This presentation was provided by Christine Stohn of ExLibris/Proquest during the NISO Virtual Conference held on February 15, 2017, entitled Institutional Repositories: Ensuring Yours is Populated, Useful and Thriving.

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Christine Stohn
Promoting discovery of Institutional
Repository content

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The discovery Landscape – different users, different entry points
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Aggregations
Social Media
Web search
engines
Websites
Library
Discovery
A&I
databases

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Institutional repositories and Discovery - examples
• > 500 Institutional repositories indexed
IR data in library discovery: Primo and summon
• Articles
• Research data
• Digital photographs
• Project reports and data
• Audio-visual material
• Manuscripts
• Thesis and dissertations
• Archival material
• Rare books
• …
Many different material and content types
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Library discovery example: A transcript in summon
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Library discovery example: A research data set in Primo
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Library discovery example: A research data set in Primo
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Open access – links to the free version of an article in the IR
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Open access – links to the free version of an article in the IR

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Institutional Repositories and Discovery - examples
PubMed LinkOut – upload option for adding links to IRs
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https://www.ncbi.nlm.nih.gov/projects/linkout/doc/nonbiblin
kout.html

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Pubmed LinkOut Example
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Pubmed LinkOut Example
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Metadata – a key discovery factor
• Metadata quality and depth
• Reliability and consistency
• Use of identifiers and standard formats for data and harvesting
Important
• No or incomplete and abbreviated titles
• Missing author/creator
• Inconsistent use of field tags
• No clear or inconsistent indication of content type
• No identifiers
• Standard and version not clear (e.g. author manuscript vs. peer
reviewed)
• Access information incorrect, leading to paywalls
Some common problems with IR metadata
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Use of repository data is a matter of trust
• The data can be found on the Internet
• The data are accessible (clear rights and
licences)
• The data are in a usable format
• The data are reliable
• The data are identified in a unique and
persistent way so that they can be referred to
Data Seal of Approval assessment:
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http://www.datasealofapproval.org/en/assessment/

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Discovery beyond searching
• Citation trails
• Topic trails
• Recommender systems
• Supplementary material
• …
Data networks and connections:
Exploration and learning
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Use of common identifiers and good metadata is
essential for exploration

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Exploration: A citation trail
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Exploration: A citation trail

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Exploration: A citation trail

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Exploration: A citation trail

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Linked open data
URIs, RDF, RESTful APIs …
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http://lod-cloud.net/

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Discovery entry points – not end points
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Aggregations
Social Media
Web search
engines
Websites
Library
Discovery
A&I
databases

21. © 2015 Ex Libris | Confidential & Proprietary© 2015 Ex Libris | Confidential & Proprietary
Discovery entry points – not end points
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Aggregations
Social Media
Web search
engines
Websites
Library
Discovery
A&I
databases

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Summary
• Wide distribution of IR data leads to discovery and is
desirable for all stakeholders
• Standards and use of widely accepted formats are
essential (OAI-PMH, NISO ResourceSync, NISO ODI and
ALI, Identifiers (DOI, ORCiD), Dublin Core, BibFrame,
MARC, NISO JATS …)
• Don’t just think searching, think also linking, exploration,
connecting content to the semantic web
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THANK YOU
christine.Stohn@exlibrisgroup.com