Smart Enterprises

DI Georg Güntner

Smart Enterprises
Successful implementation of semantic technologies in enterprises

Abstract

 Smart Enterprises
Successful implementation of semantic technologies in enterprises

The technologies of the “Web od Data” have reached a degree of maturity and acceptance
allowing the productive use in enterprises for the support of their business processes. Though the
focus is currently on the adoption and use of Open (Linked) Data, the underlying principles can
also be applied to the closed data sources and proprietary data structures usually available in
enterprises.
The presentation outlines the basics and shows concrete application scenarios of an open source
“semantic toolset” that can be integrated with enterprise information and content management
systems to open data silos, establish a layer of adaptive integrated views of the enterprise
information and support decision processes thus paving the way to an “open semantic enterprise”.
The topical semantic toolset for enterprise content integration includes Apache Stanbol (knowledge
extraction), the Linked Media Framework (networked knowledge) und VIE (interactive knowledge).
We show practical examples for the use of the toolset in concrete enterprise application scenarios

 Georg Güntner, I-Praxis, 06.09.2012, 14:45

© 06.09.2012 i-Praxis "Smart Enterprises" (G. Güntner) 2

Salzburg Research

 Salzburg Research was founded in 1996 as the research organisation of the
Province of Salzburg (www.salzburgresearch.at)
 Salzburg Research is located at Techno-Z Salzburg and conducts applied research
and development in the area of information and communication technologies (ICT)
 Salzburg Research employs about 70 researchers and has a turnover of about 4,8
million €
 Research areas
 Knowledge and media technologies
 Computational logistics
 Spatial-temporal data mining,
quality aspects in the area of geographic
information (GI), GI software technologies
 Research and consulting in early phases of
innovation management
 IT- security and QoS networks
 Salzburg NewMediaLab – The Next
Generation (COMET)
 The core activities comprise applied research, technological and methodological
support, co-ordination and networking, know how transfer and scientific studies.


Guide through the Presentation

 Semantic technologies in the enterprises:
Case studies and use cases
 Abstract problem definition: the „Smart Enterprise“ vision
 Toolset for Smart Enterprises
 Knowledge Extraction
 Networked Knowledge
 Knowledge Interactivation
 Solutions
 „Wings for the Red Bull Content Pool“
 „News and Information Platform”
 Conclusions


Semantic Technologies in the Enterprise

 Various applications (not restricted to enterprise sector)
are listed, e.g. in the directory of „Semantic Web Case
Studies and Use Cases” at
http://www.w3.org/2001/sw/sweo/public/UseCases/
 Sectors:
 automotive (2), broadcasting (2), energy (3), IT industry (5), oil & gas (3),
publishing (4), telecommunications (4), utilities (1) (out of totally 46 entries
as of Sep. 2012)
 Some examples:
 Contextual Search for Volkswagen and the Automotive Industry (Link)
 How Ontologies and Rules Help to Advance Automobile Development
(use case at AUDI) (Link)
 Semantic Web Technologies in Automotive Repair and Diagnostic (use
case at Renault) (Link)
 Active Knowledge Management for Integrated Operations (use case at
Statoil) (Link)
 B2B Integration with Semantic Mediation (use case at BT Research) (Link)
 WEASEL: Corporate Semantic Web (use case by Vodafone R&D) (Link)



 Exploitation scenarios in “Salzburg NewMediaLab – The
Next Generation” (SNML-TNG), a centre of excellent
technologies in the COMET programme
(www.newmedialabn.at, labs.newmedialab.at)
 Some examples:
 Concept based annotation in the ORF media archive (see demo
session)
 Semantic search and annotation of media fragments in the Red
Bull Content Pool
 Search and recommendation in a heterogeneous content pool at
Salzburger Nachrichten
 Enterprise search at Salzburg AG
 Search and recommendation in a job portal at derStandard.at



 Interactive Knowledge Stack (IKS) is an open source
community, whose projects are focused on building an
open and flexible technology platform for semantically
enhanced Content Management Systems (CMS)
www.iks-project.eu
 Some examples of Stanbol adoption and integration:
 Drupal: Stanbol plug-in; on-going: discussion to use VIE
(createjs) in the user interface
 Alfresco: Storage of content enhancements for semantic
search
 GOSS iCM: data exploration (navigation, browsing) in the
e-government domain
 Nuxeo: Stanbol integration and topic categorisation for the
news domain
 Searchbox Demo: Deep integration of IKS stack
 Wordpress: Semantic word lift (semantic SEO)



 Demonstrations shown in the i-Praxis Track
 Linked Enterprise Data with the PoolParty Framework (Semantic Web Company)
 Semantic Web for Legal Publishers (Wolters Kluwer)
 Connect your cloud apps … in style (Gnowsis)
 Corporate Semantic Web Day
 Berlin, 10.9.2012: at Xinnovations 2012
http://www.xinnovations.de/programm-montag-10.09.2012.html
 Further applications
 Application of semantic technologies in a network centred approach for corporate
knowledge management: “TechnoWeb 2.0” (Siemens)
http://www.e20cases.org/fallstudie/siemens-wissensvernetzung-mit-technoweb-2-0/
(German)


Smart Enterprise
A Vision for Data Integration Derived from the WWW

Attribution:


Implementation of the Vision in Enterprises

Institutional “Content Silos” Trusted Content Providers
Media- and document archives Partner organisations
Web content (Wikis, Blogs) Syndication, RSS-Feeds
Newsgroups, eMails Agencies
Web Content
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Knowledge Space Communities
Linked Data, Open Data, Customers, subscribers, employees, prosumers
Taxonomies


What Makes up a Smart Enterprise?

 Characteristics of a type of enterprise that uses the concepts of interlinking
at various levels to optimize their business processes:
 Operating heterogeneous information systems (loosely coupled, if at all; distinct information
silos)
 Storage and management of huge amounts of structured and unstructured digital
information increasingly including media assets
 Operating in an agile environment with ever
changing data schemas for structured information
resources
 Data sources not only interlinked among themselves,
but also with external information pools.
 Smart Enterprises develop policies for
linking their internal information and media
resources with trusted external knowledge bases
and for opening part of their information resources
to the public.

©

Abstract Task of Information Management
in Smart Enterprises

 Given: heterogeneous, incomplete
datasets with different formats and data
models

 Required: unified data representation
with connected datasets, with context
information from the domain and with
additional information from the Web

© 06.09.2012 12

Toolset for Smart Enterprises (1)

 The „Toolset“ for Smart Enterprises comprises Open Source tools and
frameworks, that can easily be integrated into existing applications
without replacing them

 Knowledge Extraction (Apache Stanbol)
 Natural language processing (NLP)
 Entity linking und disambiguation
 Content classification
 Metadata extraction
 Networked Knowledge (Linked Media Framework)
 Implementing the Read-/Write-Webs
based on the Linked Data Principles
 Data Federation
 Caching
 Versioning
 Reasoning


Toolset for Smart Enterprises (2)

 The „Toolset“ for Smart Enterprises comprises Open Source tools and
frameworks, that can easily be integrated into existing applications
without replacing them

 Knowledge (Inter-)Activation (VIE)
 Decoupling of the CMS and the semantic interaction
 Semantic content editing
 Knowledge based navigation
 Semantic search

 Open Source: Apache License 2.0 (permissive)


Knowledge Extraction (Apache Stanbol)

 Support for NLP techniques like Named Entity
Recognition, POS Tagging, key phrase Extraction, etc.
 Support for automatic interlinking of content with
Linked Data concepts
 Support for statistical text classification, allows to train different classifiers
with sample texts for arbitrary categories
 Suggest most likely category for a text according to similarity with training
data
 Analyse text for positive or negative sentiment (German and English)

© 15

Invitation to the IKS Early Adopter Programme

www.iks-project.eu

 The Early Adopter Programme allows CMS-vendors and system
integrators to validate the software components if the IKS stack.
 Please consult us at the IKS booth in the exhibition area.
 Examples for demonstrators and solutions developed in the Early
Adopter Programme: Drupal, OpenSaga, Alfresco, Plone,
Searchbox, Wordpress,

Cf. http://www.iks-project.eu/community/funding/early-adopters-programme


Networked Knowledge (Linked Media Framework)

 The Linked Media Framework provides an enterprise information
integration platform based on an extension of the Linked Data
principles aiming at the unified management, integration, interlinking
and processing of information resources in the enterprise or from
Web data sources.

 Available under Apache license 2.0 at www.newmedialab.at/LMF,
coming along with a one-click-installer and a profound
documentation

©

The Linked Media Principles

 The Linked Media Principles extend the Linked Data
approach in answer to the following challenges:
 Linked Data is „read-only“
 The Linked Media principles extend Linked Data with updates by using
the REST Web services approach (GET, POST, PUT, DELETE)
 Realizing (part of) recent W3C notes on “Read Write Web of Data”
(http://www.w3c.org/wiki/WriteWebOfData)
 Linked Data is “data-only”
 Linked Media principles extend Linked Data with any media format based
on MIME thus allowing handling of content and metadata in a uniform way

©

Linked Media Framework
Functionalities / Features

 Linked Data Server
with updates, transactions, versioning and SPARQL 1.1 endpoint
 Easy to set up in 15 minutes (“1-click-installer”)
 Unified management of content and metadata
 Linked Data Client and transparent caching
 Direct access, cache server, SPARQL 1.1 endpoints
 Automatic retrieval when additional data is required
 Rule-based reasoning engine with reason maintenance
 User-defined rules allow customization
 Justifications can give explanations to users
 Semantic Search component
 Making use of Linked Data properties
 Highly customizable through “search programs”
 Integration with SKOS Managers (PoolParty, SKOSjs)
 Integration with Google Refine (google-refine.googlecode.com)
 Integration with Apache Stanbol (incubator.apache.org/stanbol/)

©

Applications and Use Cases


Scenario: „Wings for the Red Bull Content Pool“

 Search and display of semantically enhanced video fragments

 Information from various enterprise databases Technologies and concepts
 Resource Description Framework (RDF)
 Ontology for Media Resources
 Media Fragments URI
 SPARQL 1.1 Query Language
 HTML 5



 Source material: videos and text transcripts
(terminology „concepts“ are manually marked in the screenshot below)



 Content Enhancement with Apache Stanbol



 Structured metadata in the LMF
 Semantic search and navigation



 HTML5-Player for video fragments (temporal, spacial)
 Time code synchronized visualisation of concepts („catamaran“)



 Annotation with concepts from the „Web of Data“ (DBpedia)
 Interactive extension of the „knowledge base“


Scenario: News and Information Platform

 Requirements: Stable and performant backbone for the semantic
search in a regional news service; content enhancement; content
recommendation; integration and interlinking of distinct information
sources (articles, wiki pages, blog entries, comments, photos,
videos)
 Content basis:
 ~800.000 articles
 50.000 videos and photos
 300.000 blog entries and comments
 14.000 wiki pages

©

Scenario: Semantic Search over News Content

 News content from daily newspaper News
and online news, community content Articles
from blogs and wiki
Blogs
Semantic
Search
Videos
 Semantic search over different
types of content from different
sources
 Facetting over metadata that Wiki
is relevant in the news domain
(location, time, category, persons)
 Shows how the LMF as core technology Text Analysis
(Interlinking,
can be used to set up a ready-to-use
Annotation)
semantic search over heterogeneous
sources in short time.

©

Scenario: News Content Recommendation

Content
recommendations
based on the
semantic index in
LMF
www.salzburg.com


Scenario: Search for Related Images

 VIE Integration Widget for tinyMCE for the search of
related images (Alkacon Software GmbH)

Cf. http://alkacon.github.com/vie-related/


Scenario: Annotation and Search

Goal is to simplify
the annotation for
editors and
archivists at the
Austrian Broad-
casting Corporation
(ORF) by linking
with concepts from
a thesaurus and
the Linked Data
Cloud.

©

Conclusions: Foundations of Smart Enterprises

 Sven pillars for Smart Enterprises
(cf. „Open Semantic Enterprise“, Michael K. Bergman)

 Graph-based data model (RDF)
 (Open) Linked Data technologies
 Adaptive ontologies
 Ontology-driven applications
 Web-oriented architecture
(from linked documents
to linked data)
 Layered approach
 Open World Mindset

Cf. www.mkbergman.com/859/seven-pillars-of-the-open-semantic-enterprise


Smart Enterprise: Content Integration Workflow

• The Content Management Systems provide data in
Content Ingest various formats (CSV, XML or RSS-feeds)

Content Integration • Normalisation of the content (conversion to RDF)
• Integration of the content of different systems

Content Enhancement • Enhancement of the content (interlining with internal and
external information sources)

Semantic Search • Creation of the search index
• Support for the search interface

Content
• Recommendation of related content
Recommendation

Administration • Administrative interface (update, delete, weights, „boost“:
configuring the relevance)

©

Process View: Linked Media Life Cycle

• Plan
• Create
• Acquire
Creation

• Organize
• Produce
• Compose
• Maintain
• Enrich
Management • Store

• Sell
• Distribute
• Publish
• Deliver
• Involve
Transaction • Interact
© B. Smith - Media Life Cycle and Metadata

©

References

 IKS-Projekt (EU FP7 – Integrated Project)
 Website: www.iks-project.eu
 Demos: www.iks-project.eu/Demos
 Salzburg NewMediaLab – The Next Generation (K-Projekt)
 Website: www.newmedialab.at
 Labs (Demo-Bereich): labs.newmedialab.at
 Apache Stanbol
 Project Repository: incubator.apache.org/stanbol/
 Linked Media Framework
 Linked Media Principles: www.newmewdialab.at/LinkedMediaPrinciples
 Google Code-Repository: www.newmewdialab.at/LMF, lmf.googlecode.com
 LMF demo: labs.newmedialab.at/DEMO
 VIE
 Project Repository: viejs.org
 Weitere Technologien
 PoolParty: www.poolparty.biz
 LD-Path: www.newmedialab.at/LDPath, code.google.com/p/ldpath/
 Apache Solr: lucene.apache.org/solr/
 Weitere Information
 Open Semantic Enterprise: www.mkbergman.com/859/seven-pillars-of-the-open-semantic-enterprise


Please visit us at the IKS booth
in the exhibition area!
See also the demos
Interlinking Media Archives with the Web of Data
ConnectME: Semantic Tools for Enriching Online Video with Web Content

DI Georg Güntner
Head of Salzburg NewMediaLab – The Next Generation
Salzburg Research Forschungsgesellschaft m.b.H.
Jakob-Haringer-Straße 5/3 | Salzburg, Austria
Tel. +43 662 2288-401 | Fax +43 662 2288-222
georg.guentner@salzburgresearch.at

©

Smart Enterprises

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