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Love Your Data (LYD)Locally
14 February 2017Medical Library, IB-226
Hello!Heather Coates (MS, MLS)Digital Scholarship & Data Management Librarian
Erin Foster (MSLS)Data Services Librarian
Love Your Data weekFebruary 13-17, 2017
loveyourdata.wordpress.com
#LYD17 #loveyourdata
#WhyILYD17
‘Data quality’ is this year’s theme
1.Why are we here?
Snacks?
2.What can the library do for you?
We’re here to help!
Individual consults
Workshops & classes
Training & education• Data management & sharing plans
• Data sharing & reuse
• Open science/research tools
Library data services
What do you want to know?
Take a look at the Topic Menu!
“Why does good data management
matter?
Some realities…
Reproducibility in science
“The publisher says I have to make my
data available before the article can go to press. How do I do that?
Data sharing -– who’s asking? (1)
Data sharing -- who’s asking? (2)
Vasilevsky NA, Minnier J, Haendel MA, Champieux RE. (2016) Reproducible and reusable research: Are journal data sharing policies meeting the mark? PeerJ Preprints 4:e2588v1 https://doi.org/10.7287/peerj.preprints.2588v1
Review of 318 biomedical journals’ author instructions & editorial policies around data sharing
Data sharing –- share where?
Publisher sites
Subject repositories• NCBI databases (e.g., GenBank, dbGaP)• ICPSR• Roper Center• Odum Institute• DataDryad
Institutional repositories• IUPUI DataWorks
Data sharing -- considerations
Mechanism Sharing Long-term access Metrics
Publisher sites ? ?Subject repositories
?
DataWorks Scholarly Data Archive (SDA)
X X
Data sharing -- support @ IUPUI
IUPUI DataWorks - a repository for sharing and preserving digital research data
Scholarly Data Archive (SDA) - a distributed, tape system for storing and accessing research data
Library help?• Gathering, documenting data for deposit• Guidance around deposit process into DataWorks or SDA
“What is a data management plan
(DMP)? Why would I need one?
The purpose of data management planning is to ensure that research data produced by a project are high quality, well organized, thoroughly documented, preserved, and accessible so that the validity of the data can be determined at any time.
DMPs -- the basics
Describe what you will do with your data during and after the proposed project.
Ensure data is safe now and in the future.
A DMP should reflect:• awareness of data management and curation in your
discipline.• a feasible plan to utilize available cyberinfrastructure.
(try to…)• explain the rationale for your choices.• identify roles for data management and sharing
activities.
DMPs -- the pieces
Common elements include:
• Types of data
• Standards and metadata
• Access and sharing
• Re-use, re-distribution, and the production of
derivatives
• Long-term preservation
• Budget*
“How do I avoid losing data? What systems are available to store and
backup research data?
Storage & backup -- the 3-2-1 rule
Storage & backup -- create master files
Identify transformative steps in your data workflowa) Raw data b) Recoded or derived datac) Screened, cleaned, or processed datad) Subsets for manuscripts
Save a copy and archive it before each key transformation
Document each master file with a README file…plus any other study and data documentation that might be helpful
Storage & backup -- IUPUI systems
Active storage: files that continue to be modified, worked on• Box @ IU [entrusted & health data accounts
available]: a cloud based, file sharing and storage option
Archival storage: final versions, long-term storage• Scholarly Data Archive (SDA): a distributed, tape
system for storing and accessing research data
“Help! I need help creating and
organizing good documentation for my project.
Documentation is a love letter to
your data
Documenting, describing, defining
Capture crucial details needed for post publication peer review and validation of results, such as:
• Research questions/aims• IRB protocol• Informed
consents/authorizations• Funding sources• Study personnel
• Protocol deviations • Data collection
instruments or tools• Data sources• Data collection process or
workflow
README files
What is it?A file that includes information about other files in a directory.
Generally is:• Simple• Short• Descriptive• Instructive
Key features:AuthorsCitationData description• Collection dates• GeoSpatial• Directory & file name
conventions• Changelog File information Access & sharing
“Where can I learn about software and
tools available at IUPUI?
IUPUI tools & resources
DMPTool
Box*
REDCap*
Research DataComplex (RDC)
Git/GitHub
R & RStudio
IUanyWare
Computing*■ Karst■ Big Red II
Storage*■ Scholarly Data
Archive (SDA)
IUPUI DataWorks
*Office hours and/or trainings available
3.Upcoming events
Coming to an IUPUI location near you!
Data BootcampA set of trainings on commonly used software/tools (e.g., RStudio, GitHub, OpenRefine), data encryption methods, and open research practices.
Spring 2017
Data visualization seriesA series of workshops focused on visualizing data in basic, clinical, and applied science.
Summer 2017
Human subjects data workshopA workshop on the handling of human subjects data – from systems (what does HIPAA aligned mean?!) to data de-identification methods/techniques.
Fall 2017
What would you like to see?
Credits
Special thanks to all the people who made and released these awesome resources for free:■ Presentation template by SlidesCarnival■ Icons by Noun Project:
Created by Pravin Unagar (slide 11/top), Gerald Wildmoser (slide 11/middle), Marina Pla (slide 11/bottom), and Christine Hanna (slide 38)
■ Image courtesy of xkcd (slide 37)
Extra thanks:■ Love Your Data 2017 planning committee■ Jennifer Herron and RLML 3D print team