1
POOLPARTY
SEMANTIC
SUITE
FUNCTIONAL
OVERVIEW
Andreas Blumauer
CEO, Semantic Web Company
Helmut Nagy
COO, Semantic Web Company
2
Andreas
Blumauer
Semantic Web
Company
serves customers
>200
founded
founder &
CEO of
2004
located
INTRODUCTION
Vienna
developer and
vendor of
active at
current
Version
based on
manages
Knowledge
Graphs
Taxonomies
part of
standard for
part of
is a
6.0
3
INTRODUCING
SEMANTIC WEB
COMPANY
Semantic Web Company (SWC)
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Founded in 2004
Based in Vienna
Privately held
40+ employees, experts in text
mining & linked data
~15-20% revenue growth
per year
2.5 Mio Euro funding for R&D
SWC named to KMWorld’s
2016 and 2017 ‘100
Companies That Matter in
Knowledge Management’
https://www.semantic-web.com
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INTRODUCING
POOLPARTY
PoolParty Semantic Suite
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First release in 2009
Current version 6.0
W3C standards compliant
Over 200 installations
world-wide
50% of revenue is reinvested
into PoolParty development
PoolParty on-premises or
used as a cloud service
KMWorld listed PoolParty as
Trend-Setting Product 2015
and 2016
https://www.poolparty.biz/
5
SELECTED
CUSTOMER
REFERENCES
AND PARTNERS
Customer References
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Credit Suisse
US
Boehringer Ingelheim
West
Roche
adidas
The Pokémon Company
Canadian Broadcasting Corporation
Harvard Business School
Wolters Kluwer
Talend
HealthStream
TC Media
Techtarget
Seek
CafePress
Pearson - Always Learning
Education Services Australia
American Physical Society
Healthdirect Australia
World Bank Group
Inter-American Development Bank
Renewable Energy Partnership
Wood MacKenzie
Oxford University Press
International Atomic Energy Agency
Norwegian Directorate of Immigration
Ministry of Finance (AT)
Council of the E.U.
Australian National Data Service
UK
US
East
SWC headquarters
AUS/
NZL
Partners
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Accenture
EPAM Systems
Enterprise Knowledge
Mekon Intelligent Content Solutions
B-S-S Business Software Solutions
MarkLogic
Wolters Kluwer
Digirati
Quark
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MAKE USE OF
POOLPARTY
SEMANTIC
SUITE
OVERVIEW
7
Taxonomy &
Ontology Server
Entity Extractor &
Text Mining
controlled vocabulary
as a basis for highly
precise entity
extraction
TECHNICAL
CORE
COMPONENTS
Data Integration &
Data Linking
Unstructured
Data
Semistructured
Data
Structured
Data
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.
entity extractor informs
all incoming data
streams about its
semantics and links them
Unified
Views
identify new
candidate terms
to be included
in a controlled vocabulary
PoolParty
GraphSearch
8
PoolParty
Semantic Suite
System
Architecture
Overview
9
‘Elevator
Pitch’
▸
Built as a ‘Semantic Middleware’
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Outstanding user-friendliness
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Fully standards-compliant
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Highly precise entity extraction
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Comprehensive API
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Excellent maintainability of extraction models
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Integrated with leading search engines & graph databases
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Integrated with leading content management platforms
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Product configuration options for growing requirements
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Highly expertised partners / service team
10
Product
Overview
All products are
available as
cloud services or
for on-premise
installation
> PoolParty
Feature & Price
Matrix
Integration with Graph databases
$76,000 ppt
Integration with Search engines
$3,750/mo
Data linking & mapping
Data transformation pipelines with UnifiedViews
Graph Search Server
PoolParty
Semantic
Integrator
Entity Extractor Extractor API
Autopopulate project from DBpedia
Export to Remote Repository
Workflow Management
SKOS-XL (optional)
PoolParty
Enterprise
Server
Ontologies and Custom Schemes
Quality Management & Reports
Advanced Corpus Management
Vocabulary Mapping, Linked Data Mapping
Linked Data Enrichment, Frontend, and SPARQL endpoint
PoolParty
Advanced
Server
SKOS Taxonomy Management
Multiple Projects
Taxonomy Rest API
Import/Export (incl. Excel)
Rollback and History
PoolParty
Basic
Server
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BASIC PRINCIPLES
Benefiting from the Semantic Web
in a Nutshell
12
Four-layered
Content
Architecture
13
PoolParty as a
supervised
learning
system
PowerTagging
is user of
Content Manager
annotates
CMS
proposes
extensions
is basis of
Index
enriches
uses API
Extractor
is basis of
Integrator
analyzes
uses API
is user of
Taxonomist/
Ontologist
is basis of
Thesaurus
Server
extends
Corpus Learning/
Semantic Analysis
14
Interpretant
Semiotic Triangle
The level of efficiency of
an Interpretant depends
mainly on its ability to
correctly link a symbol
with the object it stands
for.
This is applicable to
human beings and to
software agents as
well.
Telescope
Symbol
Object
Resolving Language Problems
“While most people can deal
with linguistic features as
synonyms, homographs,
polyhierarchies, and even with
far more peculiar
characteristics of natural
languages, machines often
struggle with automatic
sense-making because of the
lack of a semantic knowledge
model that can be used
programmatically.”
‘Things’ but not Strings:
Using a ‘Semantic Knowledge Graph’
Retina
Funduscope
prefLabel
http://www.my.com/
taxonomy/62346723
image
http://www.my.com/
images/90546089
http://www.my.com/
taxonomy/
97345854
prefLabel
Ophthalmoscope
altLabel
has broader
http://www.mycom.com
/taxonomy/4543567
prefLabel
Diagnostic Equipment
The power of knowledge graphs:
Agility, extensibility, precision
Traditional approach
Retinoscope
doc
Endoscope
doc
Flowmeter
doc
Show me all documents
about Diagnostic
Equipment
Pessary
doc
Retinoscope
doc
Graph-based approach
Endoscope
doc
Flowmeter
doc
Pessary
doc
The power of knowledge graphs:
Agility, extensibility, precision
Traditional approach
Show me all documents
about Diagnostic
Equipment
Graph-based approach
Diagnostic
Equipment
Diagnostic
Equipment,
Retinoscope
doc
Diagnostic
Equipment,
Endoscope
doc
Diagnostic
Equipment,
Flowmeter
doc
Surgical
Equipment,
Pessary
doc
Retinoscope
doc
Endoscope
doc
Flowmeter
doc
Pessary
doc
The power of knowledge graphs:
Agility, extensibility, precision
Show me all documents
about Diagnostic
Equipment
Traditional approach
Show me all
documents about
Funduscopes
Diagnostic
Equipment,
Retinoscope
doc
Diagnostic
Equipment,
Endoscope
doc
Diagnostic
Equipment,
Flowmeter
doc
Graph-based approach
Diagnostic
Equipment
Surgical
Equipment,
Pessary
doc
Retinoscope
doc
Endoscope
doc
Flowmeter
doc
Pessary
doc
The power of knowledge graphs:
Agility, extensibility, precision
Show me all documents
about Diagnostic
Equipment
Traditional approach
Show me all
documents about
Funduscopes
Graph-based approach
Diagnostic
Equipment
Funduscope
Funduscope,
Diagnostic
Equipment,
Retinoscope
doc
Diagnostic
Equipment,
Endoscope
doc
Diagnostic
Equipment,
Flowmeter
doc
Surgical
Equipment,
Pessary
doc
Retinoscope
doc
Endoscope
doc
Flowmeter
doc
Pessary
doc
The power of knowledge graphs:
Agility, extensibility, precision
Show me all documents
about Diagnostic
Equipment
Traditional approach
Show me all
documents about
Ophthalmoscopes
Graph-based approach
Diagnostic
Equipment
Funduscope
Ophthalmoscope,
Funduscope,
Diagnostic
Diagnostic
Equipment,
Equipment,
Endoscope
Retinoscope
doc
doc
Diagnostic
Equipment,
Flowmeter
doc
Surgical
Equipment,
Pessary
doc
Retinoscope
doc
Endoscope
doc
Flowmeter
doc
Pessary
doc
The power of knowledge graphs:
Agility, extensibility, precision
Show me all documents
about Diagnostic
Equipment
Traditional approach
Show me all
documents about
Funduscopes
Optical
Instruments,
Ophthalmoscope
Funduscope,
Diagnostic
Equipment,
Retinoscope
doc
Optical
Instruments,
Diagnostic
Equipment,
Endoscope
doc
Diagnostic
Equipment
Optical
Instruments
Optical
instruments?
Diagnostic
Equipment,
Flowmeter
doc
Graph-based approach
Surgical
Equipment,
Pessary
doc
Funduscope
Retinoscope
doc
Endoscope
doc
Flowmeter
doc
Pessary
doc
The power of knowledge graphs:
Agility, extensibility, precision
Traditional approach
Show me all documents
about Diagnostic
Equipment
Show me all
documents about
Funduscopes
Metadata per
document
Knowledge about
metadata
Diagnostic
Equipment
Optical
Instruments
Optical
Optical
Instruments,
instruments?
1. No orOptical
little network effects
Ophthalmoscope
2. No reuse
of metadata
Funduscope,
Instruments,
Diagnostic
Surgical
Diagnostic
Diagnostic
3. Metadata resides in
silos
Equipment,
Equipment,
Equipment,
Equipment,
4. DataEndoscope
quality hard Flowmeter
to measure Pessary
Retinoscope
5.
doc
Not machine-readable
doc
doc
Graph-based approach
doc
Funduscope 1.
Retinoscope
doc
2.
3.
4.
5.
Explicit knowledge models
Reusable and measurable
Metadata is machine-processable
Standards-based
metadataPessary
Endoscope
Flowmeter
Linkable metadata opens silos
doc
doc
doc
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Support for
XML to RDF
mapping:
Structured and
unstructured
elements
transformed to
RDF
<article>
<title>How to Use an Ophthalmoscope</title>
<metadata>
<id>328832</id>
<author>Mike Miller</author>
<pub_date>March 20, 2016</pub_date>
<version>2</version>
<status>approved</status>
</metadata>
<topics>Ophtalmoscopes</topics>
<text>
Proper use of an funduscope requires a bit of
practice and familiarity with the functions of your
device. Regardless of model type, these hand-held
devices are critical in the evaluation and diagnosis
of a variety of diseases in the eye.
After this examination is complete, follow the
retinal arteries and examine the four vascular
arcades including the superotemporal,
superonasal, inferotemporal, and inferonasal.
</text>
<image>http://my.com/img/99.jpg</image>
</article>
Mike Miller
skos:prefLabel
skos:altLabel
Michael Miller
http://my.com/people/32
schema:Article
dct:creator
How to Use an
Ophthalmoscope
rdf:type
dct:title
http://my.com/docs/328832
Eye Disease
skos:subject
skos:prefLabel
schema:image
skos:subject
http://my.com/img/99.jpg
skos:prefLabel
skos:broader
schema:image
skos:prefLabel
Ophtalmoscopes
Diagnostic
Equipment
skos:altLabel
Funduscopes
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‘Setting the
rules’ for text
mining & entity
extraction via
thesaurus
Proper use of an funduscope
requires a bit of practice and
familiarity with the functions of
your device.
Diagnostic Equipment
Ophtalmoscope
26
BASIC
FUNCTIONALITIES
PoolParty’s core competencies
at a glance
27
Maintaining
Vocabularies
Taxonomies and controlled
vocabularies are maintained by
using the SKOS standard of W3C.
The intuitive user interface
provides comfortable control
elements like drag & drop or
autocomplete.
A tree view on the taxonomy
plays a central part in navigation
and orientation.
Place your screenshot here
28
SKOS Editor
The SKOS View on a concept
allows the management of labels
(e.g. synonyms), hierarchies and
non-hierarchical relations, and
mappings to other vocabularies.
Also more complex actions like
merging of concepts, moving of
subtrees or the creation of
poly-hierarchies are supported.
PoolParty fully covers the SKOS
standard of W3C incl. SKOS-XL
and SKOS Collections.
Place your screenshot here
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History &
Audit Trails
Every change being made on a
concept of a thesaurus is stored
and can be tracked.
A full history containing the author,
timestamp and action being taken
can be displayed for each concept
and for the whole project.
Recovery and rollback can be
managed by PoolParty’s snapshot
mechanism.
Place your screenshot here
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Linking &
Mapping
The same concept can occur in
several taxonomies and can be put
in different contexts.
PoolParty provides a comfortable
dialogue for the semi-automatic
linking between concepts from
several thesauri.
Additionally, concepts can also be
mapped to linked data sources like
DBpedia or Geonames, or even to
non-RDF sources provided by you.
Place your screenshot here
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User Management
& Roles
User Management is based on user
accounts, roles, and groups.
User authentication can be
integrated with LDAP.
PoolParty’s security layer is based
on Spring Security.
PoolParty’s API is fully integrated
with the security layer.
Place your screenshot here
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Workflows
Approval (or rejection) of changes
on a thesaurus can be governed by
workflows.
Several roles in the PoolParty
system have different rights to
apply changes, reject or approve
those.
A clearly structured dashboard
helps taxonomists not to loose
track of all the tasks that need to
be performed.
Place your screenshot here
33
SKOS based
Taxonomy Management
Workflows
Taxonomy Linking
Import Excel
SELECTED
VIDEOS
> PoolParty on
YouTube
34
ADVANCED
FUNCTIONALITIES
Efficient taxonomy management and
text mining based on PoolParty
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Entity Extraction
PoolParty’s API provides a rich set of
methods for text mining and entity
extraction.
This ultra-fast service makes use of
your controlled vocabularies,
therefore it is highly accurate for
your specific domain.
The service will improve over time
and learns from reference text
corpora. It supports over 40
languages and comes with a
powerful disambiguation algorithm.
Place your screenshot here
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Custom Schemes
& Ontologies
SKOS is based on a simple schema.
This can be expanded by additional
custom schemes.
Custom schemes can be created
with help of PoolParty’s ontology &
schema editor.
For an increased interoperability,
PoolParty provides a rich set of
preconfigured ontologies like
schema.org or FOAF.
Place your screenshot here
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How PoolParty’s
ontology and
custom schema
management
plays together
with taxonomies
Taxonomy
Custom Schema
Ontology
Ontology 1
from library
Ontology 2
(imported)
Ontology 3
(custom-made)
38
Quality Management
& Import Validation
Data quality and especially the
quality of metadata is key to a more
efficient information management.
PoolParty Server provides several
built-in quality checks (e.g. to avoid
circularities).
Checks can be executed when
imports are made, at run-time or at
any time to generate a quality
report.
Place your screenshot here
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Corpus Analysis
PoolParty can automatically
analyze reference text corpora.
The calculation of a statistical
model of a ‘typical vocabulary’ of
a specific domain helps to
suggest candidate concepts for
the expansion of a taxonomy.
By this means, the quality of
term extraction improves over
time and potential relations
between concepts and terms can
be suggested by the system.
Place your screenshot here
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I need support to
continuously extend our
taxonomy / controlled
vocabulary!
Term 8
skos:
Concept
Term 1
Corpus analysis
results in a
network of
concepts and
terms
skos:
Concept
Term 7
Term 2
Term 3
Reference
Corpus
-
Websites
PDF, Word, …
Abstracts from
DBpedia
RSS Feeds
skos:
Concept
Term 4
Term 5
-
Term 6
Relevant terms and phrases
Relevancy of concepts
co-occurence between concepts and terms
co-occurence between terms and terms
41
Linked Data
The use of Linked Data standards
increases interoperability of your
knowledge graphs & metadata.
With PoolParty, each thesaurus
and ontology can be provided as a
Linked Data graph.
In return, every linked data source
can potentially be used to enrich a
thesaurus.
PoolParty supports scenarios like
‘Enterprise Linked Data’ as well as
‘Linked Open Data’.
Place your screenshot here
42
RDF based ETL
Data processing tasks can be
modelled as pipelines: Make use of
the intuitively usable graphical
interface.
Versatile data integration platform:
Link data from internal and
external data sources in a central
NoSQL linked data warehouse.
Custom plugins: Your data
processing pipelines are highly
customizable by creating your own
data processing units (DPUs).
Place your screenshot here
43
PoolParty
Semantic
Integrator at a glance
Unstructured
Data
Deep Data
Analytics
Structured
Data
Semantic
Integrator
Watch Tutorial
Semantic
Search
ETL / Monitoring / Scheduling
44
GraphSearch
Semantic search at the highest
level: PoolParty Graph Search
Server combines the power of
graph databases and SPARQL
engines with features of
‘traditional’ search engines.
Document search and visual
analytics: Benefit from additional
insights through interactive
visualizations of reports and search
results derived from your data lake
by executing sophisticated SPARQL
queries.
Place your screenshot here
45
Custom Schemes & Ontologies
Entity Extraction
Corpus Analysis
UnifiedViews
SELECTED
VIDEOS
> PoolParty on
YouTube
46
INTEGRATION
WITH MARKLOGIC
Benefiting from a
Full Semantics Stack
47
MarkLogic and
PoolParty
at a Glance
48
YOUR BENEFIT
FULL SEMANTICS
STACK
Semantic Middleware for
Enrichment and Linking
Operational and
Transactional Enterprise
NoSQL Database
Fast Time to Results
Ask Anything Universal Index
Trusted Data and Transactions
Enterprise-Grade Security
Superior user friendliness
+
Semantic as a Service
Standards-based technology
Data Integration
=
Data Enrichment
Intelligent Search
Precise document classification
Scale-Out Commodity Hardware
Graph-based metadata
management
Lightning Fast and Real-Time
Beyond search
Deep Analytics
Data Governance
49
MarkLogic /
PoolParty
Demo
Application
> Try it out!
50
INTEGRATION
WITH VIRTUOSO
Benefiting from a
large-scale RDF Store
51
YOUR BENEFIT
GRAPH BASED
ANALYTICS
Semantic Middleware for
Enrichment and Linking
Native database capability
and a virtual database
Performant SPARQL engine
Massive Linked Data Graphs
Transactions
Scaling to trillions of triples
Superior user friendliness
+
Semantic as a Service
Standards-based technology
Data Integration
=
Data Enrichment
Intelligent Search
Precise document classification
Federated environments
Graph-based metadata
management
Built-in inferencing
Beyond search
Linked Data
Data Virtualization
52
INTEGRATION
WITH A CMS
Benefiting from a
Semantic Layer
53
INTEGRATING
POOLPARTY
ALONGSIDE THE
CONTENT LIFE
CYCLE
54
TWO
INTEGRATION
SCENARIOS
Option 2:
Option 1:
Concepts are derived from taxonomy and
tagging is stored together with the asset in
the DAM/CMS
Concepts are derived from taxonomy, and
tagging event is stored in a Linked Data
Store by tying together assets with
concepts from graph.
DAM/CMS
DAM/CMS
PoolParty
API
PoolParty
API
http://apple.com/graph/1234
http://apple.com/graph/1234
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http://apple.com/macmini.jpg
http://apple.com/macmini.jpg
LD Store
Pool
Party
http://apple.com/graph/1234
User4711
Pool
Party
Wed 3 May, 2017
http://apple.com/macmini.jpg
DAM/CMS
API
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SharePoint
and PoolParty
at a Glance
> Learn more
56
Autotagging &
Consistent
Tagging based on
controlled
vocabularies
57
Semantic Search
for SharePoint
and Office 365
58
USE CASES
Success Stories about SKOS, Linked Data,
and PoolParty Semantic Suite
59
Use Cases for
SKOS, Linked
Data, and for
Vocabulary
Hubs
▸
Climate Tagger (PDF)
Streamline and catalogue data and information resources
▸
CTCN Matchmaking Assistant
Accurate matchmaking between ‘problem statements’ and solution providers
▸
healthdirect Australia (PDF)
Semantic Search based on the Australian Health Thesaurus
▸
Wolters Kluwer (PDF)
Vocabularies as a backbone for enterprise linked data & visualization
▸
Boehringer Ingelheim (PDF)
Vocabularies as means for data integration
▸
A Retailer
Personalization based on controlled vocabularies
▸
Red Bull
Manage over 60 websites with the help of taxonomies
60
Climate
Tagger
Help organizations in the
climate and development
arenas catalogue, categorize,
contextualize, and connect
data and information
resources.
Climate Tagger is backed by
the expansive Climate
Compatible Development
Thesaurus.
http://www.climatetagger.net
Place your screenshot here
61
CTCN
Matchmaking
Controlled vocabularies
enable accurate
matchmaking between
‘problem statements’ and
capabilities of solution
providers.
Matchmaking is based upon
the Climate Compatible
Development Thesaurus.
Reference
Place your screenshot here
62
healthdirect
Australia
Integrated views and
semantic search over more
than 100 trusted sources.
Harmonization of various
metadata systems through
the use of a central
vocabulary hub:
Australian Health Thesaurus.
http://www.healthdirect.gov.au
Place your screenshot here
63
Wolters
Kluwer
Usage of controlled
vocabularies as part of the
semantic search architecture.
Provision of Topics Browser
to navigate topics, relations
and related documents.
Reference
http://vocabulary.
wolterskluwer.de
64
Boehringer
Ingelheim
Data integration based on
controlled vocabularies:
Linking of structured and
unstructured data.
Semantic search and data
analytics based on RDF
graphs and SPARQL.
Reference
Place your screenshot here
65
A Retailer
Controlled vocabularies
enable personalization,
searchability of localized
content, data governance
and standardization.
Personalizing user
experiences with brands and
products is a data driven
task.
See example
Place your screenshot here
66
Red Bull
Manage over 60 websites in a multi-lingual
environment with the help of taxonomies.
19 Mio. hits per day.
All content is linked to the global taxonomy.
All local versions are maintained in specific
taxonomies, which are linked to the global
taxonomy.
Specific menu structures are managed by
skos:Collections
Place your screenshot here
67
Different project stakeholders expect specific
qualities from a semantic technology platform:
SUMMARY
WHY
TAXONOMISTS &
INFORMATION
ARCHITECTS LIKE
POOLPARTY
Read more
I am a taxonomist. I need a tool that
provides convenient functionalities and
intuitive user interfaces for my daily work.
I am an information architect. Enterprise
metadata management deserves scalable
technologies, which provide semantic services
on top of rich APIs based on standards.
68
PoolParty
Academy
Get certified!
https://www.poolparty.biz/academy/
69
GET STARTED
Get your test account at
www.poolparty.biz
70
Andreas Blumauer
CEO, Semantic Web Company
CONNECT
▸
▸
▸
▸
[email protected]
https://www.linkedin.com/in/andreasblumauer
https://twitter.com/semwebcompany
https://ablvienna.wordpress.com/
© Semantic Web Company - http://www.semantic-web.com and http://www.poolparty.biz/
71
Helmut Nagy
COO, Semantic Web Company
CONNECT
▸
▸
▸
▸
[email protected]
https://at.linkedin.com/in/helmutnagy
https://twitter.com/semwebcompany
https://blog.semantic-web.at/
© Semantic Web Company - http://www.semantic-web.com and http://www.poolparty.biz/