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Karlsruhe, Germany

Becker C.,MediaEvent Services GmbH and Co. KG | Bizer C.,Free University of Berlin | Erdmann M.,Ontoprise GmbH | Greaves M.,Vulcan Inc.
CEUR Workshop Proceedings | Year: 2010

In this paper, we present a project which extends a SMW+ semantic wiki with a Linked Data Integration Framework that performs Web data access, vocabulary mapping, identity resolution, and quality evaluation of Linked Data. As a result, a large collection of neurogenomicsrelevant data from the Web can be flexibly transformed into a unified ontology, allowing unified querying, navigation, and visualization; as well as support for wiki-style collaboration, crowdsourcing, and commentary on chosen data sets. Source

Gmez-Prez J.M.,Intelligent Software Components ISOCO S.A. | Erdmann M.,Ontoprise GmbH | Greaves M.,Vulcan Inc. | Corcho O.,Technical University of Madrid | Benjamins R.,Telefnica ID
International Journal of Human Computer Studies | Year: 2010

The development of knowledge-based systems is usually approached through the combined skills of software and knowledge engineers (SEs and KEs, respectively) and of subject matter experts (SMEs). One of the most critical steps in this task aims at transferring knowledge from SMEs' expertise to formal, machine-readable representations, which allow systems to reason with such knowledge. However, this process is costly and error prone. Alleviating such knowledge acquisition bottleneck requires enabling SMEs with the means to produce the target knowledge representations, minimizing the intervention of KEs. This is especially difficult in the case of complex knowledge types like processes. The analysis of scientific domains like Biology, Chemistry, and Physics uncovers: (i) that process knowledge is the single most frequent type of knowledge occurring in such domains and (ii) specific solutions need to be devised in order to allow SMEs to represent it in a computational form. We present a framework and computer system for the acquisition and representation of process knowledge in scientific domains by SMEs. We propose methods and techniques to enable SMEs to acquire process knowledge from the domains, to formally represent it, and to reason about it. We have developed an abstract process metamodel and a library of problem solving methods (PSMs), which support these tasks, respectively providing the terminology for SME-tailored process diagrams and an abstract formalization of the strategies needed for reasoning about processes. We have implemented this approach as part of the DarkMatter system and formally evaluated it in the context of the intermediate evaluation of Project Halo, an initiative aiming at the creation of question answering systems by SMEs. © 2010 Elsevier Ltd. All rights reserved. Source

Angele J.,Ontoprise GmbH
Semantic Web | Year: 2014

OntoBroker provides a comprehensive, scalable and high-performance Semantic Web middleware. It supports all of the W3C Semantic Web recommendations for ontology languages and query languages. It is an ontology repository that includes a high performance deductive reasoning engine. Especially reasoning with rules is a major unique selling point for ontoprise. OntoBroker integrates a connector framework which makes it easy to connect a multitude of data sources like databases, web services etc. Thus it combines structured and unstructured data in one framework, OntoBroker is easy to extend and to integrate into existing IT landscapes and applications as it offers a variety of open interfaces. OntoBroker is also closely connected to ontoprise's ontology modeling environment OntoStudio which is the development environment for handling ontologies, mappings to information sources, rules, generating queries, creating business intelligence reports etc. At many customers OntoBroker serves as a common semantic layer which is accessed by various applications and integrates different information sources. OntoBroker is the run-time environment for industrial solutions like SemanticGuide, SemanticXpress, and SemanticIntegrator. As part of those meanwhile thousands of installations are in productive use. © 2014-IOS Press and the authors. All rights reserved. Source

Gomez-Perez J.M.,ISOCO S.A. | Corcho O.,Technical University of Madrid | Erdmann M.,Ontoprise GmbH
CEUR Workshop Proceedings | Year: 2010

Enabling Subject Matter Experts (SMEs) to formulate knowledge without the intervention of Knowledge Engineers (KEs) requires providing SMEs with methods and tools that abstract the underlying knowledge representation, allowing SMEs to focus on the modeling activities. However, automatically bridging the gap between SME-authored models and their internal representation is not an easy task, especially in the case of complex knowledge types like processes, where aspects like frame management, data, and control flow need to be addressed. In this paper, we present a process representation formalism and method for automatically grounding SME-authored process models in the form of process diagrams into a particular representation language, supporting process representation and reasoning. Source

Janssen F.,TU Darmstadt | Fallahi F.,Ontoprise GmbH | Noessner J.,University of Mannheim | Paulheim H.,TU Darmstadt
CEUR Workshop Proceedings | Year: 2012

Ontology matching approaches have mostly worked on the schema level so far. With the advent of Linked Open Data and the availability of a massive amount of instance information, instance-based approaches become possible. This position paper discusses approaches and challenges for using those instances as input for machine learning algorithms, with a focus on rule learning algorithms, as a means for ontology matching. Source

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