rdap 15: virginia tech university libraries’ data service pilot with the college of natural...
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Virginia Tech University Libraries’ Data
Service Pilot with the College of Natural
Resources and Environment (CNRE)
Natsuko Nicholls, Andi Ogier and Kyrille Goldbeck DeBose
Research Data Access & Preservation (RDAP) Summit
Minneapolis, MN
April 22, 2015
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Our Mission:
To deliver a suite of research data
services to the Virginia Tech Community.
Our Vision:Build Infrastructure
Advocate for Data Management
Support Collaboration
Value Partnerships
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Project Highlights
Data Profiling
Data Needs Assessment
Data Interviews
5 areas of interest
5 questions
15 faculty recruited
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Q1: Data Profiles
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ASCII is recommended,
but it triples or
quadruples the storage
size
Companies are taking
open formats and
creating their own
proprietary standards.
Data Profiles: Summary
● Diversity of data
○ types
○ formats
○ environments
● Data States
● Raw vs.
Summarized
● Media Issues
Common Elements: Points of Interest:
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Q2. Data Workflows
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Fragmented workflows are
VERY problematic.
Data Management costs
30% of project time.
Need: High-quality
workflows that allow for
creativity and spontaneity.
Data Workflows: Summary
● Lifecycles are
Complicated
● Data Management
is time consuming
● Establishing and
documenting a
workflow is time
consuming
Common Elements: Points of Interest:
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Q3. Data Challenges
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Need: Systems that allow
algorithms and processes
to be brought to the data.
Original data isn’t always
available.
Data Challenges: Summary
● Data challenges:
○ format
○ storage
○ versioning
○ ownership
○ copyright
○ privacy
● Workflows and
tracking data
Common Elements: Points of Interest:
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Q4: Data Value-Add
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Harmonization of data
users and producers.
Concern: easy to mis-
interpret some data;
analysis is dependent on
specialized knowledge.
Data Value-Add: Summary
● Value-add
○ beyond research
community
○ historical data
○ public interest
● Market impacts
● Cost of data
collection is
measurable
Common Elements: Points of Interest:
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Q5: Data Management Planning
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DMPs seem rigid and
limited.
Standardization hinders
innovation; different
people measure different
things.
Preserve data and prevent
loss by summarization.
Data Management: Summary
● Standards vs.
specifics
● Use DMP as a tool
to find data
● Metadata is vitally
important
Common Elements: Points of Interest:
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Final Thoughts
Interview process promotes partnerships,
starts conversations.
Research Management tools are needed at a
project level, not institutional/department
level. Provide information and let project
teams make the choice.
Need additional training as to why DMPs are
important to research. Many faculty still see
them as a hindrance.
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Questions?
Natsuko Nicholls
Research Data Consultant
Andi Ogier
Assistant Director
Data Curation
[email protected] Kyrille Goldbeck DeBose
College Librarian for Natural
Resources & Environment
and Animal Sciences