This article presents YAGO, a large ontology with high coverage and precision. YAGO has been automatically derived from Wikipedia and WordNet. It comprises entities and relations, and currently contains more than 1.7 million entities and 15 million facts. These include the taxonomic Is-A hierarchy as well as semantic relations between entities. The facts for YAGO have been extracted from the category system and the infoboxes of Wikipedia and have been combined with taxonomic relations from WordNet. Type checking techniques help us keep YAGO’s precision at 95% – as proven by an extensive evaluation study. YAGO is based on a clean logical model with a decidable consistency. Furthermore, it allows representing n-ary relations in a natural way while maintaining compatibility with RDFS. A powerful query model facilitates access to YAGO’s data.

We introduce Cimple, a joint project between the University of Illinois and the University of Wisconsin. Cimple aims to develop a software platform that can be rapidly deployed and customized to manage data-rich online communities. We first describe the envisioned working of such a software platform and our prototype, DBLife, which is a community portal being developed for the database research community. We then describe the technical challenges in Cimple and our solution approach. Finally, we discuss managing uncertainty and provenance, a crucial task in making our software platform practical. 1

Abstract. This paper presents the vision and results of creating a national level cross-domain ontology and ontology service infrastructure in Finland. The novelty of the infrastructure is based on two ideas. First, a system of open source core ontologies is being developed by transforming thesauri into mutually aligned lightweight ontologies, including a large top ontology that is extended by various domain specific ontologies. Second, the ONKI Ontology Server framework for publishing ontologies as ready to use services has been designed and implemented. ONKI provides legacy and other applications with ready to use functionalities for using ontologies on the HTML level by Ajax and semantic widgets. The idea is to use ONKI for creating mash-up applications in a way analogous to using Google or Yahoo Maps, but in our case external applications are mashed-up with ontology support. 1 A National Ontology Infrastructure The ambitious goal of the National Semantic Web Ontology project (FinnONTO 2003–2007) 1 [1] is to develop a semantic web infrastructure on a national level in Finland. The consortium behind the initiative—37 companies and public organizations—represents a wide spectrum of functions of the society, including libraries, health organizations, cultural institutions, government, media, and education. The project has produced a variety of scientific results, specifications, services, demonstrations, and applications: 1. Metadata standards. Nationally adapted standards for representing metadata in various application fields have been created, e.g. JHS 158 2 and [2]. 2. Core ontologies. Several core ontologies 3 have been developed in order to initiate ontology development processes in Finland.

Collaborative ontology building requires both knowledge integration and knowledge reconciliation. Wiki@nt is an ontology building environment that supports collaborative ontology development. Wiki@nt is based on an extension to with (partial order on axioms) and (localized axioms in package ) constructors. Wiki@nt supports integration and reconciliation of multiple independently developed, semantically heterogeneous, and very likely inconsistent ontology modules. A web browser based editor interface is provided, with features to support team work, version control, page locking, and navigation.

We present a national ontology development and service framework being developed in Finland in 2003-2007. The framework is based on a set of related core ontologies, most notably on a national upper ontology based on the commonly used Finnish General Thesaurus YSA maintained by the National Library of Finland. The framework implements three ontology services by a web-based system ONKI. Firstly, ONKI supports distributed collaborative development and versioning of interdependent ontologies. Secondly, external cataloging and indexing systems can use ONKI as a web service for ontology-based annotations. Thirdly, information retrieval systems can use ONKI for disambiguating keyword meanings for concept-based search on the Semantic Web.

In peer-to-peer inference systems, each peer can reason locally but also solicit some of its acquaintances, sharing part of its vocabulary. This paper studies both theoretically and experimentally the problem of computing proper prime implicates for propositional peer-to-peer systems, the global theory (union of all peer theories) of which is not known (as opposed to partition-based reasoning). 1

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The Semantic Web vision of a next generation Web, in which machines are enabled to understand the meaning of information in order to better interoperate and better support humans in carrying out their tasks, is very appealing and fosters the imagination of smarter applications that can retrieve, process and present information in enhanced ways. In this vision, a particular attention should be devoted to personalization: By bringing the user's needs into the center of interaction processes, personalized Web systems overcome the one-size-fits-all paradigm and provide individually optimized access to Web data and information. In this paper, we provide an overview of recent trends for establishing personalization on the Semantic Web: Based on a discussion on reasoning with rule- and query languages for the Semantic Web, we outline an architecture for service-based personalization, and show results in personalizing Web applications.

In the last years, ontologies have played a major role for building large, distributed, and heterogeneous intelligent systems. E.g., ontologies are one key technique of the semantic web layer. The development process of an ontology heavily depends on its evaluation. In this paper, we introduce several measures for the evaluation of ontological knowledge. Besides standard methods like taxonomic errors we also present novel metrics focusing on design anomalies. For the implementation of these measures we propose a declarative approach using the logic-based language FNQuery.

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