Your consultants

Overview &

Applications

Andreas

Welcome!

Helmut Florian

About Semantic Web Company (SWC)

SWC was founded 2001 in Vienna, Austria

Over 20 experts in linked data technologies

Product: PoolParty Suite (launched 2009)

Serving customers from all over the world

EU- & US-based consulting services

Our network: Customers & Partners

Customers

● Credit Suisse

● Daimler

● Roche

● Wolters Kluwer

● Tieto

● Canadian Broadcasting Corporation (CBC)

● World Bank Group

● The Pokémon Company

● Healthdirect Australia

● Ministry of Finance (A)

● Wood Mackenzie

● Red Bull Media House

● Council of the E.U.

● TC Media

● American Physical Society

● Education Services Australia

● Pearson

● Techtarget

● Norwegian Directorate of Immigration

● REEEP

● European Commission

● Bank of America

Finance / Automotive / Publisher / Health Care / Public Administration / Energy / EducationPartners

● Cognizant

● EBCONT

● EPAM Systems

● iQuest

● PwC

● DTI AG

● Tenforce

● OpenLink Software

● Ontotext

● MarkLogic

● Gravity Zero

● Altotech

● Wolters Kluwer

● Term Management

● Taxonomy Strategies

● Search explained

● WAND

● Digirati

● Cognistreamer

● Linked Data Factory

● Taxonic

● semweb

See how it

works...

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 knowledge graphs via API

(Read/Write)

Support of collaborative workflows

around taxonomy management

Extraction of ‘things’ (entities) from

any kind of text based on

knowledge graphs

Extraction of (free) terms from any

kind of text

Categorization of text

Ultra-fast auto completion based

on knowledge graphs

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

Semantic indexing based on URIs,

faceted search based on

taxonomies

Content recommender services

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 foranalyzes

uses API

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

‘Things’ but not strings:

Building a ‘semantic knowledge graph’

http://www.mycom.com/

taxonomy/62346723

prefLabel

Venice

image

http://www.mycom.com/

images/90546089

http://www.mycom.com/

taxonomy/97345854

prefLabel

St. Mark’s

Square

altLabelPiazza

San Marco

http://www.mycom.com/t

axonomy/4543567

prefLabel

altLabel

city squarepiazza

has broader

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

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 from

European countries

Europe

Traditional approach Graph-based approach

Show me all documents

about EU member

countries

doc doc doc

Norway France Austria Canada

The power of knowledge graphs:

Agility, flexibility, complexity

doc doc doc

Europe,

Norway

EU,

Europe,

France

EU,

Europe,

Austria

America,

Canada

doc doc doc doc doc

Show me all

documents from

European countries

Europe

Traditional approach Graph-based approach

Show me all documents

about EU member

countries

EU

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 from

European countries

Europe

Traditional approach Graph-based approach

Show me all

documents about EU

member countries

French-

speaking?

French-

speaking

EU

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 from

European countries

Europe

Traditional approach Graph-based approach

Show me all

documents from EU

member countries

French-

speaking?

French-

speaking

EU

Metadata

per

document

Knowledge

about

metadata

Use Schema.org or other ontologies to

extend your knowledge graph

http://schema.org/City

http://schema.org/TouristAttraction

http://schema.org/ArtGallery

http://www.mycom.com/

taxonomy/62346723

Venice

prefLabel

prefLabel St. Mark’s

Square

http://schema.org/containedIn

http://schema.org/location

Peggy

Guggenheim

Museum

http://www.geonames.org/7302945

http://www.freebase.com/m/0q9rr

http://dbpedia.org/resource/

Peggy_Guggenheim_Collection

https://www.youtube.com/

VeniceGuggenheim

http://www.mycom.com/

taxonomy/5456544

http://www.mycom.com/

taxonomy/7835488

Why it is

useful...

Make use of text corpus analysis

Linking and mapping of vocabularies

and knowledge graphs

including

semi-automatic

batch-linking

of taxonomies

with other taxonomies

or several

knowledge graphs

Use PoolParty PowerTagging to integrate

with Enterprise Content Systems

Confluence

Drupal

SharePoint 2013

Semantic Search in SharePoint 2013 based

on PoolParty PowerTagging

Based on the search enrichment the following features are available:

• Autocomplete• Additional search navigators

based on thesaurus structure• Query expansion

All features can be configured (e.g. number of results for autocomplete)in the search web part configuration.

sOnr webMining for Confluence

sOnr webMining for Drupal

Online-Demos:

http://www.semantic-web.at/marketscan

http://drupal.poolparty.biz/

PoolParty Applications & Demos

Thesaurus Publishing Business Intelligence Content Recommendation Semantic Expert Finder

Web Mining Semantic Search Semantic Tagging in

SharePoint

Symptom Checker

Get started! Try it out now.

Get your PoolParty

Thesaurus Server &

Entity Extractor trial:

http://www.poolparty.biz/test-demo/

Contact points & further informationAndreas Blumauer, MSc IT

a.blumauer@semantic-web.at

https://www.linkedin.com/in/andreasblumauer

Semantic Web Company GmbH

Mariahilfer Strasse 70/8, A-1070 Vienna

+43-1-4021235

http://www.semantic-web.at

http://www.poolparty-software.com

Social Media Channels

http://slideshare.net/semwebcompany

http://youtube.com/semwebcompany

https://www.linkedin.com/groups?home=&gid=4059165

More Details...

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?

PoolParty Semantic Integrator:

Unified Views on various data sources

based on

SKOS as a ‘backbone’ of knowledge graphs

http://www.w3.org/2004/02/skos/

Benefit arguments

Cost effectiveness The systemic viewOperating

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

PoolParty Thesaurus Server

from a taxonomist’s perspective

● Comfortable browser-based

user interface

o drag & drop

o autocomplete

● Rich import/export features

● Built-in corpus management

● Quality management

● Full-blown audit trails & workflow

management

● From simple taxonomies over

thesauri to ontologies

● Linking of taxonomies

● Linked Data interfaces

● Visual Browser

From simple taxonomies (SKOS) to

ontologies: custom schema management

PowerTagging for SharePoint

Technical outline

The PowerTagging integration adds the following features:

• Automatic and manual tagging of SharePoint list items and uploaded documents

• Enrichment of the SharePoint search index based on the tagged content. The search index can be enriched by:

• labels of tagged concepts• relations of tagged concepts and

their labels (top concepts, broader concepts, related concepts)

PoolParty Search Server

Create business dashboards on the fly

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.

PoolParty Visual Mapping

PoolParty API

● navigate a thesaurus (API documentation)

o retrieve schemes of a project

o show top concepts of a scheme

o describe a concept, get all the labels & relations

● search for concepts / autocomplete

o show concepts containing a string

● suggest new concepts

o integrate with a 3rd party content management system

PoolParty API

Text Analytics via REST call or file upload ● API documentation

● Test form

● extract concepts

● categorize text

http://mercury.poolparty.biz/extractor/api/extract?projectId=1DBC62B

E-DB43-0001-279F-15301B94F230&language=en&numberOfTerms=0&text=...

http://mercury.poolparty.biz/extractor/api/categorization?projectId=

1DBC62BE-DB43-0001-279F-

15301B94F230&language=en&numberOfTerms=0&text=...