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

Thanks!Any questions?

You can find us at:

medlref@iupui.eduulib.iupui.edu/form/info_request