Tackling the Curse of Prepayment – Collaborative Knowledge Formalization Beyond Lightweight Valentin Zacharias 1 , and Simone Braun 1 1 FZI, Research Center for Information Science, Haid-und-Neu Strasse 10-14, 76131 Karlsruhe, Germany {zach, braun}@fzi.de Abstract. This paper argues for collaborative incremental augmentation of text retrieval as an approach that can be used to immediately show the benefits of relatively heavyweight knowledge formalization in the context of Web 2.0 style collaborative knowledge formalization. Such an approach helps to overcome the “Curse of Prepayment”; i.e. the hitherto necessary very large initial investment in formalization tasks before any benefit of Semantic Web technologies is visible. Some initial ideas about the architecture of such a system are presented and it is placed within the overall emerging trend of “people powered search”. Keywords: Semantic Web, collaborative knowledge formalization, web 2.0, Semantic Wikis, People Powered Search 1 Introduction The Curse of Prepayment is the Chicken-Egg problem of Semantic-Technologies: that Semantic technologies promise great functionality only after a large amount of knowledge is formalized. And that no one is willing to invest large amounts of money or time in formalization until the great functionality is visible or at least foreseeable. Recently there has been a great interest in approaches that attempt to tackle this problem by adapting Web 2.0 ideas to make knowledge formalization collaborative, and very easy, cheap, and simple (e.g. [1,2]). In this way these approaches enable end users to successfully contribute to the creation of semantic structures. However, most of these approaches are restricted to very lightweight formalisms – there seems to be a lack of ideas how to extend these approaches to more powerful formalisms. This paper argues that the critical point that stops these approaches from adequately addressing heavyweight formalisms is – again - the Curse of Prepayment: that with these approaches an investment in (more) heavyweight formalization shows no immediate benefit. For example it is trivially possible to edit an OWL Full document in any Wiki by just uploading its XML representation, but there is nothing enabled by the continued development of this document; nowhere is it visible what kind of functionality is made possible by this formalization. We present the “Collaborative Incremental Augmentation of Text Retrieval” as one approach that can be used to tackle this challenge. It stipulates to enable endusers to