Dat a Sharing

Five ways that YOUR Library can support researchers when sharing their data

Library Connect Webinar:

How to assist researchers in sharing their research data

Lisa Johnston University of Minnesota - Twin Cities

October 22, 2015

5 ways that your Library might help researchers share their data:

1. Keep doing what you do….be an information resource 2. Educate on data management skills/best practices 3. Develop policy + institutional guidelines for data 4. Create a data sharing service: Lots of options! 5. Curate and archive institutional data for reuse

1. Keep doing what you do….be an information resource

Library websit e pul ls campus resources t oget her

http://lib.umn.edu/datamanagement

Bring dat a service providers t oget her in an inf ormal way

Past RDM Discussion Topics:

● Data Storage Opt ions on Campus

● Metadata Standards ● Spat ial Data ● Best Pract ices for De-

ident ifying Research Data ● Data Repositories (Local,

Nat ional) ● Data Services at the

Supercomput ing inst itute ● Pract ical Examples for

Managing data (Sciences)

https://sites.google.com/a/umn.edu/rdm-cop/home

Keep up-t o-dat e inf ormat ion f or administ rat ion

http://lib.umn.edu/datamanagement/funding

2. Educate on data management skills/best practices

Image: http://www.spellboundblog.com/wp-content/uploads/2008/09/floppy_photo.jpg

Of f er workshop on “How t o writ e a Dat a Management Plan (DMP)”

● For researchers ● Discussion Based ● RCR CE Credit ● Departments

request custom sessions

● Co-teach with Liaison

“Training Researchers on Data Management : A Scalable, Cross-Disciplinary Approach," (2012) Available in the Journal of eScience Librarianship (Vol. 1: Iss. 2)

https://www.lib.umn.edu/datamanagement/workshops

Provide DMP Templat es and of f er in-person consult at ions

● One-on-One consults

● DMP Template

● Boilerplate text

● DMPOnline Tool (CDL)

● Examples

https://www.lib.umn.edu/datamanagement/DMP

Graduat e programs do not always include dat a inf ormat ion l it eracy (DIL) skil ls/ compet encies.

http://datainfolit.org

U of MN Dat a Management Onl ine Course

● Hybrid online and in person workshops

● St ructured around DMP

● Hands on act ivit ies

● Direct applicat ion to their data

http://z.umn.edu/datamgmt15

Johnston & Jeffryes (2014). “Steal This Idea.” ACRL News Oct 2014. Slides, handouts, act ivit ies for 5-session Data Management Course

ht tp:/ /z.umn.edu/teachdatamgmt

Scaf f old DIL skil ls f or undergrads using Personal Inf ormat ion management t ools/ st ories

https://www.lib.umn.edu/pim/archiving

3. Develop policy + institutional guidelines for data

Image: http://www.businesscomputingworld.co.uk/wp-content/uploads/2012/01/Computer-Connections.jpg

Institution-wide data policies define roles and responsibilities for long-term data management issues

Also read: Erway, R. (2013). Starting the Conversation: University-wide Research Data Management Policy. EDUCAUSE Review Online.

Policy: http://policy.umn.edu/research/researchdata

Ensures accessibility and preservation of research data through curation, metadata, repositories, and other access and retrieval mechanisms to meet

federal, state, sponsor, and University requirements.

Trains and supports researchers in the creation and implementation of data management plans.

Research Data Management Responsibilities University of Minnesota Libraries

4. Create a data sharing service: Lots of options!

Image Http://cdn.slashgear.com/wp-content/uploads/2012/10/google-datacenter-tech-13.jpg

Typical Dat a Sharing

Dat a Sharing Techniques

Ways to Share your Data Pros? Cons? Post online to a personal or project website

Publish data in a journal as a “supplement ” to your main research art icle.

Make your data “Available on request ” via email or dropbox to those who ask.

Deposit in a disciplinary repository (e.g. Dryad, FlyBase, etc.)

Deposit in a general/commercial repository (e.g. FigShare, Mendeley, etc.)

Deposit in an inst itut ional repository, such as the Data Repository for the University of Minnesota (DRUM)

Lisa Johnston, University of Minnesota Libraries (ljohnsto@umn.edu)

DRUM ht t p:/ / z.umn.edu/ drum Available to U of M researchers and provides: ○ Open access ○ Curation services ○ Permanent

identifiers (DOI) ○ Flexible Licenses ○ File download

analytics ○ Preservation

Data Repository of the University of Minnesota (DRUM)

● Utilize existing repository technologies for cost savings/efficiencies (DSpace, open source software)

Custom upload form and metadata schema for research data

Apply Creative Commons licenses

Curation workflow allows for review of data before openly available

5. Curate inst itut ional research data for sharing and long-term preservation/reuse

Image: http://www.fujitsu.com/img/INTSTG/products/bpm/business-process-management-582x240.jpg

What is data curation?

Data curation steps may include appraisal, ingest, arrangement and description, metadata creation, format transformation, dissemination and

access, archiving, and preservation of digital research data.

Twin Cities Housing GIS Data, UMN

What was the process to curate the data?

Stage 0: Stage 1: Stage 2: Stage 3: Stage 4: Stage 5: Stage N:

Receive Data

Appraise / Inventory

Organize Treatment Actions /

Processing

Description/ Metadata

Access Reuse Data

Workflow Stages drafted by the “Digital Curation Sandbox” participants borrowed from DCC Curation Lifecycle.

http://hdl.handle.net/11299/162338

What happens af t er submission t o DRUM?

After submission, U of Minn researcher receives a conf irmat ion email

Within two business days, we will review their data and contact them about proposed modif icat ions to the submission

Missing f iles

Changes/addit ions to data documentat ion

Reshaping directory st ructure

Convert ing proprietary sof tware to more

archival-f riendly formats

Document Ext ensive Inf ormat ion f or Sharing

Methodological Informat ion

Data collect ion

Processing

Analysis steps

Data-Specif ic Informat ion

File abbreviat ions

Name glossary

http://z.umn.edu/readme

Data Sharing = Services in Support of Research Data Lifecycle

Grant Prep

Storage

Data Collection

Analysis

Preservation

Project Begins

Published Results

Project Close

Sharing

Data Management Plan (DMP) Consultation

Metadata Consultation

Data Management Best Practices/Training

Data Management

Data Curation & Repository Services

Thanks and questions!

Visit our website http://lib.umn.edu/datamanagement

Lisa Johnston, DMCI Lead University Libraries, ljohnsto@umn.edu