Abstract. The newly established cluster of excellence COTESYS 1 investigates the realization of cognitive capabilities such as perception, learning, reasoning, planning, and execution for technical systems including humanoid robots, flexible manufacturing systems, and autonomous vehicles. In this paper we describe cognitive technical systems using a sensor-equipped kitchen with a robotic assistant as an example. We will particularly consider the role of Artificial Intelligence in the research enterprise. Key research foci of Artificial Intelligence research in COTESYS include (◦) symbolic representations grounded in perception and action, (◦) first-order probabilistic representations of actions, objects, and situations, (◦) reasoning about objects and situations in the context of everyday manipulation tasks, and (◦) the representation and revision of robot plans for everyday activity. 1

Abstract: Linked Data is as essential for the Semantic Web as hypertext has been for the Web. For this reason, the W3C community project Linking Open Data has been facilitating the transformation of publicly available, open data into Linked Data since 2007. As of 2009, the vast majority of Linked Data is still generated by research communities and institutions. For a successful corporate uptake, we deem it important to have a strong conceptual groundwork, providing the foundation for the development of business cases revolving around the adoption of Linked Data. We therefore present the Linked Data Value Chain, a model that conceptualizes the current Linked Data sphere. The Linked Data Value Chain helps to identify and categorize potential pitfalls which have to be considered by business engineers. We demonstrate this process within a concrete case study involving the BBC.

The service industry has traditionally relied on physical documents to communicate and manage their project and operational activities. As they adopt the object-centric view of Web2.0 technologies in their productivity tools, knowledge-based workers now have to work with interconnected object-centric view of information where they earlier had to deal with only documents created from wordprocessing tools. The paper discusses the new technical and business challenges that must be addressed for making object-centric Web2.0 based tools successful for services.

Abstract: As well as providing various APIs for the development of inference engines and storage models, Jena is widely used in the development of systems or tools related with Web ontology management. However, Jena still has several problems with regard to the development of real applications, one of the most important being that its query processing performance is unacceptable. This paper proposes a storage model to improve the query processing performance of the original Jena storage. The proposed storage model semantically classifies OWL elements, and stores an ontology in separately classified tables according to the classification. In particular, the hierarchical knowledge is managed, which can make the processing performance of inferable queries enhanced and stores information. It enhances the query processing performance by using hierarchical knowledge. For this paper an experimental evaluation was conducted, the results of which showed that the proposed storage model provides a improved performance compared with Jena.

Efficient resource retrieval is a crucial issue, particularly in the context of Semantic Web, since forms of reasoning are used for answering requests. Resources are retrieved by performing a match test between each resource description and the query. This approach becomes inefficient with the increase of available resources. We propose a method for improving the retrieval process by constructing a tree index through a new conceptual clustering method for resources expressed in Web ontology languages. In the index, the available resource descriptions are located at the leaf nodes, while inner nodes represent intensional descriptions (generalizations) of their child nodes. The match process is executed by following the tree branches whose nodes satisfy the query. Query answering time may be strongly improved as the steps may be O(log n).

As we are witnessing a steady increase of semantic content on the Web, there is a (maybe not so obvious) increase in the number of web-applications that are used to produce or consume that content. Protégé offers a great toolset to deal with almost every aspect of authoring and handling ontology based semantic content. Creating easy to use applications that present the power of Protégé in a lightweight and familiar manner, accessible through a web browser has an essential role in spreading the semantic technology. There are a number of tools and frameworks that can help the application developer to rapidly and easily develop such applications. In this paper we will show how we have used the Google Web Toolkit and the Protégé API to build a couple of web applications that provide means to a wide spectrum of users to create, edit and browse biositemaps.