This presentation was provided by Kenning Arlitsch of Montana State University during a NISO Webinar entitled "Supporting Research on Your Campus", held on May 4, 2016

1. DISC –
Data Infrastructure and
Scholarly Communication
K EN N I N G A R L I T S C H , D EA N O F T H E L I B R A R Y
M O N T A N A S T A T E U N I V ER S I T Y
W W W . M O N T A N A . ED U / D I S C
M A Y 4 , 2 0 1 6

2. Environment
Growing research university with very productive faculty (grants, publications)
◦ Disparity of access to infrastructure and services
◦ MSU research is not as visible as it should be
Funding agencies requiring more data management
◦ Growing assumption that libraries will just take care of this
Research Data Census
◦ http://scholarworks.montana.edu/xmlui/handle/1/9314
Montana “bootstrap” mentality

3. Data Infrastructure and Scholarly Communication
Joint initiative of MSU Library and MSU Information Technology Center
Launched September 2015
Overall goal is to help MSU researchers become more competitive
Provide computing infrastructure and services
Existing personnel from Library and ITC
Administrative director on two-year half-time reassignment
Vision
◦ Advancing research and amplifying impact
Mission
◦ We provide MSU researchers with computational, data, and digital resources and expertise that increase
discovery, build knowledge, and communicate scholarly work.

4. Infrastructure Examples
Hyalite Cluster
◦ High performance computing cluster open to the entire MSU community with approximately 10
teraflops of computational capacity and 600 terabytes of data storage.
Bridger Network
◦ High performance “research only” physical network funded by the NSF to allow big data to move more
efficiently across the Bozeman campus and with national and international collaborators.
Cyber-CANOE – Collaborative Analysis Navigation and Observation Environment
◦ Funded and will be implemented later this year
ScholarWorks – scholarworks.montana.edu
◦ Open Access institutional repository running DSpace
◦ Data repository under development with CKAN software
Open Journal Systems – currently hosting two publications

5. Services Examples
Author Fund
Data security/confidentiality consultation
Data science/bioinformatics consultation
DOI minting/ARKs
Search Engine Optimization
Social Media Optimization
Researcher ID services
MSU Publications
SESMO for subscription databases
Semantic Web Identity optimization

6. #1 - Researcher ID Services
Suite of tools and services that disambiguate researchers and help surface their work
DISC is helping researchers decide with which services to engage
Plan to provide seeding/maintaining services
1. Author/Researcher Identification
2. Academic and Professional Networking
3. Reference and Citation Management
Shanks, Justin and Kenning Arlitsch. “Making Sense of Researcher Services,”
Journal of Library Administration, v56no3, March 25, 2016.
http://www.tandfonline.com/doi/full/10.1080/01930826.2016.1146534

7. Researcher Services -
Author/Researcher Identification

8. Researcher Services – Academic Profiling

9. Researcher Services –
Reference & Citation Management

10. #2- Researcher
Publications
Service
Harvesting service published monthly
to reveal faculty research publications
http://www.montana.edu/research/pu
blications/
Leila Sterman
Scholarly Communication Librarian

11. #3 - SESMO:
Search Engine and Social Media Optimization
Applying SEO, linked data, and social media optimization to subscribed databases
Meets scholars where they begin their research (in commercial search engines)
Increases likelihood they will discover, access and share MSU’s subscribed resources
Substantial increased traffic to paid resources
Jason Clark, Head of Library Informatics and Computing
Doralyn Rossmann, Head of Collection Development and DISC Administrative Director
◦ https://www.cni.org/topics/information-access-retrieval/open-sesmo-innovations-in-surfacing-paid-
content-to-todays-learners

12. #4 - Semantic Web Identity Services
2015-10-29 MONTANA STATE UNIVERSITY 12
Academic organizations are poorly represented on the Semantic Web…
…because search engines don’t understand them as entities…
…because librarians have not built and maintained the data sources
that search engines trust.

13. Google’s Perception of MSU Lib - 2012
2015-10-29 MONTANA STATE UNIVERSITY 13

16. Semantic Web Identity Enhancement
Only about 60% of ARL libraries have accurate Knowledge Cards and most are not very robust
Presently working with all MSU colleges to improve their SWI
Will then work down toward departments, centers, institutes
Goal is for search engines to have a better semantic understanding of the business of those
academic organizations.
Justin Shanks, Semantic Web Identity Researcher