1 Growing the Semantic Web with Inverse Semantic Search Hans-Jörg Happel, FZI Karlsruhe 1st Workshop on Incentives for the Semantic Web (INSEMTIVE 2008) at ISWC 2008, Karlsruhe, Germany, October 26 th, 2008

2 The Basis  Metadata (and structured data) are useful for a lot of fancy things Many kinds of search and retrieval tasks „Task automation“ on the Semantic Web  „Metadata“ can be „created“ in various ways Exposure of existing structured data (e.g. DBPedia) (Semi-)Automatic metadata creation Human metadata creation (e.g. tagging, annotations)  Access to metadata might be restricted Different spheres of sharing (private, friends, world…) – even in Web 2.0 applications (e.g. Flickr, del.icio.us) Growing the Semantic Web with Inverse Semantic Search 2

3 The Problem  So metadata is a nice thing…but… Metadata creation is costly Metadata creation is decoupled from metadata use (concerning time and actors)  No unified theory, why metadata is created and how it is shared SemWeb Vision does not address the creator side of metadata – it spends a lot of effort to convince people using the Semantic Web but not contributing to it  Research questions How can individuals be guided to create the right metadata? How can individuals be motivated to create this metadata? Growing the Semantic Web with Inverse Semantic Search 3

4 Individual‘s incentives and disincentives for contributions  (Photo) tagging systems Personal and social benefit (organizational, functional) [1, 2, 3]  (Movie) rating systems Uniqueness of contribution and goal setting [4] Value and relationships [5]  General knowledge management Lack of personal benefit [6, 7, 8] Privacy (expose information or expertise) [9, 10] Effort (cost of knowledge capturing, categorization and setting access rights) [10, 11] Growing the Semantic Web with Inverse Semantic Search 4

5 mentionedIn(Casablanca, Paris) mentionedIn(Casablanca, ?x) actsIn(Casablanca, Borgart) The Idea (1) Growing the Semantic Web with Inverse Semantic Search Metadata creator Metadata user Evolution of the Semantic Web + + ? ? HOW IT WORKS NOW Metadata creatorMetadata user Evolution of the Semantic Web + + ? ? INVERSE SEM. SEARCH ? ? „Search“ leads to importing metadata from the Semantic Web to the private space of the user „Inverse Search“ leads to contributing metadata to the public Semantic Web 5 ! !

6 The Idea (2)  Inverse Semantic Search means Share semantic queries instead of metadata (to preserve data privacy) Derive an aggregated information need from the semantic queries of a community (to lower cost) Display/use aggregated information need to acquire/share metadata in a focussed and selective way (to raise motivation)  Initial concept lined out in the papers leaves further questions Work with more complex semantic queries Proper heuristics for deriving unsatisfied information needs Applying reasoning to aggregate information needs Embed principle in concrete application designs Growing the Semantic Web with Inverse Semantic Search 6

7 Summary  How can individuals be guided to create the right metadata? Try to predict which metadata could be useful in the future Inverse search as a meachnism to use semantic query logs for that purpose  How can individuals be motivated to create this metadata? Address feedback channels and easy sharing facilities in application design Nice UIs with context-specific need representations („What is missing?“) Growing the Semantic Web with Inverse Semantic Search 7

8 The End  Thanks for your attention!  Any questions?  Further reading Happel, H.-J., Stojanovic, L.: Analyzing organizational information gaps. In: I-Know08: Proceedings of 8rd International Conference on Knowledge Management. (2008) Happel, H.-J.: Closing Information Gaps with Inverse Search. In Proceedings of the 7th International Conference on Practical Aspects of Knowledge Management (PAKM2008) (to appear) Growing the Semantic Web with Inverse Semantic Search Hans-Jörg Happel FZI Forschungszentrum Informatik Karlsruhe, Germany

9 Cited Literature [1] Ames, M., Naaman, M.: Why we tag: motivations for annotation in mobile and online media. In: CHI ’07: Proceedings of the SIGCHI conference on Human factors in computing systems, New York, NY, USA, ACM (2007) 971–980 [2] Kustanowitz, J., Shneiderman, B.: Motivating annotation for personal digital photo libraries: Lowering barriers while raising incentives. Technical Report HCIL , University of Maryland, College Park, MD, USA ( ) [3] Marlow, C., Naaman, M., Boyd, D., Davis, M.: Ht06, tagging paper, taxonomy, flickr, academic article, to read. In: HYPERTEXT ’06: Proceedings of the seventeenth conference on Hypertext and hypermedia, New York, NY, USA, ACM 2006) 31–40 [4] Beenen, G., Ling, K., Wang, X., Chang, K., Frankowski, D., Resnick, P., Kraut, R.E.: Using social psychology to motivate contributions to online communities. In: CSCW ’04: Proceedings of the 2004 ACM conference on Computer supported cooperative work, New York, NY, USA, ACM (2004) 212–221 [5] Rashid, A.M., Ling, K., Tassone, R.D., Resnick, P., Kraut, R., Riedl, J.: Motivating participation by displaying the value of contribution. In: CHI ’06: Proceedings of the SIGCHI conference on Human Factors in computing systems, New York, NY, USA, ACM (2006) 955–958 [6] Angel Cabrera and Elizabeth F. Cabrera. Knowledge-sharing dilemmas. Organization Studies, 23:687–710, [7] Ulrike Cress and Friedrich-Wilhelm Hesse. Knowledge sharing in groups: experimental findings of how to overcome a social dilemma. In ICLS ’04: Proceedings of the 6th international conference on Learning sciences, pages 150–157. International Society of the Learning Sciences, [8] Molly McLure Wasko and Samer Faraj. Why should i share? examining social capital and knowledge contribution in electronic networks of practice. MIS Quarterly, 29(1):35–57, [9] Alexander Ardichvili, Vaughn Page, and Tim Wentling. Motivation and barriers to participation in virtual knowledge- sharing communities of practice. Journal of Knowledge Management, 7(1):64–77, [10] Kevin C. Desouza. Barriers to effective use of knowledge management systems in software engineering. Commun. ACM, 46(1):99–101, [11] Kevin C. Desouza and J. Roberto Evaristo. Managing knowledge in distributed projects. Commun. ACM, 47(4):87– 91, Growing the Semantic Web with Inverse Semantic Search 9

10 Metadata gaps Growing the Semantic Web with Inverse Semantic Search 10

11 Types of queries Growing the Semantic Web with Inverse Semantic Search 11

12 Simple semantic query log Growing the Semantic Web with Inverse Semantic Search 12

13 High-level architecture & UI (for keyword-based Inverse Search) Server Clients Growing the Semantic Web with Inverse Semantic Search 13

14 Inverse search (process perspective) Growing the Semantic Web with Inverse Semantic Search 14