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RESEARCH! DATA!
MANAGEMENT! SHARING!
+
Brianna Marshall | @notsosternlib !
UW-Madison Libraries | #uwECR!
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about me!
Brianna Marshall!
Digital Curation Coordinator, UW Libraries!
Lead, Research Data Services
– Education + training
– Consultations
– Data management plans (DMPs)
researchdata.wisc.edu
@UWMadRschSvcs
!
!
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caveats!
• Given limited time, I’ve chosen to mention things
- even just briefly! - rather than forego them
entirely
• Hopefully you’ll get ideas for concepts and tools
to explore later
• Expectations and best practices are often field-
specific, so it’s tough to generalize
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hopes + dreams!
you’ll find something I
talk about today useful
+ put it into practice
you’ll share your top
data management
tips with us
you’ll tell me what you
want to know more
about for future
workshops!
you’ll be reenergized
enough by the topic to
find something else
that works for you
and / or
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what is research data?!
“the recorded factual information commonly accepted
in the scientific community as necessary to validate
research findings.”
INCLUDES: code, figures, statistics, interviews,
transcripts
EXCLUDES: preliminary analyses, drafts of papers,
plans for further research, communication + peer
reviews, physical samples
- OMB Circular, White House
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time to ponder!
Can you still access your data from…
– 10 years ago?
– 5 years ago?
– 1 year ago?
Let’s talk about the data you’ve kept and lost.
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time to ponder!
Can you still access your data digital stuff
from…
– 10 years ago?
– 5 years ago?
– 1 year ago?
Let’s talk about the data digital stuff you’ve
kept and lost.
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data horror stories!
Image courtesy of Flickr user wolfgangfoto (CC BY ND)!
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https://i.imgflip.com/ntnjb.jpg
you can’t!
find it.!
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or you can’t!
understand it.!
http://cdn.meme.am/instances/58392702.jpg
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or it’s!
long gone.!
https://community.spiceworks.com/topic/813225-
best-backup-recovery-memes
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federal funding requirements!
Data management plans (DMPs) are required by all federal
funding agencies.
Office of Science and Technology Policy (OSTP) memo
– Released spring 2013; took effect fall 2015
– Requires open sharing of published articles and data
– Publication repository is provided; data repository is not
– Applies to agencies with $100M + in R&D
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dmptool.org!
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what’s up with researchers?!
Ample technology to generate data but few skills to
manage it effectively
Movement toward openness, impacted by OSTP
and spurred by early career researcher expectations
Disciplinary culture shifts toward data reuse +
reproducibility
Need for multi-purpose online spaces to
collaborate, share, store, and archive research
outputs (including data)
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DATA
MANAGEMENT
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data management basics!
File organization
• Is your data organized meaningfully or jumbled together? Do you
know where your data is?
Documentation
• How much contextual information accompanies your data? Can you
understand it? Can a stranger understand it?
Storage & backup
• Where is your data stored and backed up? Could you recover from
hardware failure or accidental deletion?
Media obsolescence
• Do you know how the software, hardware, and file formats you use
will impact your data’s readability in the future?
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file naming conventions!
• Use them any time you have related files
• Consistent
• Short yet descriptive
• Avoid spaces and special characters
example
File001.xls vs. Project_instrument_location_YYYYMMDD.xls
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directory/folder organization!
Lots of possibilities, so consider what makes sense
for your project
– File type
– Date
– Type of analysis
example:
MyDocuments\Research\Sample12.tiff vs.
C:\\NSFGrant01234\WaterQuality\Images\LakeMendota_20141030.tiff
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retroactive organization!
• Do a data inventory. List all the places
where your data lives (both physical and
digital)
• Make a plan for consolidating – follow the
rule of 3, not the rule of 17
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documentation!
Coded SPSS
survey
responses
(Useless without
the original
questionnaires)
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document on many levels!
Project- & folder-level
– Create a readme file. (Good example located here:
http://hdl.handle.net/2022/17155)
– Document any data processing and analyses.
– Don’t forget written notes.
Item-level
– Remember the importance of file names for conveying
descriptive information.
– Find and adhere to disciplinary metadata standards
• XML
• Dublin Core
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what’s in a good readme file?!
• Names + contact information for people associated
with the project!
• List of files, including a description of their
relationship to one another!
• Copyright + licensing information!
• Limitations of the data!
• Funding sources / institutional support!
!
tl;dr !!
Any information necessary for someone with no knowledge of
your research to understand and / or replicate your work.!
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example readme file!
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storage & backup!
storage = working files.
The files you access regularly and change frequently.
In general, losing your storage means losing current
versions of the data.
backup = regular process of copying data separate from
storage.
You don’t really need it until you lose data, but when
you need to restore a file it will be the most important
process you have in place.
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rule of 3
Keep THREE copies of your data
– TWO onsite
– ONE offsite
Example
– One: Network drive
– Two: External hard drive
– Three: Cloud storage
This ensures that your storage and backup is not all
in the same place – that’s too risky!
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Original clipart from http://cliparts.co/clipart/2532461.
Modified version made available as CC0.
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evaluating cloud services!
• Lots of options out there – and not all are
created equal
• Read the Terms of Service!
• While at UW, use your free UW Box or
Google Drive accounts
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h#p://www.doit.wisc.edu/news/collabora6on-‐tools-‐google-‐docs-‐vs-‐box-‐2
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media obsolescence!
CC
image
by
Flickr
user
wlef70
• software
• hardware
• file formats
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thwarting obsolescence!
• You can’t.
• Today’s popular software can become
obsolete through business deals, new
versions, or a gradual decline in user base.
(Consider WordPerfect.)
• Anticipate average lifespan of media to be
3-5 years. Migrate your files every few years,
if not more frequently!
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thwarting obsolescence!
• Some file formats are less susceptible to
obsolescence than others
– Open, non-proprietary formats (pick TXT over
DOCX, CSV over XSLX, TIF over JPG)
– Wide adoption
– History of backward compatibility
– Metadata support in open format (XML)
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back to (data management) basics!
File organization
• Is your data organized meaningfully or jumbled together? Do you
know where your data is?
Documentation
• How much contextual information accompanies your data? Can you
understand it? Can a stranger understand it?
Storage & backup
• Where is your data stored and backed up? Could you recover from
hardware failure or accidental deletion?
Media obsolescence
• Do you know how the software, hardware, and file formats you use
will impact your data’s readability in the future?
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DATA
SHARING
+
PUBLICATION
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get credit for your data!
• Many ways to share/publish your data!
– Institutional + disciplinary repositories
– Data papers/journals
• If your research is federally funded, remember that
you’ll now have to share your data
• Data is not copyrightable; best practice is to apply a
Creative Commons 0 license
• There’s even a proven citation advantage to sharing
your data*
*Piwowar HA, Vision TJ. (2013) Data reuse and the open data citation advantage. PeerJ 1:e175
https://dx.doi.org/10.7717/peerj.175
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minds.wisconsin.edu!
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dryad.org!
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figshare.com!
http://figshare.com/articles/Prevalence_and_use_of_Twitter_among_scholars/104629
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zenodo.org!
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nature.com/sdata/!
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github.com!
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re3data browse functionality!
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Image courtesy of Flickr user davegray (CC BY ND)
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Image courtesy of Flickr user mabi (CC BY SA)
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FINAL
THOUGHTS
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final thoughts!
• Think about how your existing data management
practices will impact your ability to access your
data days/weeks/years from now.
• If organizing retroactively, prioritize your most
important research.
• Managing digital stuff requires a LOT of decision
making, so embrace it!
• Any plan is better than no plan at all. Start today.
Ask for help.
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my suggestion?!
Grant or not, start new projects with a data
management plan compiled by project leaders.
The plan should cover:
• Organization + naming
• Documentation + metadata
• Storage + sharing
• Any and all other pertinent details. (The more the better;
it’ll save you headaches later.)
The plan should be actively revisited and adapted as
needed throughout the project.
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GOOD DATA
MANAGEMENT
+ sharing
!
BETTER, !
FASTER!
research!
=
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researchdata.wisc.edu!
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upcoming digital scholarship workshops!
An Introduction to Open Research DECEMBER 10
AVAILABLE ONLINE
Project Management + Productivity Tools
Crafting Your Digital Identity
Steenbock Library BioCommons | 4-5pm