The document summarizes a presentation given by Dr. Diane Pennington and Laura Cagnazzo on library linked data implementations and perceptions. The presentation discussed the evolution of the semantic web and linked open data principles. It provided an overview of a study on the status and perceptions of linked data among European national libraries and Scottish libraries. The study found lack of awareness and expertise to be challenges for implementation. Benefits included improved data visibility and opportunities for collaboration. Recommendations focused on training, collaboration, and developing implementation guidelines and case studies.
Library Linked Data Implementations and Perceptions
1. RIVAL Network Event 2 – November 7th 2019 – Edinburgh
Library linked data implementations and perceptions:
implications for practice
Dr Diane Pennington, Strathclyde University & Laura Cagnazzo, UWS
Research, Impact, Value & LIS - #lisrival - Edinburgh – 7th November 2019
2. Library linked data
implementations and perceptions:
Implications for practice
Dr Diane Rasmussen Pennington FHEA FRSA
Senior Lecturer in Information Science, University of Strathclyde
@infogamerist
diane.pennington@strath.ac.uk
Ms Laura Cagnazzo MA MSc
Repository & Research Data Librarian, University of the West of Scotland
@LauraFCagnazzo
laurafcagnazzo@outlook.com
3. The evolution of the Web (1989-now)
• Web 1.0: hand-coded HTML pages; accessible
and readable, but not interactive
• Web 2.0: Facebook and Twitter; everyone can
post, share, and respond without extensive
technical knowledge
• Web 3.0: the Semantic Web
– “Semantic” is “meaning in language”
– “Semantic Web” communicates “the meaning of the content on
web pages in a way that computers can understand. If they can
process these meanings, they can then make and convey
relationships between related web pages. This leads to improved
– and more meaningful – information retrieval.” (p. 34)
Source: Rasmussen Pennington, D. (2016, July/August). Demystifying linked data:
Are you ready for what's next? CILIP Update, 34-36.
4. 4
Linked open data principles
1. Use URIs as names for things
2. Use HTTP URIs so that people can
look up those names
3. When someone looks up a name,
provide useful Resource
Description Framework [RDF]
information, using the standards
(RDF*, SPARQL)
4. Include links to other URIs so that
they can discover more things
Source: http://www.w3.org/DesignIssues/LinkedData.html
5. 1. Use URIs as names for things
2. Use HTTP URIs so that people can
look up names
5
• The Hypertext Transfer Protocol (HTTP) is a
networking protocol for distributed, collaborative,
hypermedia information systems.
• HTTP is the foundation of data communication for
the World Wide Web.
• Use URIs to name people, for institutions,
concepts, topics, and geographical places.
Examples:
• http://www.strath.ac.uk (a university)
• https://www.facebook.com/CILIPinfo (a professional association)
• https://personal.cis.strath.ac.uk/diane.pennington (a lecturer)
• https://www.flickr.com/photos/chandlerinok/6168389622 (a
Chihuahua)
6. 3. When someone looks up a name,
provide useful [RDF] information
6
• Use RDF subject-predicate-object ‘triples’ to describe a thing
• Reciprocate triples to show relationships between things
Emma Watson → StarredInMovie → Harry Potter and the Half-Blood Prince
Emma Watson is the subject, StarredInMovie is the predicate, and Harry Potter
and the Half-Blood Prince is the object.
This relationship also needs to be reciprocated:
Harry Potter and the Half-Blood Prince → Has Movie Star → Emma Watson
RDF, or Resource Description Framework, is
the language of the Semantic Web
predicate objectsubject
7. 7
4. Include links to other URIs so that
users can discover more things
An example using
DBpedia; shows
relationships between
philosophers
Source: http://io9.gizmodo.com/5923583/the-complete-history-of-philosophy-visualized-in-one-graph
9. • Semantic Web = enhanced form of web;
content expressed in machine-readable
format (Berners-Lee, Hendler, Lassila,
2001)
• SW = goal; LD = means to reach it (Bizer
et al., 2009)
• LD as “a means to dismantle data silos”
(Heath, 2009)
• W3C standards
• LD applied to library data: Baker et al.,
2011; Tallerås, 2013; Shiri & Davoodi,
2016; OCLC surveys 2014, 2015, 2018
(Karen Smith-Yoshimura)
Linked data: what we know
10. 10
Linked data use across European
national libraries: methodology
• Literature review
• Semi-structured interviews (n=15;
Skype, email)
• Departmental ethics approval
• Recruitment through Twitter, libraries’
email addresses, electronic mailing lists
• Online resources analysis (n=26;
Semantic Radar)
11. • Short online Qualtrics survey
• Departmental ethics approval
• Recruitment through Twitter, SLIC, CILIPS
• Open from 03/05/17 to 18/05/2017
• n=113 completed responses
Linked data: Opening Scotland’s
library content to the world:
methodology
13. Scottish Government’s Open Data
Strategy (2015)
“This strategy seeks to create a Scotland where non-
personal and non-commercially sensitive data from
public services is recognised as a resource for wider
societal use and as such is made open in an intelligent
manner and available for re-use by others …
The Vision sets out ambitions for a Scotland which, by
2020, recognises the value of data and responsibly
makes use of data to improve public services and deliver
wider societal and economic benefits for all.”
Source: http://www.gov.scot/Publications/2015/02/6614
14. • Open government initiatives spreading world-
wide
• Transparency (fight corruption / improve
accountability)
• Enable citizens’ participation
• Strengthen democracy
• Data generated, gathered and stored by
government agencies (e.g., national, school,
public libraries) using public money (through
taxes) should be available to everyone
Open Government Data
15. • Two individual studies revealed similar
results
• Status of awareness of “linked data” and
“Semantic Web” concepts
• Linked data uses
• Reasons for, challenges/benefits of linked
data implementation
• Recommendation and best practice
Findings
16. Do you know what the term
‘Semantic Web' means?
Definitely yes
Probably yes
Might or might not
Probably not
Do you know what the term
'linked data' means?
Definitely yes
Probably yes
Might or might not
Probably not
Linked data awareness
• European national libraries: lack of
awareness among staff (e.g., IT) hinders
projects design and actuation
• Scottish libraries:
17. European nat. libraries
Linked data implementation
status
Scottish libraries
Have implemented
Have plans to implement
Have no current plans to implement
No response
Have Implemented
Have plans to implement
Not implemented
Taking steps towards
18. Uses of linked data
European nat. libraries
• Provide data to LD data
sets (VIAF, Wikidata,
Europeana)
• Publish bibliographic and
authority data
• National bibliographies
• Digitized resources
• Thesauri and ontologies
Scottish libraries
• MARC catalogue
records
• Digitized resources
• Social media
• Research outputs
using RDF, Dublin
Core, SPARQL
• OWL, SKOS,
Europeana Data
Model
19. • Popularity of linked data on international
scene (perceived/expected benefits)
• Improve data visibility and discoverability
• Enhance existing data sets
• Enriched, open, reusable information,
available for various purposes to the wider
community
• Adhere to standards (W3C)
• Open up data silos
Reasons for implementing linked
data
20. • Lack of awareness
• Lack of expertise / time / staff
• Difficulties in obtaining management buy-
in
• Licencing constraints (permission needed
from database providers to link)
• Potential loss of control of data
• Lack of agreement on standards
• Lack of tools / guidelines
Challenges of implementation
21. • Augment visibility and discoverability of
library data
• Support interoperability
• Overcome linguistic barriers
• Acquire better understanding of linked
data potential
• Enable cataloguing efficiency and
innovation (e.g., workload reduction)
• Obtain authoritative position as data
provider (to which other institution will
refer to)
Benefits of implementation
22. • Is LD the right technology for your scope?
• Design a detailed roadmap before acting
• Consider legal issues
• Training
• Adopt tools to support implementation
• Contact/collaborate with LD implementers
• Seek expert developers, if necessary
• URI syntax maintenance
• Reuse data /existing vocabularies, whenever
possible
• Adopt entity-based approach to data
Best practices
23. • Teach practitioners what linked data can achieve
• Familiarize yourself with LD
• Focus on goals, rather than technical matters
• Involve your institution/community of stakeholders
• Look at examples offered by successful projects
• Focus on data specific to your institution
• Consider needs of wider community (not just library
community)
• Collaborate with local universities/institutions and
benefit from their expertise – Collaboration is key!
Recommendations
24. • Encourage open data movement at government level
• Case studies: Successful implementation examples
• Re-use vs creation of ontologies
• Licensing constraints
• Step-by-step implementation guidelines
• Improve communication between system
providers/technicians and information professionals
• Collaboration towards design and adoption of a
common model, to facilitate data integration
Further research / direction
25. Conclusions
• Still far from the SW as
envisaged by Berners-Lee,
Hendler, and Lassila in
2001 – SW enabling better
“understanding between
humans and machines”
• No agreed-upon standards
= risk of “LD silos”
• Need for spreading
awareness and advocate
for LOD with government /
public bodies
27. Implementation/Review
User testing – evaluation> revision> improvement
Building documentation on progress>Assessing
outcomes
Project definition and planning
Defining scope, timeframe, core team involved,
desired end results
Resource (staff, tools, budget) assessment – gap
analysis
Initial needs assessment / Management buy-in
What is our data?
Evidence of successful implementation cases - How
implementation will benefit UWS
Scenario: publishing researcher data
as linked data at UWS
29. References
• Baker, T., Bermès, E., Coyle, K., Dunsire, G., Isaac, A., Murray, P.,
Panzer, P., Schneider, J., Singer, R., Summers, E., Waiters, W., Young,
J. and Zheng, M. (2011) Library Linked Data Incubator Group final
report, W3C, http://www.w3.org/2005/Incubator/lld/XGR-lld-20111025/
• Berners-Lee, T., Linked Data:
http://www.w3.org/DesignIssues/LinkedData.html
• Berners-Lee, T., Hendler, J. and Lassila, O. (2001) ‘The Semantic Web’.
Scientific American, 284(5), pp.29-37, https://tinyurl.com/hh3h9m6
• Bizer, C., Heath, T. and Berners-Lee, T. (2009) ‘Linked Data: The story
so far’. International Journal on Semantic Web and Information
Systems, 5(3), pp.1-22
• Cagnazzo, L. (2017) Linked Data: Implementation, Use, and
Perceptions across European National Libraries, MSc Dissertation,
http://hdl.handle.net/10760/32004
• Heath, T. (2009) ‘Linked Data? Web of Data? Semantic Web? WTF?’
Tom Heath’s Displacement Activities, 2 March,
http://tomheath.com/blog/2009/03/linked-data-web-of-data-semantic-
web-wtf/
• Hobbs, P. (2009) Project management, London: Penguin Random
House.
• Rasmussen Pennington, D. (2016, July/August). Demystifying linked
data: Are you ready for what's next? CILIP Update, 34-36.
29
30. • Rasmussen Pennington, D. (2017) ‘Linked data: Opening
Scotland’s library content to the world’,
https://www.slideshare.net/CILIPScotland/linked-data-
opening-scotlands-library-content-to-the-world
• Shiri, A. and Davoodi, D. (2016) ‘Managing Linked Open Data
across discovery systems’, in Spiteri, L. (ed.) Managing
metadata in web-scale discovery systems. London: Facet
Publishing, pp.57-90
• Smith-Yoshimura, K. (2015) ‘Linked Data implementations—
Who, what and why?’,
http://www.oclc.org/research/themes/data-
science/linkeddata.html
• Suominen, O. and Hyvönen, N. (2017) ‘From MARC silos to
Linked Data silos?’, O-bib, 4(2), https://www.o-
bib.de/article/view/2017H2S1-13/5883
• The Linking Open Data cloud diagram: http://lod-cloud.net/
• Tallerås, K. (2013) ‘From many records to one graph:
Heterogeneity conflicts in the linked data restructuring cycle’.
Information Research, 18 (3),
http://www.informationr.net/ir/18-
3/colis/paperC18.html#.WUEwnZB95dg
References
31. RIVAL Network Event 2 – November 7th 2019 – Edinburgh
Library linked data implementations and perceptions:
implications for practice
Dr Diane Pennington, Strathclyde University & Laura Cagnazzo, UWS
Research, Impact, Value & LIS - #lisrival - Edinburgh – 7th November 2019