love your data locally
TRANSCRIPT
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Love Your Data (LYD)Locally
14 February 2017Medical Library, IB-226
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Hello!Heather Coates (MS, MLS)Digital Scholarship & Data Management Librarian
Erin Foster (MSLS)Data Services Librarian
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Love Your Data weekFebruary 13-17, 2017
loveyourdata.wordpress.com
#LYD17 #loveyourdata
#WhyILYD17
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‘Data quality’ is this year’s theme
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1.Why are we here?
Snacks?
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2.What can the library do for you?
We’re here to help!
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Individual consults
Workshops & classes
Training & education• Data management & sharing plans
• Data sharing & reuse
• Open science/research tools
Library data services
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What do you want to know?
Take a look at the Topic Menu!
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“Why does good data management
matter?
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Some realities…
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Reproducibility in science
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“The publisher says I have to make my
data available before the article can go to press. How do I do that?
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Data sharing -– who’s asking? (1)
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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
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Data sharing –- share where?
Publisher sites
Subject repositories• NCBI databases (e.g., GenBank, dbGaP)• ICPSR• Roper Center• Odum Institute• DataDryad
Institutional repositories• IUPUI DataWorks
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Data sharing -- considerations
Mechanism Sharing Long-term access Metrics
Publisher sites ? ?Subject repositories
?
DataWorks Scholarly Data Archive (SDA)
X X
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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
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“What is a data management plan
(DMP)? Why would I need one?
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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.
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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.
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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*
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“How do I avoid losing data? What systems are available to store and
backup research data?
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Storage & backup -- the 3-2-1 rule
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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
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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
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“Help! I need help creating and
organizing good documentation for my project.
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Documentation is a love letter to
your data
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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
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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
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“Where can I learn about software and
tools available at IUPUI?
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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
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3.Upcoming events
Coming to an IUPUI location near you!
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Data BootcampA set of trainings on commonly used software/tools (e.g., RStudio, GitHub, OpenRefine), data encryption methods, and open research practices.
Spring 2017
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Data visualization seriesA series of workshops focused on visualizing data in basic, clinical, and applied science.
Summer 2017
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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
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What would you like to see?
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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