StephanBloehdorn PeterHaase MarkHefke YorkSure ChristophTempich Intelligent Community Lifecycle Support 278–285 2005 SimoneBraun MarkHefke AndreasSchmidt NeyirSevilmis Im Wissensnetz: Linked Information Processes in Research Networks 2007 At first glance, it seems to be quite surprising that so far traditional business process-oriented knowledge management techniques have not been transferred to research in order to improve the efficiency of scientific work on a larger scale. But due to the high variability and unpredictability of scientific work processes, these techniques are not applicable. In fact scientific work processes have to be understood as a network of informal learning processes with a high level of social in-teraction. For this purpose, we have elaborated the model of a “Knowledge-Added Process” as a new paradigm of process-oriented support. We are developing various models, methods, and tools on the basis of semantic technologies supporting this process, and which are exemplified within three scenarios within the application domain “rapid prototyping”. SimoneBraun MarkHefke AndreasSchmidt NeyirSevilmis Im Wissensnetz: Linked Information Processes in Research Networks 2007 At first glance, it seems to be quite surprising that so far traditional business process-oriented knowledge management techniques have not been transferred to research in order to improve the efficiency of scientific work on a larger scale. But due to the high variability and unpredictability of scientific work processes, these techniques are not applicable. In fact scientific work processes have to be understood as a network of informal learning processes with a high level of social in-teraction. For this purpose, we have elaborated the model of a “Knowledge-Added Process” as a new paradigm of process-oriented support. We are developing various models, methods, and tools on the basis of semantic technologies supporting this process, and which are exemplified within three scenarios within the application domain “rapid prototyping”. SimoneBraun AndreasSchmidt MarkHefke A Socially-Aware Desktop for e-Science: Supporting Learning in Networked Scientific Processes 2007 Research is likely to be the most knowledge-intensive environment, and it seems to be quite surprising that so far knowledge management (KM) techniques from business environments have not been transferred to e-science initiatives in order to improve the efficiency of scientific work on a larger scale. An empirical analysis accomplished in the research area of rapid prototyping has unveiled that due to the high variability and unpredictability of scientific work processes, state-of-the-art business process-oriented KM approaches are not applicable and that scientific work processes need a different paradigm understanding knowledge processes as informal learning processes with a high level of social interaction. For this purpose, we present the model of a “knowledge-added process” as a foundation and a socially-aware desktop as an appropriate tool paradigm. SimoneBraun AndreasSchmidt MarkHefke A Socially-Aware Desktop for e-Science: Supporting Learning in Networked Scientific Processes GITO 2 47-54 2007 Research is likely to be the most knowledge-intensive environment, and it seems to be quite surprising that so far knowledge management (KM) techniques from business environments have not been transferred to e-science initiatives in order to improve the efficiency of scientific work on a larger scale. An empirical analysis accomplished in the research area of rapid prototyping has unveiled that due to the high variability and unpredictability of scientific work processes, state-of-the-art business process-oriented KM approaches are not applicable and that scientific work processes need a different paradigm understanding knowledge processes as informal learning processes with a high level of social interaction. For this purpose, we present the model of a "knowledge-added process" as a foundation and a socially-aware desktop as an appropriate tool paradigm. SimoneBraun AndreasSchmidt MarkHefke NeyirSevilmis Im Wissensnetz: Vernetzte Informationsprozesse in Forschungsverbünden 2007 Klassische (prozessorientierte) Wissensmanagementansätze wurden in der Forschung bislang nur wenig umgesetzt. Hauptgründe hierfür sind zum einen die hohe Variabilität von wissenschaftlichen Arbeitsprozessen, zum anderen die Tatsache, dass in der Forschung Strukturen erst im Entstehen begriffen sind. Vielmehr ist wissenschaftliche Arbeit als ein Geflecht von von informellen Lernprozessen zu verstehen. Hierfür wurde im BMBF-Forschungsprojekt "Im Wissensnetz" der sog. „Wissensschöpfungsprozess“ erarbeitet. Anhand der Anwendungsdomäne „Rapid Protyping“ werden Modelle, Methoden und Werkzeuge auf der Basis semantischer Technologien entwickelt, die diesen Wissensschöpfungsprozess unterstützen und effizienter gestalten. MarcEhrig PeterHaase MarkHefke NenadSojanovic Similarity for Ontologies - a Comprehensive Framework: workshop paper December 2004 In this paper we present a comprehensive framework for measuring similarity within and between ontologies as a basis for the collaboration across various application fields. In order to define such a framework, we base our work on an abstract ontology model that allows to adhere to various existing and evolving ontology standards. The main characteristics of the framework is its layered structure: We have defined three levels on which the similarity between two entities (concepts or instances) can be measured: data layer, ontology layer, and context layer, that cope with the data representation, ontology meaning and the usage of these entities, respectively. In addition, in each of the layers corresponding background information is used in order to define the similarity more precisely. The framework is complete in the sense of covering the similarity between all elements defined in the abstract ontology model by comprising similarity measures for all above-named layers as well as relations between them. Moreover, we have validated our framework with several practical case studies in order to prove benefits of applying our approach compared to traditional similarity measures. One of these case studies is described in detail within the paper. MarcEhrig PeterHaase NenadStojanovic MarkHefke Similarity for Ontologies –- A Comprehensive Framework 2005 MarcEhrig PeterHaase NenadStojanovic MarkHefke Similarity for Ontologies - A Comprehensive Framework 2005 MarkHefke ValentinZacharias AndreasAbecker QingliWang ErnstBiesalski MarcoBreiter An Extendable Java Framework for Instance Similarities in Ontologies INSTICC, Setúbal, Portugal 263–269 2006