INSEMTIVES is a FP7 collaborative project funded by through the grant number FP7-231181 under EU Objective 4.3. It brings together program computer scientists, software engineers, economists, social scientists and end-users from six European countries, coordinated by STI Innsbruck. INSEMTIVES is about bridging the gap between human and computational intelligence and providing incentives for users to contribute to the massive creation of semantic content.

1. 11/10/2009 www.insemtives.eu 1 INSEMTIVESIncentives for Semantics www.insemtives.eu http://blog.insemtives.eu

2. Agenda Idea What Why How Expected outcomes Potential impact Key facts 11/10/2009 www.insemtives.eu 2

3. Idea 11/10/2009 www.insemtives.eu 3 Realizing the Semantic Web by encouraging millions of end-users to create semantic content.

4. 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. 11/10/2009 www.insemtives.eu 4

5. 11/10/2009 www.insemtives.eu 5 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.

6. 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

7. 11/10/2009 www.insemtives.eu 7 How

8. How (cont‘d) 11/10/2009 www.insemtives.eu 8 WPs 5-7 WP 8 Dissemination & Exploitation WP3 WP 9 Management WP4 WPs 1-2

9. 11/10/2009 www.insemtives.eu 9 Expected outcomes A unified methodology for authoring semantic data. Incentive mechanisms for semantic content creation. Design guidelines for tools.

10. 11/10/2009 www.insemtives.eu 10 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.

11. 11/10/2009 www.insemtives.eu 11 Expected outcomes (cont) A semantic content management platform for the storage and retrieval of user-generated content, including methods for supporting the lifecycle of this content.

12. 11/10/2009 www.insemtives.eu 12 Expected outcomes (cont) 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.

13. Expected outcomes: an example 11/10/2009 www.insemtives.eu 13

14. 11/10/2009 www.insemtives.eu 14 Expected outcomes (cont) 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.

15. 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. 11/10/2009 www.insemtives.eu 15

16. 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. 11/10/2009 www.insemtives.eu 16

17. 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. 11/10/2009 www.insemtives.eu 17

18. 11/10/2009 www.insemtives.eu 18 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

19. 11/10/2009 www.insemtives.eu 19 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).

20. 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 11/10/2009 www.insemtives.eu 20

21. 11/10/2009 www.insemtives.eu 21 INSEMTIVESIncentives for Semantics www.insemtives.eu http://blog.insemtives.eu