IINSEMTIVES

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INSEMTIVESIncentives for Semantics
www.insemtives.eu
http://blog.insemtives.eu

Agenda
Idea
What
Why
How
Expected outcomes
Potential impact
Key facts
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Idea
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Realizing the Semantic Web by encouraging millions of end-users to create semantic content.

What
Bridging the gap between human and computational intelligence in semantic content authoring.
Methodologies, methods, tools for the large-scale creation of semantics
Driven by ideas from incentive theory and participatory design.
Optimally combine human input and automatic techniques.
Wide range of content types (text, multimedia, Web services).
Case studies addressing the most important issues of semantic content creation projects.
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Why
More and more information is available on the Web. The information overflow is un-manageable.
Semantic technologies help to make sense of this huge amount of information.
BUT: Many tasks related to semantic content creation are human-driven and can not be carried out automatically.
Limitedinvolvement of users in the Semantic Web.
Incentive structures are not in place for semantic content authoring.

The Web 2.0 experience
Altruism
Reciprocity (tags: Organisation, Reuse)
Reputation
Competition
Belonging to a community, a common goal
Autonomy, freedom
Attracting attention
Self Portaits (Facebook)
Social Component
(Kuznetsov, 2004; Marlow et al, 2006)
The impact of incentives can be exemplified on popular Web 2.0 platforms

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How

How (cont‘d)
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WPs 5-7
WP 8 Dissemination & Exploitation
WP3
WP 9 Management
WP4
WPs 1-2

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Expected outcomes
A unified methodology for authoring semantic data.
Incentive mechanisms for semantic content creation.
Design guidelines for tools.

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Expected outcomes (cont)
Models and methods for the creation of lightweight, structured knowledge.
Bootstraping through the extraction of contextual knowledge.
Converge of semantics.
Linking semantic content.
Semantic search.

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A semantic content management platform for the storage and retrieval of user-generated content, including methods for supporting the lifecycle of this content.

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A toolkit implementing guidelines and incentive mechanisms for ontology development and annotation of different types of media.
Generic games toolkit and games.
Semi-automatic annotation tools.
Bootstrapping tools.
Search and navigation tools.

Expected outcomes: an example
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3 case studies for evaluation of INSEMTIVES technology in real-world settings.
Different types of communities of users.
Different types of information items.
Different types of semantic content.

OKEnterprise
In corporate environments, important information is often lost.
Okenterprise is a social network for corporate knowledge management in Telefonica.
We will apply INSEMTIVES technology to this network in order to generate and share new knowledge among co-workers.
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Virtual worlds
Media producers and companies face the lack of reliable metadata for the huge collections of assets they produce.
In this case study, we will apply incentive methods to the virtual world “Tiny planets” to semi-automate the creation of descriptive metadata.
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Web service annotation
The lack of rich descriptions beyond their current syntactical interface hampers the automatic retrieval of Web services on the Internet.
The case study will apply INSEMTIVES technology to facilitate user-provided annotation of Web services.
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Potential impact
Massive amounts of useful semantic content which can enable the uptake of semantic technology through the development of application producing real added value for the Semantic Web and for industrial adopters.
Production of digital resources easier and more cost-effective
Enhanced search of digital resources
Case studies solving real world problems
PGP: multimedia annotation
Seekda: annotation of Web services
Telefonica: semantically enhanced corporate knowledge management

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Potential impact: the same example
50 users playing games 24/7 for 6 months.
216,000 hours (50 * 24 * 180), hourly rates of 10€ 2 million € investment.
4 modeling decisions per 2 minutes game  12 milion modeling decisions in 6 months (216,000 * 60 = 12,960,000).

Key facts
2009 – 2012
Budget: 4.3 MEuro
7 Partners
STI Innsbruck, University Innsbruck, Austria
University of Trento, Italy
Peppersghost Productions, UK
Telefonica, Spain
Seekda, Austria
OntoText, Bulgaria
University of Siegen, Germany
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INSEMTIVESIncentives for Semantics
www.insemtives.eu
http://blog.insemtives.eu