data sharing five ways that your library can support...
TRANSCRIPT
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 ([email protected])
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, [email protected]