The vision of TRANSPARENCY is to allow European machine-tool builders for transferring their business into a machine-related cooperation of service oriented partners in a dynamic network. The project aims for a vertical integration of management, design and operation of machine-tools to provide long-ranging transparency for both the end users and the machine-tool builder throughout the whole life-time of the machine-tool. This is achieved by a knowledge based Collaborative Co-Design Environment approach using semantic technologies. Special attention will be paid for the conceptual system design stage, the feed-back of knowledge from the operational life-cycle stages. Life-cycle performance, knowledge about produced products, and experiences of human personnel will be constantly incorporated into the set of knowledge. Handling of complexity will be achieved by self-descriptive Active components and the realization of a flexible, knowledge based Co-Design Methodology.

Advanced assessment and prediction tools with links to commercial of the shelf simulations will assess important key performance indicators to execute virtual test cases to support especially early design decisions. This will drastically reduce costly re-design cycles in detailed design. Furthermore, the continuous availability of dynamically assessed Life-Cycle Costing data will allow for constant total life cycle cost optimization of the machine-tool and its components. Via web-based collaboration and secure storage of data, the project will ensure that every responsible stakeholder will have access to all information available throughout the whole life-time of the product and towards the re-use or disposal of the machine-tool or its components.  

 
For further information please see our flyer or visit www.transparency-project.eu.

FRAME (Fast Ramp Up and Adaptive Manufacturing Environment) aims to create a new solution for highly adaptive, self-aware assembly systems, which will use automated self-learning, dynamic knowledge sharing, highly integrated sensor networks and innovative human-machine interaction mechanisms. These next generation assembly systems equipped with FRAME technology will be able to proactively support ramp-up, error recovery and operational performance improvement.  This will lead to a dramatic cost and time reduction of deploying and maintaining complex assembly systems on demand and improve their effectiveness.

FRAME is funded by the EU 7th Framework Programme.

For further information about FRAME please visit www.frame-eu.org.

Interactive Diagnosis and Resolution for Semantic Data Integration

MappingAssistant is a joint research project of ontoprise and the Knowledge Representation and Knowledge Management Group at the University of Mannheim, which is focused on developing methods and tools for instance-based diagnosis and correction of mapping rules in the semantic data integration process. The project is funded by the German Federal Ministry of Education and Research (BMBF) and is supervised by Germany's national research center for aeronautics and space (DLR).

The MappingAssistant tools support the evaluation of existing mappings between ontologies. The mappings may be the result of a manual alignment process or the result of an automated ontology matching algorithm. Alignments produced by automated ontology matching algorithms are especially error-prone, but errors may occur also if a matching is done manually by a technical expert with insufficient domain expertise. Consequently, matching results need to be supervised by a human domain expert. As they are usually represented in ways only technical experts can deal with, the evaluation task is complicated and time-consuming. The MappingAssistant simplifies the alignment evaluation process by decreasing the amount of user interactions needed to correct the automatically generated mapping results. In particular, we developed a user-friendly conflict resolution method utilizing data reduction techniques for illustrating representative individuals and an algorithm for minimizing user interaction in the evaluation process of aligned data. In order to avoid overwhelming the user by presenting him thousands of individuals, we used a combination of clustering algorithms for data simplification.

The MappingAssistant Diagnosis Component has been implemented as an add-on to the ontoprise OntoStudio MappingEditor and is based on the OntoStudio and Eclipse framework. Its main feature is an interactive process for detection of incorrect mapping rules. An intuitive and user-friendly visualization of mapping rules and error reasons supports the user in the task of understanding and correcting the mapping rules.

The MappingAssistant Recommendation Component will assist users with recommendations for feasible mapping rules, which he may accept or reject. Currently, we are evaluating ILP (Inductive Logic Programming) methods and tools for the task of learning complex logical mappings.

For more details see the abstract of the poster we presented at the ESWC 2011 [MappingAssistant: Interactive Conflict-Resolution for Data Integration] or contact us.

ONTORULE (ONTOlogies meet business RULEs) is a large-scale integrating project (IP) partially funded by the European Union's 7th Framework Programmen under the Information and Communication Technologies (ICT) Call 3 (ICT-231875). Leading vendors of knowledge-based systems and a handful of top research institutions join their efforts to develop the technology that will empower business policies in the enterprise of the future. Two large companies are the test-beds that ensure the success and business impact of the technology produced by ONTORULE.

Further information can be found at the official webpage of the project: ontorule-project.eu

Aletheia is a leading innovation project, sponsored by the Federal Ministry of Education and Research, that aims at obtaining comprehensive access to product information through the use of semantic technologies.

Today’s systems for managing product information focus on the development, production, and distribution phases. Thereby they neglect the preceding customer demand analysis and product portfolio management phases, as well as the subsequent operations, maintenance, and recycling phases. In addition, important and increasingly comprehensive sources of information, such as internet forums, blogs, wikis, and emails or office application documents, are currently not collected. Finally, current systems are not suited for product types, such as software or services.

These deficits in the central product lifecycle points, information sources, and product types are addressed by Aletheia. On the one hand, Aletheia consults structured data from company-owned information sources, such as product databases, to respond to inquiries, but on the other hand also unstructured data from office documents and web 2.0 sources, such as wikis, blogs, and web forums, as well as sensor and RFID data are regarded.

The information contained in these heterogeneous sources is converted into a homogeneous form to respond to user inquiries. Hereby, the information that is explicitly contained in the source is not only returned, but semantic technologies are used in order to deduce implicit knowledge and make it available for the user. The results are returned in a context-oriented manner. This means they will be presented in a design that is adapted to the context and role of the user (customer, customer service staff, product designer, etc.). As such, it is important to consider the respective access rights and data security.

For further information please visit www.aletheia-projekt.de

Within the BMBF funded joint research project V.em.Pro an integrated development environment will be developed that allows considering knowledge about the reliability of a product in an early stage of the development cycle of multifunctional products. A holistic concept will be developed that allows the virtualisation of the product concept as well as the knowledge and rule based analysis of the reliability of the developed concept.

The aim is to develop a computer aided tool for developing virtual product concepts in early stages of the development cycle as well as for modelling and representing knowledge about the reliability of the developed products using ontologies.

The main idea of the approach is the heterogeneous modelling of multifunctional product concepts as well as the derivation of actions and strategies to increase the reliability of the products to be developed in an early stage of the development cycle.

The Project is funded by the German Federal Ministry of Education and Research (BMBF) and is supervised by the Project Management Agency Forschungszentrum Karlsruhe (PTKA).

For further information please visit www.produktionsforschung.de/verbundprojekte/vp/index.htm?TF_ID=49&VP_ID=2642