain empirical work, simulations,
or experimental work must provide to the Review, prior to
publication, the data, programs, and other details of the
computations sufficient to permit replication.”
“…authors are required to make materials, data and
associated protocols promptly available to readers.”
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Managing Research Data
WHY –WHAT – WHO – WHEN & HOW

19. http://www.sciencemag.org/site/feature/contribinfo/prep/gen_info.xhtml#dataavail
http://www.bmj.com/about-bmj/resources-authors/article-types/research
“…trials of drugs and medical devices will be considered
for publication only if the authors commit to making the
relevant anonymised patient level data available on
reasonable request”
“All data necessary to understand,
assess, and extend the conclusions of
the manuscript must be available to any
reader of Science. All computer codes
involved in the creation or analysis of
data must also be available...”
19
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Managing Research Data
Journal Sharing Policies:

20. Benefits of good data management & sharing
practices:
20
WHY –WHAT – WHO – WHEN & HOW
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Managing Research Data
• Increase citations
• Avoid retractions (& potential misconduct questions)
• Advance knowledge
• Enable reproducibility

21. Increase citations:
Piwowar HA, Day RS, Fridsma DB (2007). Sharing Detailed Research Data Is
Associated with Increased Citation Rate. PLoS ONE 2(3): e308. doi:10.1371/
journal.pone.0000308
21
WHY –WHAT – WHO – WHEN & HOW
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Managing Research Data
Publicly available data was significantly associated with a 69%
increase in citations, independent of journal impact factor, date
of publication, and author country of origin using linear
regression.

22. Avoid retractions:
http://retractionwatch.wordpress.com/2013/10/30/nejm-paper-on-sleep-apnea-
retracted-when-original-data-cant-be-found/
22
WHY –WHAT – WHO – WHEN & HOW
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Managing Research Data

23. Advance knowledge:
http://www.sciencedaily.com/releases/2013/09/130903194155.htm23
WHY –WHAT – WHO – WHEN & HOW
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Managing Research Data
“70 percent of published genetic sequence comparisons are not
publicly accessible, leaving researchers worldwide unable to get
to critical data they may need to tackle a host of problems
ranging from climate change to disease control.”

24. Enable reproducibility:
Looking at 238 recently published papers, pulled from five
fields of biomedicine, a team of scientists found that just
under 50 percent of the research materials, from lab mice
to antibodies, used in the work could not be identified.
This phenomenon impedes the ability of scientists to
reproduce & extend published studies.
Vasilevsky NA, Brush MH, Paddock H, Ponting L, Tripathy SJ et al. (2013) On the
reproducibility of science: unique identification of research resources in the
biomedical literature. PeerJ 1:e148 http://dx.doi.org/10.7717/peerj.148
24
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Managing Research Data

25. TAKE-AWAYS
25
WHY –WHAT – WHO – WHEN & HOW
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Managing Research Data
• Researchers share the products of their research (e.g.,
publications, data) for the good of:
– Society
– Advancement of science
– Themselves
• Data management is required by:
– Funding bodies
– Institutions
• Data sharing is a requirement of:
– Funding bodies
– Publishers

26. What are the research data
that need to be managed?
WHY –WHAT – WHO – WHEN & HOW
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Managing Research Data

27. WHY –WHAT – WHO – WHEN & HOW
Defining Research Data:
1 Marieke Guy. http://www.slideshare.net/MariekeGuy/bridging-the-gap-between-
researchers-and-research-data-management , #2
2 Queensland University of Technology. Manual of Procedures and Policies. Section
2.8.3. http://www.mopp.qut.edu.au/D/D_02_08.jsp
3 http://www.whitehouse.gov/omb/circulars_a110#362744/
Managing Research Data
“…information created [or discovered] in the course of
research”1
Material or information “on which an argument, theory, test or
hypothesis, or another research output is based.” 2
“(i) Research data is defined as the recorded factual material
commonly accepted in the [research] community as necessary to
validate research findings…”3

28. Data may be collected in many ways:
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Managing Research Data
WHY –WHAT – WHO – WHEN & HOW
Through real time & unique observations, from repeatable
experiments or simulations, or through derivations from unique
collections of data, as a few examples.
Data collection method costs and
risks:
Some data may be impossible to replace, some data may merely
be very expensive replace. Alternatively, some data are so cheap
and quick to acquire that it is less expensive to repeat the
collection process than to store the data, e.g., some gene
sequences.

29. Data may be classified by collection
method, which include:
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Managing Research Data
WHY –WHAT – WHO – WHEN & HOW
OBSERVATIONS – collected in real time / irreplaceable
e.g. survey results, images, telemetry, sensor readings, some literary/historical
sources, recordings
EXPERIMENTS – reproducible/ variable expense
e.g. chromatograms, antenna mappings, word frequency
SIMULATIONS – Models & inputs used to create datasets
e.g. economic models, climate models
DERIVATIONS/COMPILATIONS – reproducible/expensive
e.g. text or data mining, 3D models, compiled database
RESEARCH PROCESS DATA – real time / irreplaceable
e.g. survey instruments, data description/documentation, developed software,
algorithms, code/script, instrument settings

30. TRUE OR FALSE:
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Managing Research Data
WHY –WHAT – WHO – WHEN & HOW
In scientific research, only the information and observations
that are collected as part of your research are considered data.

31. FALSE
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Managing Research Data
WHY –WHAT – WHO – WHEN & HOW
Data are not only the information and observations made as
part of scientific research but also the materials, the means, and
the products of that research.
Examples:
• Survey instruments
• Associated software
• Cell lines
• Specimens

32. Information exists in different forms
during the research process:
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WHY –WHAT – WHO – WHEN & HOW
RAW OR PRIMARY– Lab notebooks, observational notes,
instrument readings, images, footage, individual survey
responses, historical sources, textual analysis, etc.
PROCESSED– Statistical analyses, sources organized as evidence,
rich descriptions, aggregated survey responses, etc.
PUBLISHED– Distribution in some finalized format to those
outside of the project. Distribution may occur in both static
and dynamic (e.g. longitudinal data sets with annual
reporting) instances, etc.

33. “Research data means the recorded factual material commonly
accepted in the scientific community as necessary to validate
research findings”
33
• Preliminary analyses
• Drafts of scientific papers
• Plans for future research
• Peer reviews
• Communications with colleagues.
• Trade secrets
• Commercial information
• Materials necessary to be held
confidential by a researcher until they
are published
• Information which is protected under
law
• Personnel and medical information
• Information the disclosure of which
would constitute a clearly unwarranted
invasion of personal privacy, such as
information that could be used to
identify a particular person in a
research study.
http://federalregister.gov/a/2013-3046544/
Managing Research Data
WHY –WHAT – WHO – WHEN & HOW
The federal Office of Management
and Budget offers the following
explanation (summarized):
Exclusions:
2 CFR § 200.315, Intangible property, e (3)

34. Some data on research subjects may require special protections
because they are highly sensitive and highly regulated. These
sensitive data may require encryption and other security
measures:
• Personal Health Information (PHI) e.g. insurance
information, health conditions, etc.
• Personally Identifying Information (PII) e.g. financial
information, social security numbers, etc.
There are a number of university policies that govern handling
information of these types. Special training is required for
researchers and others handling PHI.
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WHY –WHAT – WHO – WHEN & HOW
Sensitive data:

35. Release of sensitive data can damage:
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Managing Research Data
WHY –WHAT – WHO – WHEN & HOW
- Individuals whose data were released: identity theft, financial
loss, privacy violations, etc.
- Research team members: loss of reputation, loss of position
- Research institution: financial liability
UNIVERSITY RESOURCES:
- Office of HIPAA Compliance website
- HIPAA training
- IRB website and training
- Data Classification Policy
- Policy on Electronic Data Security Breach Reporting and
Response
- Other IT Security Policies

36. Take-aways:
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Managing Research Data
WHY –WHAT – WHO – WHEN & HOW
• Definitions of data are varied – Use the one(s) appropriate to
your research community
• Some data are sensitive
– Know which data they are
– Know and take the proper precautions to protect these data

37. Who is responsible for
Research Data Management?
WHY –WHAT – WHO – WHEN & HOW
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Managing Research Data

38. WHY –WHAT – WHO – WHEN & HOW
Who is responsible for research data?
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Managing Research Data
The PI is ultimately responsible for the data, and is the steward
of the data (more on this later).
It is incumbent upon every member of the research team to
safeguard research products (more on this later, too).

39. PI responsibilities:
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Managing Research Data
WHY –WHAT – WHO – WHEN & HOW
“The full administrative, fiscal and scientific responsibility for
the management of a sponsored project resides with the
principal investigator named in the award”
Faculty Handbook 2008
As with all aspects of a proposal submission, the PI must be
involved with establishing and describing an appropriate data
management plan, as required.

40. PI responsibilities:
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Managing Research Data
WHY –WHAT – WHO – WHEN & HOW
The PI is responsible for the collection, management,
maintenance and retention of research data accumulated during
a research project. It is the PI’s responsibility to:
• Determine what records need to be retained to comply with
sponsor requirements
• Adopt an orderly system of data organization
• Communicate the chosen system to all members of a research
group & to the appropriate administrative personnel
• Establish & maintain procedures for protection of essential
records in the event of a natural disaster or other emergency
Sponsored Projects Handbook

41. Research team member
responsibilities:
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Managing Research Data
WHY –WHAT – WHO – WHEN & HOW
Everyone involved in the research project is responsible for
adhering to the statements and requirements presented in the
data management plan, and all other data management
practices related to the research project.
These may include practices of handling:
• Physical data e.g., lab notebooks, samples, data
documentation (aka metadata), etc.
• Electronic data e.g., file naming conventions, generating
metadata, keeping an e-lab notebook, data storage, data back-
ups, annotating findings

42. Take-aways:
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Managing Research Data
WHY –WHAT – WHO – WHEN & HOW
• PI is responsible for all aspects of the grant, including data
management
• All members of the research team are responsible for
adhering to the data management plan
Research data management can be complex, but there are
resources available
See Part 2 of this course for details on WHEN & HOW to
practice Research Data Management
à SEE NEXT PAGE!

43. Resources for Research Data Management:
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Managing Research Data
WHY –WHAT – WHO – WHEN & HOW
Title
URL
Scholarly Communications Program,
Data Management
http://scholcomm.columbia.edu/data-management/
Research and Data Integrity Program
(ReaDI)
http://www.columbia.edu/cu/compliance/docs/ReaDI_Program/
index.html
Data Management Plan Templates
http://scholcomm.columbia.edu/data-management/data-
management-plan-templates/
CUIT Research Computing Services http://rcs.columbia.edu
Academic Commons Archival Storage http://academiccommons.columbia.edu/about
Citation Management http://library.columbia.edu/research/citation-management.html
Managing Secure Information -
Training
http://columbia.sighttraining.com
Data Security Policies http://policylibrary.columbia.edu/category/computingtechnology
This work is licensed under a Creative Commons
Attribution 4.0 International License.

44. REFERENCES
• Sco$,
Mark,
Boardman,
Richard
P.,
Reed,
Philippa
A.S.
and
Cox,
Simon
J.
(2012)
Introducing
research
data.
Southampton,
GB,
Univeristy
of
Southampton,
29pp.
h$p://eprints.soton.ac.uk/338816/
• Responsible
research
data
management
and
the
prevenQon
of
scienQfic
misconduct
www.knaw.nl/Content/Internet_KNAW/publicaQes/pdf/2013449.pdf
• h$p://dmconsult.library.virginia.edu/
4444/
Managing Research Data
Created
by:
Amy
Nurnberger,
2015-­‐05-­‐12
This work is licensed under a Creative Commons
Attribution 4.0 International License.