Semantic Information Management using PoolParty 4

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Information about Semantic Information Management using PoolParty 4

Published on February 28, 2014

Author: MartinKaltenboeck



Presentation by M. Kaltenböck of Semantic Web Company given at the Linked Open Data MeetUp Mannheim on 23 February 2014 on: Semantic Information Management using PoolParty 4 - explaining PoolParty Semantic Suite with features and applications and real world use cases...

PoolParty 4 From Text Mining to Linked Data Martin Kaltenböck CFO, Semantic Web Company @semwebcompany @lod2project

About Semantic Web Company Company was founded 2001 in Vienna, Austria >20 experts in linked data technologies Product: PoolParty Suite (launched 2009) Serving global 500 companies EU- & US-based consulting services

Customers we serve • Pearson • Daimler • Wolters Kluwer • European Commission • TechTarget • Credit Suisse • Wood Mackenzie • Ministry of Finance AT • World Bank • Roche • Council of EU • Education Services AUS Partner Network:

About PoolParty Semantic Suite

PoolParty knowledge modeling process

SKOSsy – Generate Thesauri on the fly LD Harvester in PoolParty SKOSsy Introduction Video 6

User-friendliness Very fast, browser-based, drag & drop, auto-complete, online help,…

Thesaurus Linking Auto-suggest, drag & drop, various mapping properties, various views on mappings

Import / Export Import of Excel, CSV, XML, SKOS/RDF; import and analysis of various text formats, export of various RDF serializations, customised exports for Oracle, SharePoint, etc.

Integrated Quality Management

Integrated Linked Data Harvester

Integrated Text Corpus Analysis

PoolParty PowerTagging PowerTagging works with any version of PoolParty (Basic, Advanced, Enterprise) and can be integrated with your CMS. PoolParty PowerTagging Your PoolParty Server

PowerTagging for SharePoint

PowerTagging for Confluence

PoolParty Semantic Integrator Semantic Search Mashups & 360O views Data Visualisation PoolParty Semantic Integrator Your Linked Data App

Application example #1: Energy Market Intelligence Scenario #1: I am an energy market researcher at the International Energy Agency (IEA). I inform policy makers about the situation in specific renewable energy areas to develop targeted energy support programs. For my research I need indicators about utilisation levels of all alternative forms of energy with regards to geographical and political categories.

How does it work?  Articles about Renewable Energy  72,018 documents  From ~300 web sources  Reegle Thesaurus: ~3,000 concepts  Traverse hierarchies below main categories (wind, solar, etc.) and classify documents  Geonames  Annotate documents with regards to their geographical entities  DBpedia  Lookup several Yago classes to all extracted geographical entities to assert additional categories, e.g.: EU-countries, French-speaking countries etc.

How does it work? Semantic Search Geospatial Search PoolParty Semantic Integrator …. Data Visualisation

Application example #2: Health Care Scenario #2: I am an information officer at the Global Health Observatory of the World Health Organisation. I inform policy makers about the global situation in specific disease areas to direct support to the required health support programs. For my research I need data about disease prevalence in relation to socio-economic factors.

How does it work?  PubMed Articles  Cardiovascular Diseases: 39,911 documents  Neoplasms: 69,937 documents  Nervous System Diseases: 48,128 documents  MeSH: 26,700 concepts / 346,600 triples  Traverse hierarchies below disease main categories and classify documents  Geonames  Annotate documents with regards to their geographical entities  DBpedia  Lookup HDI (The Human Development Index (HDI) is a composite statistic of life expectancy, education, and income indices used to rank countries into four tiers of human development)

How does it work? Semantic Search Geospatial Search PoolParty Semantic Integrator Data Visualisation

Application Scenarios

Example: GBA-Thesaurus

Example: Enterprise Terminology (SharePoint of Roche) List of Synonyms Number of Results Search Phrase Marked Synonyms

Linked data based search Identify ‘hidden’ links and relations between documents, things or persons. Complex queries become possible!

Example: FINDOK (BMF)

Example: Clean Energy Search

Example: Matchmaking EIP on Water Matchmaking based on the Semantic Footprint communication collaboration publishing, edititng, reading, commenting, sharing …

Example: Arbeitsrecht-Thesaurus 50 Billions Facts • • • • EuroVoc Thesaurus Sozial-Wissenschaften DBPedia Standard-Thesaurus Wirtschaft

Example: Education Services Australia

Example: Energy Country Profiles 38

European Data Forum 2014 (EDF2014) 19 – 20 March 2014, Greece Athens Call for Exhibition still open! See: SEMANTICS Conference 4. & 5. September 2014 in Leipzig, Germany September 2015 in Vienna, Austria coming soon !

Contact Martin Kaltenböck CFO, Semantic Web Company +43 1 4021235 These slides are published under : Copyright SWC 2014

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