Linked Data for the Masses: The approach and the Software

Linked Data for the Masses: The
approach and the Software
G. Anadiotis, P. Andriopoulos, P. Alexopoulos, D.
Vekris, A. Zosakis
IMC Technologies S.A.
ELLAK conference 2010 – 15/5/2010
Licensed under Creative Commons Attribution-
Noncommercial-Share Alike 3.0 Unported License

Linked Data for the Masses 1

Presentation Structure

1. Introduction: From the World Wide Web to the Semantic
Web and Linked Data
2. The Inbound/Outbound Linked Data approach
3. Implementation: Standards and Software
4. Applications and Future Work



Web and Linked Data


WWW Shortcomings

• Lack of structure: Information ≠ Data. The WWW gives
access to information in the form of pages, thus mixing
content with presentation. Data structure is missing,
even if it is in fact available - e.g. the information
presented resides in a Database.
• Lack of semantics: what does this mean? Even if we can
separate presentation from content, there is no way to
interpret the latter: it takes a human to 'understand' the
meaning of the content, thus automatically combining
and processing data on the web is next to impossible.


The Semantic Web

• The goal of dealing with these shortcomings gave birth to the
Semantic Web, which aims to bring elements of Knowledge
Representation and Artificial Intelligence to WWW in order to help it
evolve.


Semantic Web Standards

• XML (eXtended Markup Language) is a
standard for data interoperability on the syntactic level.
• RDF(S). RDF (Resource Description
Framework) is a model to represent classes and their
relationships that can also be represented in XML
notation. RDF Schema defines a set of rules to describe
RDF classes, properties and hierarchies.
• OWL (Web Ontology Language) adds extra
options to RDF(S).
• SPARQL (Simple Protocol and RDF Query
Language) is the equivalent of SQL for querying RDF
data, as well as an access protocol via HTTP.


The RDF Model

• RDF data is different than relational data in their
underlying model: RDF is a graph
• RDF data are expressed as triples
• <subject><predicate><object> : <cat><is-a><mammal>
• RDF(S) provides a first layer of logic: classes and
taxonomical relationships (hierarchy)
• OWL adds options for axiomatic restrictions and
inference


Linked Data

• Linked Data is about using the Web to connect related data that
wasn't previously linked, or using the Web to lower the barriers to
linking data currently linked using other methods
• Sir Tim Berners Lee set the 4 basic principles of Linked Data,
aiming to get ‘the Web done right’.
• Rely on existing standards and 4 basic principles:
1. Use URIs as names for things
2. Use HTTP URIs so that people can look up those names
3. When someone looks up a URI, provide useful information, using the
standards (RDF, SPARQL)
4. Include links to other URIs, so that they can discover more things
• Data structure and semantics specified via vocabularies/ontologies


The Linked Data cloud


DBpedia

• Extracts structured information from Wikipedia and publishes it as
Linked Data.
• Uses an OWL to represent and publish extracted information
– Places
– Person
– Organization
– …
• Provides a SPARQL endpoint to access and query data
• Extracted data stored in a cross-domain knowledge base (479
million RDF triples)
• 2 versions available:
– English
– German



Web and Linked Data


The Inbound/Outbound Linked Data
approach

• How can Linked Data be used in real-world applications?
• Each node/application in the Semantic Web can act as a
Linked Data consumer (Inbound Linked Data) or provider
(Outbound Linked Data), or both
• As a consumer, the benefit is obvious: applications may
tap on a rich web database to enhance content and
provide additional services


approach

• As a provider, the benefits are perhaps less clear, yet definitely
existing:


approach

• The approach was presented in the context of the 2009
Linking Open Data Triplification Challenge, a contest
organized by a group of experts and sponsored by Sir
Tim Berners Lee, aiming to promote adoption of Linked
Data by providing:
– Open Linked Data Datasets
– Opens software that can be used to produce Linked Data

• Outbound Linked Data application: Liferay Linked Data
Module
• Inbound Linked Data application: Tag Disambiguiation



Web and Linked Data


Outbound Linked Data: Liferay Linked
Data Module

• Liferay: open source Portal/CMS framework (Java, Portlet container)
– Over 10 years of development
– Extensive customer base: UN, Cisco, BMW, …


Outbound Linked Data: Liferay Linked
Data Module

• Make Liferay-generated content (blogs, web content,
forums, wikis…) available as Linked Data
• Meta-information: users, groups, organizations, tags..
• SPARQL endpoint.
• Use of open source software: D2R Server + Mapping
language
• Use of standard vocabularies
• Available on Sourceforge, LGPL license


Knowledge Representation Vocabularies

• Using appropriate vocabularies for our content:
– FOAF: Friend-Of-A-Friend
– DC: Dublin Core
– SIOC: Semantically Interlinked Online Communities
– SKOS: Simple Knowledge Organization System
– MOAT: Meaning Of A Tag

• Relying on standard vocabularies promotes
interoperability and enables applications to process
shared data seamlessly.


D2R Server

• Tool and mapping language to map relational databases to
semantic vocabularies and publishing relational data as Linked Data
• RDF data navigation and retrieval
• SPARQL Endpoint
• Mapping Liferay Server database to vocabularies of choice


Inbound Linked Data: Tag
Disambiguation Application

• Developed on Liferay Portal
• Provides a GUI for semantically specifying tag meanings
in their context of use
• Useful for
– Advanced search
– Finding related concepts
– Mapping tags
– …

• Taps on DBpedia, using its concepts and an
asynchronous query and matching mechanism



• New blog entry, adding tag “Apple”



• Interlink Tags
– Finding possible tag meanings
– Letting the user choose one



Web and Linked Data


Applications

• Liferay Linked Data Module is part of IMC Technologies’
eDialogos platform for eParticipation
• Contextual distributed view retrieval application
• Creating a ‘Dialogue ecosystem’
– Transparency - Accessibility: Open data
– Compatibility: Direct access on the data level, removing the need
for proprietary APIs


Extending standards:
eDialogos - eDeliberation Ontology

• Relying on standard vocabularies to create our domain-specific
eParticipation ontology


Dialogue Ecosystem


The Future

• Collaboration with Liferay
– Linked Data Module to be included in the official distribution in
the future
– Consulting with Liferay to include more advanced features

• Collaboration with DBpedia, Greek Universities
– Creation of a Greek DBpedia

• Open sourcing eDialogos
– Timeframe to be established in 2010


References

• [1] Anadiotis, G., Andriopoulos, P., Vekris, D. and Zosakis, A. Linked
data for the masses – using open source infrastructure and the
inbound/outbound linked data approach to bring added value to end
user applications. In I-KNOW 09 and I-SEMANTICS 09, 2009. See
http://i-
semantics.tugraz.at/2009/triplification/04_liferay_TriplificationChalle
nge2009.pdf
• [2] Liferay Linked Data Module:
http://sourceforge.net/projects/liferayldm/
• [3] Bryan Cheung (Liferay CEO), “Liferay Linked Data Module”,
Liferay Blog, December 12, 2009. See
http://www.liferay.com/web/bryan.cheung/blog/-/blogs/liferay-linked-
data-module
• [4] Anadiotis, G., Alexopoulos, P., Mpaslis, K., Zosakis, A.,
Kafentzis, K. and Kotis, K. (2010). Facilitating Dialogue – Using
Semantic Web Technology for eParticipation. Extended Semantic
Web Conference, June 2010, Crete.


Questions

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Linked Data for the Masses: The approach and the Software

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