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Friedrich-Wilhelm-Lübke-Koog, Germany

Hatko R.,University of Wurzburg | Schadler D.,University of Kiel | Mersmann S.,Drager Medical GmbH | Baumeister J.,denkbares GmbH | And 2 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2012

In this paper, we report on the experiences made during the implementation of a therapeutic process, i.e. a guideline, for automated mechanical ventilation of patients in intensive care units. The semantic wiki KnowWE was used as a collaborative development platform for domain specialists, knowledge and software engineers, and reviewers. We applied the graphical guideline language DiaFlux to represent medical expertise about mechanical ventilation in a flowchart-oriented manner. Finally, the computerized guideline was embedded seamlessly into a mechanical ventilator for autonomous execution. © 2012 Springer-Verlag. Source

Baumeister J.,denkbares GmbH | Reutelshoefer J.,University of Wurzburg
ACM International Conference Proceeding Series | Year: 2011

With the industrial success of knowledge-based systems new requirements with respect to Knowledge Engineering processes arise. Besides advanced knowledge acquisition tools, novel techniques for the quality assurance need to be established in order to maintain a safe development process. In Software Engineering, the application of continuous integration as a collection of practices has proved to be suitable for this task. In this paper, we transfer the general ideas of continuous integration from Software Engineering to Knowledge Engineering, and we demonstrate the implementation of a continuous integration tool into a state-of-the-art Knowledge Engineering workbench. Source

Baumeister J.,University of Wurzburg | Baumeister J.,denkbares GmbH | Striffler A.,denkbares GmbH
Knowledge-Based Systems | Year: 2015

The paper describes a new approach of developing and maintaining state-of-the-art decision support systems. Such systems are able to capture the collaborative work on decision problems over time. Due to the complexity of large problem spaces a multi-modal knowledge representation is proposed. For the realization of a multi-modal knowledge base we integrate semantic technologies as a fundamental layer by combining the W3C ontologies PROV-O and SKOS. The approach is demonstrated by an implementation report of an industrially deployed decision support system. © 2015 Elsevier B.V. Source

Furth S.,denkbares GmbH | Baumeister J.,denkbares GmbH | Baumeister J.,University of Wurzburg
CEUR Workshop Proceedings | Year: 2014

The regular improvement and adaptation of an ontology is a key factor for the success of an ontology-based system. In this paper, we report on an ongoing project that aims for a methodology and tool for ontology development in a self-improving manner. The approach makes heavy use of methods known in natural language processing and information extraction. Copyright © 2014 by the paper's authors. Source

Baumeister J.,denkbares GmbH | Baumeister J.,University of Wurzburg | Reutelshoefer J.,denkbares GmbH
CEUR Workshop Proceedings | Year: 2014

Today, large knowledge bases are developed collaboratively and in an incremental manner. Often the engineering starts with the collection and organization of informal elements, that are subsequently refined into explicit knowledge. Due to the size of knowledge bases and the collaborative setting, the analysis of the current development progress becomes an important issue. The results of that analysis usually steer the further development direction and efforts. In this paper, we introduce a graph-based representation of general knowledge bases, containing formal and informal knowledge.We use this representation to define general and tailored connectivity measures for knowledge bases. We briefly report on the application of these measures in an industrial case study. Copyright © 2014 by the paper's authors. Source

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