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Vision for Open Research Data
Oya Y. Rieger
Cornell University Library
rieger@cornell.edu
June 2012, Copenhagen
Research involves the systematic collection and analyses of information to
increase our understanding of the phenomenon under study

source: flicker.com
Scholarly communication involves the creation, exchange,
and dissemination of knowledge within the context of
academic discourse.

Analysis
Interpretation

?

Authoring
Presenting

Research
Data Collection

KNOWLEDGE
CREATION

Sharing
Networking

Archiving
Preservation
Publishing
Dissemination
Access to Research Data
•
•
•
•
•
•
•
•

support open scientific inquiry
encourage diversity of hypotheses & data analysis
encourage interdisciplinary research
provide greater returns for public investment in
research
facilitate the education of new researchers
foster downstream commercialization of outputs
support studies on data collection & analysis methods
engage public in science

Arzberger et al., “Promoting Access to Public Research Data for Scientific,
Economic, and Social Development.” Data Science Journal, 3/29, 2004
http://data.research.cornell.edu
http://data.research.cornell.edu
Steinhart et al., Journal of eScience Librarianship, 2012; 1(2)
txt
doc
xls
jpeg

Steinhart et al., Journal of eScience Librarianship, 2012; 1(2)
What might prevent you from sharing the data you have produced or
intend to produce for this project?
Steinhart et al., Journal of eScience Librarianship, 2012; 1(2)
The Loon Project (Funded by NSF)
flickr.com
http://www1.chapman.edu/~wpiper/index.html
http://ecommons.library.cornell.edu/handle/1813/13098
http://ecommons.library.cornell.edu/handle/1813/13098
Carrol

http://ecommons.library.cornell.edu/handle/1813/17040
http://www.cornell.edu/video/index.cfm?VideoID=1166
Loon Project
technical

informational

usability
organizational

sociocultural
technical infrastructure
• scalable and flexible systems to store,
discover, access, and archive content
• interoperability standards to link related
information objects and various types of
repositories
• metadata standards to facilitate discovery,
access, archiving, and repurposing
sociocultural issues
• community-based standards for deposit, use,
and maintenance of data
• different access provisions in support of
academic, and entrepreneurial requirements
• incentives and rewards for scientists to share
the outputs of their research endeavors
information policies
• information policies to support:
– IPR
– privacy
– confidentiality
– institutional ownership
– security
– access limitations
– retention and deaccessioning
organizational infrastructure
•
•
•
•
•

business and sustainability plans
governance models
recognition and engagement of stakeholders
collaboration strategies
communication and marketing strategies
usability
• data quality standards
• ease of deposit to encourage end-users
• tools to support analytics, mining, integration,
and visualization
• digital identifiers to persistently locate
• citation standards to reference resources
• metrics to track and communicate impact
technical

informational

usability
organizational

sociocultural

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The research data landscape: an overview - Oya Rieger, Cornell University