The document discusses the UNLV Libraries' efforts to create linked open data (LOD) from their digital collections, focusing on the challenges and advantages of interlinking metadata to reveal hidden relationships within and across collections. A pilot project demonstrated the feasibility of converting existing data into LOD, enhancing discoverability and usability through improved metadata management and visualization tools. Future steps include publishing data, interlinking with other datasets, and training staff in new workflows to sustain the linked data implementation.

1. EXPOSING HIDDEN RELATIONSHIPS:
PRACTICAL WORK IN LINKED DATA
USING DIGITAL COLLECTIONS
Cory Lampert and Silvia Southwick
UNLV University Libraries Digital Collections
April 23, 2015
Linked Data & RDF: New Frontiers in Metadata and
Access Conference

2. OVERVIEW
 Video Demo
 UNLV Linked Data Project
 Digital Collections Metadata: Source of Rich (But
Hidden) Relationships
 Video Demo
 Next Steps, Future
 Questions

3. VIDEO DEMO
This short video (no sound, just image) will give a preview of
what linked data may look like to users.
It shows the Virtuoso Pivot Viewer software acting upon
UNLV’s Linked Open Data – triplestore.
Think about how this is similar/different to how users
currently view data in library systems.
[PLAY PIVOTVIEWER.mp4]

4. EXPLORING LOD: TAKING THEORY
TO PRACTICE
• How we started
• Goals set
• What we accomplished

5. HOWWEBEGAN
Conferences and
“buzz”
Curiousity and
professional
development
Exploration and pilot
project
Compelling results;
sharing impact of
what we’ve learned
Assessment
Much more to do... A
sense of humor is
helpful!
Photo: Five men with
burros, circa 1900,
Tonopah/Goldfield
Collection

6. MOTIVATION
 Information encapsulated in
records
 Records contained in collections
 Very few links are created within
and/or across collections
 Links have to be manually
created
 Existing links do not specify the
nature of the relationships
among records
This structure hides potential
context (links) within and across
collections
 Free metadata from silos
 Expose rich relationships
 Leverage powerful, seamless,
interlinking of data from multiple
sources
 Discover and query data in new
ways
 More precise searching
 More opportunities to repurpose
data
Current Practice LOD Potential

7. POLL
Please use the agree/disagree button, available from
the pull down menu at the top of the screen to
respond to the statement below:
Statement: There is interest in doing practical work
with linked open data at my institution.

8. FOUNDATION OF PILOT
 Our digital collections consist of unique materials
documenting the history of Southern Nevada stored
in CONTENTdm; project focused on LOD for visual
material collections
 Definition of LOD we are using: “Linked Data refers
to a set of best practices for publishing and
interlinking data on the Web.”
 A good way to better understand this is the 5-Star
Data diagram: http://5stardata.info/

9. PREPARINGFORDEPARTURE
Before we launch into a
discussion of how we
created our linked data,
let’s take a short trip.
We will start in our
current data: digital
collections metadata
records, and end in the
new world of linked
open data.
Photo: Photograph of
Howard Hughes in cockpit
of the second XF-11, April
4, 1947, Howard Hughes
Collection

10. Graphical Representation: Part of a
Record

11. EXAMPLES OF RECORDS

12. December
12, 1915
EXPOSING HIDDEN LINKS

13. POLL
Please use the agree/disagree button, available from
the pull down menu at the top of the screen to
respond to the statement below:
Statement: The diagrams helped me to see how
linked data helps to reveal hidden relationships in
existing metadata.

14. UNLV LINKED OPEN DATA PROJECT GOALS
Study the feasibility of developing a common
process that would allow the conversion of our
collection records into linked data preserving their
original expressivity and richness
Publish data from our collections in the Linked Open
Data Cloud to improve discoverability and
connections across our collections and with data from
other related data sets on the Web

15. ACTIONS TECHNOLOGIES
Clean data
Export data
CONTENTd
m
Open
Refine
Import data
Prepare data
Reconcile
Generate
triples
Export RDF
Import data
Publish
Mulgara /
Virtuoso
Phase 1
Phase 2
Phase 3

16. WHATWELEARNED
With interest and
motivation, Linked
Open Data is a
feasible goal
Visualization tools
help convey the
benefits of LOD work
A pilot quickly turned
into a project and
then into production
Moving into the next
phase required
careful examination
of current practice
focusing on
expressing links
(relationships)
Photo: Film
transparency of a
chimpanzee with slot
machines at the Sands
Hotel, Las Vegas, circa
late 1950s, Sands
Collection

17. LOD APPROACH AFTER THE PILOT
 After learning the concepts, applying a model, and
testing technologies, the LOD transformation
process becomes repeatable
 Sustainability of process depends upon data quality
 Data begins with existing metadata in current
collections; there are many lessons from the pilot
that should inform revisions to current practice
(even if LOD is more in future than present)

18. MINING THE METADATA
Application profile
Shared Vocabularies
Managing Controlled Vocabularies
Managing Linked Data

19. When should we start preparing metadata for Linked Data?
EVOLUTION OF METADATA

20. OUR FOCUS IS ON METADATA
 Why?
 Metadata is essential for establishing relationships
 Any metadata?
 Ability of discovering relationships is directly affected by
metadata quality
 It is critical to:
 Use well-established Controlled Vocabularies
(particularly if they are linked data ready)
 Rigorously control local terms
 Re-use URIs
 Assign URIs for local terms

21. METADATA CREATION –
COMMON APPROACHES
 Focus is on the collection being created
 Usually metadata consistency is managed within collections
 Not much rigor is used to enter controlled vocabulary
terms
 Exs.: Misspellings, use of terms that do not match the
preferred terms, etc.
 Limited control of local terms
 Implications:
 Ability to identify relationships within and across collections is
decreased

22. When should we start preparing metadata for Linked Data?
WHAT CAN WE DO TO CREATE “SAPIENT”
METADATA?
Application
Profile
Re-design
strategies to
manage and
use CVs

23. WHAT DO I DO WITH MY LEGACY METADATA?
Adjust
metadata
according
to the
Application
Profile
Apply
strategies
to
manage
and use
CVs
effectively

24. METADATA MILESTONES AT UNLV LIBRARIES
Adopted an approach that considers each individual
digital collection as part of an integrated digital library.

25. THE UNLV APPLICATION PROFILE
 Specifies:
 which metadata terms UNLV Libraries uses for its digital
collections
 the source of metadata terms
 how metadata should be expressed
 labels to be used for each metadata field
 Benefits:
 Increases consistency of content across digital collections
 Improves user interactions with digital collections
 Indexing guidelines are easy to generate
 Facilitates transformation to Linked Data
 Increases compliance with regional and national aggregators

26. OUTCOMES
 Well-established CVs  allow re-use of URIs
 Rigorous rules of data entry  facilitate
reconciliation
 Local Controlled vocabularies  allow interlinking
among local terms / names within collections
 Shared vocabularies  allow interlinkage among
local terms / names across collections

27. All these actions:
allow creation of a single process to transform
digital collections into linked data
Video: [PLAY SUPER-SKELETON-WHH.mp4]

28. MOVING FROM EXPERIMENTATION TO
IMPLEMENTATION
 Cleaning and sharing controlled vocabularies from
legacy collections (time consuming)
 Re-training metadata creators
 Re-designing workflows
 Delegating additional data management
responsibilities

29. DATA MANAGEMENT
 Maintenance of local URIs
 Terms
 Authoritative Names
 Design and implementation of new processes to
maintain synchronization between digital library and
linked data set
 Design processes to enrich relationships with
external data sets

30. NEXT STEPS
Future Activities
Resources
Video Demo

31. FUTURE ACTIVITIES
 Publish data
 Interlinking with other data sets
 Documentation
 Collaborative activities (regional controlled
vocabularies)
 Training and staff skill development
 Interface design and development
 Work with hierarchical data

32. VIDEO DEMO
This short video (no sound, just image) will give a preview of
what linked data may look like to users.
It shows the Relfinder software acting upon UNLV’s Linked
Open Data – triplestore.
Think about how this is similar/different to how users
currently view data in library systems.
[PLAY SHOWING RELATIONSHIPS.mp4]

33. THE LINKED DATA CLOUD

34. RESOURCES
Leading to Linking: Introducing Linked Data to Academic Library
Digital Collections:
http://www.tandfonline.com/doi/pdf/10.1080/19386389.2013.826
095
A Guide for Transforming Digital Collections Metadata into
Linked Data Using Open Source Technologies:
http://www.tandfonline.com/doi/pdf/10.1080/19386389.2015.100
7009
UNLV Linked Data Blog (videos posted here):
https://www.library.unlv.edu/linked-data
Contact us!

35. THANKYOU!
Contact Us:
Cory Lampert
cory.lampert@unlv.edu
Silvia Southwick
silvia.southwick@unlv.edu
UNLV Digital
Collections
www.d.library.unlv.edu
Questions?
Photo: Photograph of
Bluebells posing
outside of Pan Am jet,
1958, Donn Arden
Collection

36. QUESTIONS?
Contact:
Cory Lampert
cory.lampert@unlv.edu
Silvia Southwick
silvia.southwick@unlv.edu
UNLV Digital Collections
www.d.library.unlv.edu