How to survive the document & data tsunami? Lambda Verdonckt Business Analyst TenForce

We know how to handle large data, regardless of the technology used. 1

Semantic Technology The only purpose-built technology, to survive a tsunami of doc and data. 2

Semantic Technology Leveraging information in old systems, no need to change current way of working. 3

How did we end up here in the first place?

Semantic Technology Turns the web of documents into a web of data. Turns the web as a virtual library into a virtual database. TenForce applies these technologies in corporate environments.

How to survive the document & data tsunami? Semantic Technology 1.State-of-the-art 2.Examples 3.Future

Semantic Technology The meaning of the data is encoded separately The only purpose-built technology for handling a tsunami of data, in a flexible way. data Software understands the data and can reason about it (JohnDoe, type, Customer) (JohnDoe, owns, Account123) (Account123, type, BankingAccount) model Customer type Person owns Account => ontology, thesaurus, taxonomy etc.

Semantic Technology Standards A set of standards & tools to work with large data sets

Semantic Technology Architectures

TenForce Semantic Offering Consultancy Projects Training Products Semantic Technology  Assesment  Architectures  Modeling  Validation  Standard compliancy Semantic Technology  Assesment  Architectures  Modeling  Validation  Standard compliancy End-to-end projects  mixed teams  research projects  EU framework End-to-end projects  mixed teams  research projects  EU framework Unique Training Offer  Introduction  Modeling  Programming Unique Training Offer  Introduction  Modeling  Programming and many others…

How to survive the document & data tsunami? Semantic Technology 1.State-of-the-art 2.Examples 3.Future

Semantic Technology Solutions The ‘semantic web’ is an application of semantic technology Corporate solutions built with semantic technology include: Knowledge Bases Automatic Categorization & Archiving Natural Language Processing in documents …

Semantic Technology Solutions TenForce projects Publications Office of the EU – a thesaurus of European activities Wolters Kluwer Globally – building a multilingual publishing bus DG Employment of the EC – a taxonomy of European Skills, Competences & Occupations

Semantic Technology Solutions Advanced examples New York Times – automatic categorization & archiving with Linked Data Amdocs – telecom solutions for pro-active decision support Audi – modeling behaviour to make testing less error-prone

How to survive the document & data tsunami? Semantic Technology 1.State-of-the-art 2.Examples 3.Future

Industry Analysts Gartner: high benefit rating (2010) “ Semantic technologies offer … options that now are difficult or impossible “ HP: top 10 trend in BI (2010) “New approaches are needed, and semantic technologies hold part of the solution.”

A vision of the data web LOD2 – a European FP7 project Build the infrastructure for the web of data Opportunities & challenges for all of us!

Future We know the tsunami is coming, the question is – who will be ready to survive?

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BACK-UP SLIDES

Semantic Technology Solutions Knowledge Bases Knowledge is captured in a model, making the DB a KB Allows to manage & share knowledge i.s.o. mere storage >50% of companies indicate the need to share stored knowledge (VALUE-IT) Better & faster retrieval of information for decision support Human-readable: typical CRM with search functionality Machine-readable:expert systems, incl. reasoning eg. clinical decision support  Rules are part of the data, i.s.o. hard-coded: more readily adaptable to changing needs, while interoperable with existing DB’s

Semantic Technology Solutions Automatic Categorization & Archiving Categorization based on controlled vocabularies (taxonomies, thesauri, ontologies)  makes content more searchable: better!  eliminates cost of labour-intensive processes: cheaper! vs. user-driven categorization & tagging (web 2.0) Remark: Look at Evri as an online example!

Semantic Technology Solutions Natural Language Processing Software that analyzes the structure and meaning of textual information analyze texts, identify terms & concepts, extract information, understand meaning  Automatic categorization & archiving based on NLP Tools: Alchemy, OpenCalais, PoolParty

Publications Office of the European Union Cellar, a common portal for all European content & metadata 25

Multilingual publishing system in a EU context for Legal, Tax & Regulatory 2010TenForce26 Wolters Kluwer Global

ESCO, a taxonomy of European Skills, Competences & Occupations 2010TenForce27 DG Employment of the EU Commission

A Semantic Job Portal to leverage the information in ESCO and other information on the web 2010TenForce28 DG Employment of the EU Commission

Advanced examples Publishing New York Times in-house developed vocabulary automatic categorization & archiving published as Linked Data (open to the world!)

Advanced examples Telecom Amdocs Knowing why a customer is calling, saves 3’ per call (or € 0,30)! RDF billing social fora call center logs... advanced inference Pro-active decision support

Advanced examples Manufacturing Audi (Ontoprise) Testing electronic systems in cars using simulations  huge amounts of data are recorded  to be collected and analyzed  time-consuming & error-prone Need for a standardized way to describe desired system behaviour known error-cases Solution: ontology-driven & visualized