The webinar introduces SKOS (Simple Knowledge Organization System) and argues it should be the focal point of linked data strategies. It discusses using SKOS to create knowledge graphs by linking various data sources and perspectives. It then demonstrates PoolParty software for building and querying SKOS knowledge graphs, including importing and annotating documents, applying ontologies, and asking complex queries across linked data sources.

1. Why SKOS should be a focal point
of your linked data strategy

2. Welcome to this webinar!
Agenda (including several live demos)
1. Intro: Knowledge graphs & linked data
2. Various perspectives on SKOS
3. Linked data based information architecture
4. Proudly presenting … PoolParty 4.2
1. Discussion
Andreas Blumauer, MSc IT
CEO of Semantic Web Company, Vienna
“Product owner” of PoolParty Semantic Suite
Working in the fields of Text Mining, Semantic Web &
Linked Data for over 13 years

3. About Semantic Web Company (SWC)
SWC was founded 2001 in Vienna, Austria
Over 20 experts in linked data technologies
Product: PoolParty Suite (launched in 2009)
Serving customers from various industries
EU- & US-based partner network

4. Our network: Customers & Partners
Customers
● Credit Suisse
● Daimler
● Roche
● Wolters Kluwer
● World Bank Group
● The Pokémon Company
● Healthdirect Australia
● Ministry of Finance (A)
● Wood Mackenzie
● Council of the E.U.
● TC Media
● American Physical Society
● Education Services Australia
● Pearson
● Techtarget
● Norwegian Directorate of
Immigration
● REEEP
● GBPN
● City of Vienna
● ...
Finance / Automotive / Publisher / Health Care / Public Administration / Energy / Education
Partners
● Cognizant
● EPAM Systems
● iQuest
● DTI AG
● Tenforce
● OpenLink Software
● Ontotext
● brox
● bridgingIT
● Wolters Kluwer
● Term Management
● Taxonomy Strategies
● Search explained
● WAND
● Digirati
● KMSolutions
● Linked Data Factory
● Taxonic
● semweb

5. 1. Intro: Knowledge graphs & linked data

6. Graphs everywhere...
Microsoft
Facebook
Google

7. Graphs are the key to ‘smart data’
It’s all about things,
not strings!

8. Why is Google’s Knowledge Graph just
about to transform ‘search’?
Facts and context information
around an entity, incl. dynamic
API calls
Imagine, your company had already
its own specific knowledge graph(s).
- complex queries (‘questions’) can be answered
- integrated views on ‘things’
- networked nature of entities used for research
- basis for personalised services

9. How does it work?
http://rdf.freebase.com/m/07d5b
“Tim Berners-Lee”
rdfs:label
http://rdf.freebase.com/m/04jpl
freebase:place_of_birth
“London”rdfs:label
freebase:tourist_attractions
http://rdf.freebase.com/m/07gyc
“London Eye”rdfs:label

10. Why should I use graphs
instead of relational databases?
http://rdf.freebase.com/m/07d5b
“Tim Berners-Lee”
rdfs:label
http://rdf.freebase.com/m/04jpl
freebase:place_of_birth
“London”rdfs:label
freebase:tourist_attractions
http://rdf.freebase.com/m/07gyc
“London Eye”rdfs:label
http://dbpedia.org/
resource/Tim_Berners-Lee
http://www.w3.org/People/
Berners-Lee/
foaf:homepage
http://dbpedia.org/resource/
World_Wide_Web_Consortium
dbpedia:leaderName
http://sws.geonames.org/
4943351/
dbpedia:location
“Massachusetts Institute
of Technology”
http://sws.geonames.org/
2643743/
wgs84_pos:lat
wgs84_pos:long
42.35954-71.09172

11. Why should I use
semantic web standards based graphs?
● URIs
● HTTP and
● reuse of standards based
vocabularies enable
● collaborative efforts to create
o links
o links
o links
o links
o links
o links
o links
● …
● between entities and not only
● documents
● to build the basis for standards
based Q&A machines

12. Pitstop: Linked Data is a data model
based on graphs
● Linked Data is a graph based data
model
which can represent & process
a wide range of information
→
Perfectly suitable for data integration &
dynamic semantic publishing (DSP)
in distributed environments (“semantic
web”)

13. Linked data platforms:
How many data sources are used here?

14. 2. Various perspectives on SKOS

15. SKOS makes taxonomies/thesauri
accessible, linkable & reusable
http://www.w3.org/2004/02/skos/

16. SKOS as a basis to visualize and browse
semantic knowledge graphs

17. SKOS: You are not alone...
● Eurovoc (EU)
● ESCO (EU)
● Jurivoc (SUI)
● ScoT (AUS)
● Agrovoc (UN)
● MeSH (US)
● Getty Vocabularies (US)
● GEMET (EEA)
● GeoThesaurus (AT)
● STW Economy (DE)
● Polythematic SH (CZ)
● Canadian Subject Headings (Can)
● LCSH (US)
● Worldbank Taxonomy (WBG)
● Labor Law Germany Thesaurus (DE)
● Reegle Thesaurus (REEEP)
● Austrian Tax Law Thesaurus (AT)
● UNESCO Thesaurus (UN)
● New York Times SH (US)
● RAMEAU subject headings (FR)
● TheSoz (DE)
● The General Finnish Thesaurus (FIN)
● NAL Thesaurus (US)
● Social Semantic Web Thesaurus (AT)
● Courts thesaurus (DE)
● SITC-V4 (UN)
● Google Product Taxonomy (US)
● NAICS 2012 (US)
● Common Procurement Vocabulary (ES)
● UKAT UK Archival Thesaurus (UK)
● NASA taxonomy (US)
● IVOA astronomy vocabularies (UK)
● IPTC News Codes (UK)
● WAND taxonomies (US)

18. SKOS is a ‘semantic interface’ to retrieve
and link distributed content
EurovocWKD German labor law thesaurus
STW
Thesaurus
DBpedia

19. SKOS is at the intersection of three
disciplines and their paradigms
SKOS
librarians &
taxonomists
data engineers &
artificial intelligenceschemas &
ontologiestaxonomies &
classification
systems
text mining &
data analytics
computational linguists &
information managers

20. Provide integrated & interlinked views on
all kind of information
The SKOS/Linked Data based approach for
information integration
Transforming documents
into SKOS based graphs
Annotating &
categorising
documents
SKOS based graph of
concepts
Tree of categories
& terms
Standards based
ontologies linked to
SKOS based
concept graphs
Schemas, classes,
properties,
restrictions & rules

21. Access SKOS via URIs and HTTP, based on
standards, it’s machine-readable!
SKOS based graph of
concepts
Tree of categories
& terms
http://vocabulary.semantic-web.at/semweb/367
Tim Berners-Lee TimBL
skos:altLabelskos:prefLabel
(Poly-)hierarchical
relations
Mappings
non-hierarchical
relations

22. Let your documents become part of
something bigger & make them smart!
Transforming documents
into SKOS based graphs
Annotating &
categorising
documents
http://vocabulary.semantic-
web.at/semweb/367
Tim Berners-Lee TimBL
skos:altLabelskos:prefLabel
Show me biographies of all
computer scientists working
for an organization located
near Boston.

23. Make conceptual model & the semantics
of your data explicitly available
Standards based
ontologies linked to
SKOS based
concept graphs
Schemas, classes,
properties,
restrictions & rules

24. SKOS is not expressive enough?
Apply ontologies on your SKOS thesauri!

25. 3. Linked data based
information architecture

26. Four-layered information architecture
enterprise
knowledge model
domain specific
knowledge model
annotation &
categorization
legacy data
& documents

27. Linked Enterprise Data
Relevant information to
answer specific questions is
all over the places.
It’s often time consuming to
find and link them.
1. Use
taxonomies/ontologies
for information integration
2. Use documents as they
were a knowledge graph
3. Use relational databases
as
virtual RDF graphs

28. SPARQL is close to the way non-
technicians use to formulate questions
SELECT DISTINCT ?personname ?picture ?countryname ?hdi ?picture
WHERE
{
?person skos:prefLabel ?personname .
?country skos:prefLabel ?countryname .
?person a dbpedia:Person .
?country a dbpedia:Country .
?person skos:related ?country .
?country <http://dbpedia.org/property/hdi> ?hdi .
FILTER ( ?hdi < 0.6)
OPTIONAL
{
?person foaf:depiction ?picture .
}
} ORDER BY DESC(?hdi)
I want to explore medical
research trends in relation to
regional prosperity.

29. The traditional approach for
data integration
Person 4711
Name
Jeff Bezos
Affiliation
Amazon
Born in
Albuquerque
Land 4812
Name
USA
BIP
$ 15.684 billion
HDI
0.937
Solution: Application will be
developed to integrate the
two databases.
Show me the ‘most influential people
in the world’ who were born in countries
with an HDI less than 0.5?

30. PersonOrganization Place
affiliated with born in
Ontology-Graph
Jeff Bezos
Amazon Albuquerque
United States
Knowledge Graph 2
GDP
$ 15.684
billion
HDI
0,937
Continents U.S.
Thesaurus/Taxonomy-Graph
America New Mexico
Albuquerque
South
America
Knowledge Graph 1
Show me the ‘most influential
people in the world’ who were
born in countries
with an HDI less than 0.5?
Solution: Taxonomies
are used
to link/map graphs

31. 4. Proudly presenting … PoolParty 4.2

32. The Hitchhiker’s Guide to
Ontology Management
The answer to taxonomy,
ontology management and
everything is...

33. PoolParty at a glance
● user-friendly: create & maintain knowledge graphs
● standards-based: based on W3C standards
● graph-based: natively built on graph databases
● embedded in ecosystem: use of linked (open) data
● best-of-breed: text mining, taxonomies & ontologies
● enterprise-ready: secure, simple to install
● integrable: connectors for SharePoint, Drupal,
Confluence, WordPress, … your own CMS?

34. Creation and maintenance of SKOS graphs:
drag & drop, autocomplete, browser-based

35. Import and creation of ontologies

36. Apply ontologies on SKOS model:
Classification of concepts

37. Apply ontologies on SKOS model:
Relations and Attributes

38. Apply ontologies on SKOS model:
Domain and Range Restrictions
For example: ‘Product’ and ‘Standard’ may be related by ‘uses’.
PoolParty rule engine takes care of domain and range restrictions.

39. Make use of linked (open) data

40. ...and ask tricky questions
Step 1: Link your thesaurus to
knowledge graphs (e.g. DBpedia) /
ontologies (e.g. schema.org)
Step 2: Ask tricky questions
PREFIX skos:<http://www.w3.org/2004/02/skos/core#>
PREFIX foaf:<http://xmlns.com/foaf/0.1/>
PREFIX dbpedia:<http://dbpedia.org/ontology/>
SELECT DISTINCT ?personname ?timelink
WHERE
{ ?person skos:prefLabel ?personname .
?person a dbpedia:Person .
?person <http://purl.org/dc/terms/subject>
<http://dbpedia.org/resource/Category:Princeton_University_alumni> .
OPTIONAL
{ ?person
<http://mercury.poolparty.biz/PoolParty/schema/Time#time100page>
?timelink .
} }
alumni Who of the ‘most influential
people in the world’ are
Princeton University alumni?
Results
Carl Cahn http://time.com/70813/
Jeff Bezos http://time.com/70917/

41. Reuse ontologies from LOD sources

42. Link between several thesauri/taxonomies

43. Make use of text corpus analysis

44. Use your knowledge graph
for entity extraction
Step 1: Create a thesaurus Step 2: Deploy Extraction Service

45. Use PoolParty PowerTagging to integrate
with enterprise content systems

46. Use PoolParty for Semantic Search

47. Make use of PoolParty Semantic Integrator

48. Start SKOS, grow big.
So Long, and Thanks
for All the Links

49. Announcements
Webinar:
Semantic SharePoint
Wed, June 25, 2014
4:30 PM - 5:30 PM CEST
Register here.

50. Contact points & further information
Andreas Blumauer, MSc ITa.blumauer@semantic-web.at
http://at.linkedin.com/in/andreasblumauer/
https://plus.google.com/115842492297705285184/
Semantic Web Company GmbH
Mariahilfer Strasse 70/8, A-1070 Vienna
+43-1-4021235
http://www.semantic-web.at
http://www.poolparty-software.com
http://slideshare.net/semwebcompany
http://youtube.com/semwebcompany