Linked data implementations -- who, what, why? · 2018-12-05 · Semantic Web in Libraries...
Transcript of Linked data implementations -- who, what, why? · 2018-12-05 · Semantic Web in Libraries...
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Semantic Web in Libraries (SWIB18), Bonn, Germany
28 November 2018
Linked data implementations—
who, what, why?
Karen Smith-Yoshimura
OCLC Research
Linking Open Data cloud diagram 2017, by Andrejs Abele, John P. McCrae, Paul Buitelaar, Anja Jentzsch and
Richard Cyganiak. http://lod-cloud.net/ by CC-BY-SA license.
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International Linked Data Surveys for Implementers
2014
2015
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International Linked Data Surveys for Implementers
2014 only 2015 only 2018 only 2 surveys All 3 surveys
Total =143
35
33
24 27
24
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Geographic breakdown of 143 responding institutions
23 countries represented
0 10 20 30 40 50 60 70
USA
Spain
UK
The Netherlands
Canada
Germany
Norway
Australia
Italy
France
Switzerland
Ireland
Singapore
Sweden
Austria
China
Czech Republic
Finland
Hungary
Japan
Luxembourg
Malaysia
Portugal
2018 German Respondents
• Bavarian State Library
• German National Library
• North Rhine-Westphalian Library
Service Centre (HBZ)
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Responding institutions by type
0
5
10
15
20
25
30
Research library National library Researchinstitution
Library Network Government Service provider Public Library Museum Other
2014 2015 2018
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2018 2015
Not yet in production 26 37
Less than one year 14 19
More than one year,
less than two years15 10
More than two years 18 46
More than four years 31
How long linked data project or service in production
Total 104 112
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2018 2015
Consume linked
data34 38
Publish linked data 5 10
Both consume &
publish65 64
How linked data is used
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Success assessment
35%
21%
30%
14%
2018
Don'tknow yet
Partially
Mostly
Yes
46%
22%
19%
13%
19%
2015
Indicators of success:
• Usage
• Data re-use
• Interoperability
• User satisfaction
• Influence
• Professional development
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Most accessed
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PUBLISHING LINKED DATA
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Reasons for publishing linked
data (n=92 in both 2015 & 2018) 2018 2015
Expose to larger audience on the
Web74% 73%
Demonstrate what could be done
with datasets as linked data65% 64%
Heard about linked data and
wanted to try it out by exposing
our data as linked data.
45% 47%
Needed to publish linked data in
order to consume it25% *
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Types of data published as linked data
0 10 20 30 40 50 60
Descriptive metadata
Bibliographic data (e.g., MARC records)
Authority files
Data about people*
Ontologies/vocabularies
Digital collections
Geographic data
2015 2018
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RDF vocabularies/ontologies used
0% 10% 20% 30% 40% 50% 60% 70%
Schema.org
SKOS
Dublin Core Terms
FOAF
DCMI Metadata Terms
RDF Schema
BibFrame
Local vocabulary
2015 2018
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Serializations used
0% 10% 20% 30% 40% 50% 60% 70% 80%
N-Quads
RDFa
N3 RDF triplets
RDF/JSON
N-Triples
JSON-LD
Turtle
RDF/XML
2015 2018
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Barriers to publishing linked
data 2018
Steep learning curve for staff 41
Inconsistency in legacy data 38
Selecting appropriate ontologies to
represent our data26
Lack of resources 23
Little documentation or advice on how to
build the systems23
Establishing the links 22
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CONSUMING LINKED DATA
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Reasons for consuming linked data 2018 2015
Provide our users with a richer experience. 54 51
Enhance our own data by consuming linked data
from other sources.49 50
Heard about linked data and wanted to try it out
by using linked data sources.23 17
More effective internal metadata management. 21 32
Experiment with combining different types of
data into a single triple store. 20 17
Greater accuracy and scope in our search
results19 27
See if consuming linked data would improve our
Search Engine Optimization (SEO)7 19
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Linked Data sources consumed
0% 10% 20% 30% 40% 50% 60% 70%
id.loc.gov*
VIAF*
Dbpedia
GeoNames
Wikidata
WorldCat.org*
Getty Vocabularies
FAST*
ISNI
Resources we convert ourselves
2015 2018
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Some that started consuming Wikidata
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Barriers to consuming linked
data 2018 2015
Matching, disambiguating and
aligning source data and linked
data resources
48% 39%
What's published as linked data
isn’t always reusable/lacks URIs31% 27%
Size of RDF dumps 28% 20%
Unstable endpoints 28% 17%
Service reliability 26% 15%
Mapping of vocabulary 26% 29%
Understanding how data is
structured before using it24% 20%
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SOME NEW EXAMPLES IN
PRODUCTION
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http://data.nationallibrary.fi
http://v.mek.oszk.hu/FlintSparqlEditor
/index-mek.html
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http://data.carnegiehall.org http://archesproject.com/
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SOME ADVICE FROM
IMPLEMENTERS & IMPLICATIONS
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• Learn from others
• Focus on your use cases
• Collaborate with others
• Integrate linked data into your daily workflows
• Analyze what legacy data should be converted
• Never underestimate the amount of data
cleanup that will be required.
• Use existing identifiers and ontologies
• Iterate based on user feedback
• Expect benefits only after reaching scale
Advice from implementers
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• Emergence of service providers
• Growing diversity of linked data implementations
• Most linked data projects and services remain
experimental or educational in nature.
Implications
“This is the future of data for libraries
and the longer we wait the further
behind we're going to fall.”
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SM
Together we make breakthroughs possible.
Thank you!
Contact: Karen Smith-Yoshimura
Semantic Web in Libraries (SWIB18), Bonn, Germany
28 November 2018
@KarenS_Y
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