The document presents a webinar by Martin Kaltenböck from the Semantic Web Company, discussing the PoolParty suite for developing semantic knowledge graphs aimed at enhancing sustainable development. It details the company's background, its global clientele, and partnerships while emphasizing the significance of knowledge graphs in improving data management and visibility. The session also highlights various success stories and the technical advantages centered around flexible and efficient data integration using PoolParty's services.

1. Webinar: PoolParty for
Sustainable Development:
The Climate Tagger
Welcome!
Martin Kaltenböck
Managing Partner & CFO
Semantic Web Company

2. About Semantic Web Company (SWC)
SWC was founded 2001, head-quartered in Vienna
25 experts in linked data technologies
Product: PoolParty Suite (launched 2009)
Serving customers from all over the world
EU- & US-based consulting services

3. Our Ecosystem: Customers & Partners
Some of our Customers
World Bank Group
Inter-American Development Bank (IADB)
Renewable Energy & EE Partnership (REEEP)
Development Initiatives (DI, UK)
International Atomic Energy Agency (IAEA)
Climate Technology Network (CTCN)
C2E2, DTU – UN Partnership
Ministry of Finance (A)
Council of the E.U.
European Commission (several DGs)
BMU & GIZ
Global Buildings Performance Network (GBPN)
European Innovation Partnership on Water
Canadian Broadcasting Corporation (CBC)
Red Bull Media House
Wolters Kluwer
BMJ Publishing Group
Pearson - Always Learning
Education Services Australia
Healthdirect Australia
Finance / Automotive / Publisher / Health Care / Public Administration / Energy / Education
Selected Partners
PwC (EU, US)
EPAM Systems (DE)
iQuest (RU)
EBCONT (AT)
Gravity Zero (US)
MarkLogic (US, EU)
OpenLink Software (UK, US)
Ontotext (BU)
Wolters Kluwer (worldwide)
Data to Value (UK)
Digirati (UK)
Term Management (US)
Altotech (FI)
Open Knowledge (Foundation)
Open Data Institute, The ODI (UK)
Fraunhofer IAIS (DE)
University of Leipzig (DE)
Demokritos (GR)
University of Economics (AT)
INSIGHT / DERI Galway (IRL)
We are all working on the
replacement of data chaos
by an information network

4. See how it
works...

5. ‘Things’ but not strings:
Building a ‘semantic knowledge graph’
http://www.mycom.com/
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Venice
image
http://www.mycom.com/
images/90546089
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taxonomy/97345854
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St. Mark’s
Square
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Piazza
San Marco
http://www.mycom.com
/taxonomy/4543567
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city square
piazza
has broader

6. The power of knowledge graphs:
Agility, flexibility, complexity
doc doc doc
Norway France Austria Canada
doc
Norway France Austria Canada
doc
Show me all
documents about
European countries
Traditional approach Graph-based approach
doc doc doc

7. The power of knowledge graphs:
Agility, flexibility, complexity
doc doc doc
Europe,
Norway
Europe,
France
Europe,
Austria
America,
Canada
doc
Norway France Austria Canada
doc
Show me all
documents about
European countries
Europe
Traditional approach Graph-based approach
doc doc doc

8. The power of knowledge graphs:
Agility, flexibility, complexity
doc doc doc
Europe,
Norway
Europe,
France
Europe,
Austria
America,
Canada
doc
Norway France Austria Canada
doc
Show me all
documents about
European countries
Europe
Traditional approach Graph-based approach
Show me all documents
about EU member
countries
doc doc doc

9. Norway France Austria Canada
The power of knowledge graphs:
Agility, flexibility, complexity
doc doc doc
Europe,
Norway
E.U,
Europe,
France
E.U,
Europe,
Austria
America,
Canada
doc doc doc doc doc
Show me all
documents about
European countries
Europe
Traditional approach Graph-based approach
Show me all documents
about EU member
countries
E.U

10. Norway France Austria Canada
The power of knowledge graphs:
Agility, flexibility, complexity
doc doc doc
Europe,
Norway
French,
EU,
Europe,
France
EU,
Europe,
Austria
French,
America,
Canada
doc doc doc doc doc
Show me all
documents about
European countries
Europe
Traditional approach Graph-based approach
Show me all
documents about EU
member countries
French-
speaking?
French-
speaking
EU

11. Norway France Austria Canada
The power of knowledge graphs:
Agility, flexibility, complexity
doc doc doc
Europe,
Norway
French,
EU,
Europe,
France
EU,
Europe,
Austria
French,
America,
Canada
doc doc doc doc doc
Show me all
documents about
European countries
Europe
Traditional approach Graph-based approach
Show me all
documents from EU
member countries
French-
speaking?
French-
speaking
EU
Metadata per
document
1. No or little network effects
2. No reuse of metadata
3. Metadata resides in silos
4. Data quality hard to measure
5. Not machine-readable
Knowledge about
metadata
1. Explicit knowledge models
2. Reusable and measurable
3. Metadata is machine-processable
4. Standards-based metadata
5. Linkable metadata opens silos

12. SKOS as a ‘backbone’ of knowledge graphs
http://www.w3.org/2004/02/skos/

13. PoolParty core components
Bain Capital is a venture capital
company based in Boston, MA.
Since inception it has invested in
hundreds of companies including
AMC Entertainment, Brookstone,
and Burger King. The company was
co-founded by Mitt Romney.

14. See how it works:
PoolParty components & workflows
works on
basis for
● reference taxonomies
● linked data sources
● text reference corpora
enrich
basis for
Taxonomist/
Ontologist
Developer
● Confluence, WordPress
SharePoint, Drupal, ...
● search engine
● database
is user ofContent
Manager
enrich
annotate
basis for
analyzesuses API

15. PoolParty core components
Create and maintain
taxonomies and knowledge
graphs
“URIfication” of all types of things
Linking and mapping between
taxonomies and various graphs
Access and integrate knowledge
graphs via API (Read/Write)
Support of collaborative
workflows around taxonomy
management
RDFization of text
Extraction of ‘things’ (entities)
from text based on graphs
Extraction of (free) terms and
phrases from any kind of text
Categorization of documents
Ultra-fast auto completion based
on controlled vocabularies
Integrated with highly scalable
graph databases
Integration layer to improve
content and collaboration systems
Existing integrations with
SharePoint, Drupal, Confluence
Provision of user-dialogues to
support semi-automatic tagging
URI-based Semantic Indexing
Faceted search based on
taxonomies
Content recommender services

16. PoolParty - Technical Architecture

17. Why it is useful...
For whom…

18. Success story: EIP Water Marketplace

19. Success story: The World Bank

20. Success story: GBPN Prediction Tool

21. Success story: Council of European Union

22. Success story: Healthdirect Australia
Over 120 information partners and sources
Great variety of category and metadata systems
One central vocabulary hub:
Australian Health Thesaurus (AHT)
Single point of access incl. harmonized search facets:
http://www.healthdirect.gov.au/

23. Success story: CTCN Matchmaking Assistant

24. Success story: REEEP Climate Tagger

25. Five more reasons to get started with
PoolParty. Try it out now!
Get your PoolParty 5
Thesaurus Server &
Entity Extractor trial:
http://www.poolparty.biz/test-demo/

26. Contact points & further information
Martin Kaltenböck, m.kaltenboeck@semantic-web.at
Semantic Web Company GmbH
Mariahilfer Strasse 70/8, A-1070 Vienna
+43-1-4021235
http://www.semantic-web.at
http://www.poolparty.biz
http://blog.semantic-web.at
Social Media Channels
http://slideshare.net/semwebcompany
http://youtube.com/semwebcompany
https://www.linkedin.com/groups?home=&gid=4059165

27. More Details...

28. From Simple SKOS to
large knowledge graphs
your data,
e.g. Excel
your
docs
Generate 1st
version of SKOS
taxonomy
Edit,extend &
curate
taxonomy
Extend schema,
apply ontologies,
use SKOS-XL
Link and map
between
taxonomies
and LD graphs
- Taxonomy Editing
- Collaborative workflows
- Free term extraction
- Tag recommender
- Quality Checker
- Reuse of existing
vocabularies
- Corpus Analysis
- Excel import
- XML import
- Linked data harvester
your CMS
- Reuse existing ontologies
- Create custom schemes
- Apply SKOS-XL
- Apply ontologies on your
SKOS taxonomy
- Automatic mapping between
taxonomies
- Linked Data frontend
- Link to other LD graphs, e.g.
DBpedia or Geonames

31. PoolParty at a glance - Technical Overview
user-friendly: create & maintain vocabularies
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?

32. Benefit arguments
Cost effectiveness The systemic view
Operating
efficiency
Basic
argument
IT-Management /
Software Architect
Information &
Knowledge Management
Business Process
Management
Efficient
and agile
data model
Better reuse of
existing information
resources helps to save
costs
Better understanding of
relations between things
increases communication
skills
Unified views on
business objects
lead to better
decisions
Higher
information
quality
Efficient handling of
metadata
Increased transparency on
inconsistencies and
contradictions
Information flows
adapt to the needs
of the user
Improved
information
retrieval
Automatic structuring
of unstructured data
help to save costs
Consistent use of controlled
vocabularies triggers
additional network effects
BI-like, complex
queries become
possible