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What Does A Metadata Professional Need
to Know?
Ted Lawless
NISO Virtual Conference: BIBFRAME & Real WorldApplications of Linked
Bibliographic Data – June 15, 2016
2
Abstract
What does a metadata professionalhave to learn to begin working with linked
data? How does one get started?
This talk with focus on concepts, tools, and techniques necessary to begin
"doing" linked data. Workedexamples will provide the audience with concrete
ideas and resources for getting started with implementations.
3
Outline
• Work through a linked data example
• Discuss concepts
• Talk about resources and tools
• Final observations
Where to begin?
5
"Linking Open Data cloud diagram 2014, by Max Schmachtenberg, Christian
Bizer, Anja Jentzsch and Richard Cyganiak. http://lod-cloud.net/"
6
Where to begin?
• Overwhelming when thinking at the scale of the Web.
• Where is the clear, immediate benefit?
• How do I get there?
7
Motivation – experience with VIVO
http://vivoweb.org
8
Worked Example
• Identify important sub-collection
• Match data to a central source
• Map existing data to RDF
• Publish as linked data
• Integrate
https://github.com/lawlesst/c4l16-idhub
9
Collection – Web of Science™
• Web of Science Core Collection - Science Citation Index
• 8,797 journals as of 2016
• Started in Philadelphia in 1964 by Eugene Garfield
• Carefully selected and curated to include only most
important peer reviewed journals
• Evolved to include Social Sciences, Humanities,
Conference Proceedings, and Scholarly Books
10
Process
11
Matching to Central Source
Local ID Title ISSN
70884J Nature 0028-0836
Local ID Title ISSN Wikidata ID
70884J Nature 0028-0836 Q180445
12
Results
• 8,797 journals
• 7,365 links to Wikidata
• ~84%
13
CSV to RDF
14
Tying it together
15
Tying it together
https://jsfiddle.net/lawlesst/n5pLx38j/
16
Skills and Concepts
Repurposing
existing data
• Often CSV exported
from system
SPARQL
• RDF query language Matching or
reconciliation
Ontology
modeling
Creating RDF
programmatically
Querying Web
APIs
System
configuration
Integration
• Web development
skills
17
Skills and Concepts
18
Repurposing existing data
19
SPARQL
20
Matching / Reconciliation
21
Ontology mapping & RDF creation
22
Publishing
23
Integrating
24
Skills and Concepts
Repurposing
existing data
• Often CSV exported
from system
SPARQL
• RDF query language Matching or
reconciliation
Ontology
modeling
Creating RDF
programmatically
Querying Web
APIs
System
configuration
Integration
• Web development
skills
25
Resources
• Programming
– Python for Informatics
• http://www.pythonlearn.com/book.php
– Software Carpentry
• http://software-carpentry.org/
• Linked Data / Semantic Web
– Linked Data Patterns
• http://patterns.dataincubator.org/book/
– Learning SPARQL by Bob DuCharme
• http://www.learningsparql.com/
– Semantic Webfor the WorkingOntologist
• https://www.amazon.com/Semantic-Web-Working-Ontologist-
Second/dp/0123859654
26
Tools
• Python
– RDFLib, csvkit, petl, fuzzywuzzy
• OpenRefine http://openrefine.org/
– Graphical, text cleaning, mapping to RDF
• Karma http://usc-isi-i2.github.io/karma/
– Graphical, ontology mapping, data integration, sophisticated.
27
Tools
• VIVO as a platform
– http://vivoweb.org
– Triple store manager, ontology editor, instance editor, user accounts, Solr
searchindex of triples, Refine reconciliation endpoint.
– Try it: https://github.com/lawlesst/vivo-vagrant
• Linked Data Fragments
– http://linkeddatafragments.org
– Low cost of serving data, modern framework, query in the browser.
28
Observations
• Hands on experience
• Time to experiment with new tools and techniques
• Abundance of resources and tools to learn
Thank you
Ted Lawless – ted.lawless@thomsonreuters.com

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Lawless-3-jun15

  • 1. What Does A Metadata Professional Need to Know? Ted Lawless NISO Virtual Conference: BIBFRAME & Real WorldApplications of Linked Bibliographic Data – June 15, 2016
  • 2. 2 Abstract What does a metadata professionalhave to learn to begin working with linked data? How does one get started? This talk with focus on concepts, tools, and techniques necessary to begin "doing" linked data. Workedexamples will provide the audience with concrete ideas and resources for getting started with implementations.
  • 3. 3 Outline • Work through a linked data example • Discuss concepts • Talk about resources and tools • Final observations
  • 5. 5 "Linking Open Data cloud diagram 2014, by Max Schmachtenberg, Christian Bizer, Anja Jentzsch and Richard Cyganiak. http://lod-cloud.net/"
  • 6. 6 Where to begin? • Overwhelming when thinking at the scale of the Web. • Where is the clear, immediate benefit? • How do I get there?
  • 7. 7 Motivation – experience with VIVO http://vivoweb.org
  • 8. 8 Worked Example • Identify important sub-collection • Match data to a central source • Map existing data to RDF • Publish as linked data • Integrate https://github.com/lawlesst/c4l16-idhub
  • 9. 9 Collection – Web of Science™ • Web of Science Core Collection - Science Citation Index • 8,797 journals as of 2016 • Started in Philadelphia in 1964 by Eugene Garfield • Carefully selected and curated to include only most important peer reviewed journals • Evolved to include Social Sciences, Humanities, Conference Proceedings, and Scholarly Books
  • 11. 11 Matching to Central Source Local ID Title ISSN 70884J Nature 0028-0836 Local ID Title ISSN Wikidata ID 70884J Nature 0028-0836 Q180445
  • 12. 12 Results • 8,797 journals • 7,365 links to Wikidata • ~84%
  • 16. 16 Skills and Concepts Repurposing existing data • Often CSV exported from system SPARQL • RDF query language Matching or reconciliation Ontology modeling Creating RDF programmatically Querying Web APIs System configuration Integration • Web development skills
  • 21. 21 Ontology mapping & RDF creation
  • 24. 24 Skills and Concepts Repurposing existing data • Often CSV exported from system SPARQL • RDF query language Matching or reconciliation Ontology modeling Creating RDF programmatically Querying Web APIs System configuration Integration • Web development skills
  • 25. 25 Resources • Programming – Python for Informatics • http://www.pythonlearn.com/book.php – Software Carpentry • http://software-carpentry.org/ • Linked Data / Semantic Web – Linked Data Patterns • http://patterns.dataincubator.org/book/ – Learning SPARQL by Bob DuCharme • http://www.learningsparql.com/ – Semantic Webfor the WorkingOntologist • https://www.amazon.com/Semantic-Web-Working-Ontologist- Second/dp/0123859654
  • 26. 26 Tools • Python – RDFLib, csvkit, petl, fuzzywuzzy • OpenRefine http://openrefine.org/ – Graphical, text cleaning, mapping to RDF • Karma http://usc-isi-i2.github.io/karma/ – Graphical, ontology mapping, data integration, sophisticated.
  • 27. 27 Tools • VIVO as a platform – http://vivoweb.org – Triple store manager, ontology editor, instance editor, user accounts, Solr searchindex of triples, Refine reconciliation endpoint. – Try it: https://github.com/lawlesst/vivo-vagrant • Linked Data Fragments – http://linkeddatafragments.org – Low cost of serving data, modern framework, query in the browser.
  • 28. 28 Observations • Hands on experience • Time to experiment with new tools and techniques • Abundance of resources and tools to learn
  • 29. Thank you Ted Lawless – ted.lawless@thomsonreuters.com