Thönssen, Barbara
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Thönssen, Barbara
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- PublikationArchiMEO: A standardized enterprise ontology based on the ArchiMate conceptual model(2020) Hinkelmann, Knut; Laurenzi, Emanuele; Martin, Andreas; Montecchiari, Devid; Spahic, Maja; Thönssen, Barbara; Hammoudi, Slimane; Ferreira Pires, Luis; Selić, Bran [in: Proceedings of the 8th International Conference on Model-Driven Engineering and Software Development]Many enterprises face the increasing challenge of sharing and exchanging data from multiple heterogeneous sources. Enterprise Ontologies can be used to effectively address such challenge. In this paper, we present an Enterprise Ontology called ArchiMEO, which is based on an ontological representation of the ArchiMate standard for modeling Enterprise Architectures. ArchiMEO has been extended to cover various application domains such as supply risk management, experience management, workplace learning and business process as a service. Such extensions have successfully proven that our Enterprise Ontology is beneficial for enterprise applications integration purposes.04B - Beitrag Konferenzschrift
- PublikationArchitectures for Business Processess in Organizations(2015) Thönssen, Barbara; Pierantonio, Alfonso; Silingas, Darius; Rosa, Gianni; Woitsch, Robert [in: Procs. Project Showcase (PS’15), Software Technologies: Applications and Foundations (STAF’15)]04B - Beitrag Konferenzschrift
- PublikationTowards a Procedure for Assessing Supply Chain Risks Using Semantic Technology(Springer, 2013) Emmenegger, Sandro; Hinkelmann, Knut; Laurenzini, Emanuele; Thönssen, Barbara; Fred, Ana; Dietz, Jan L. G; Liu, Kecheng; Felipe, Joaquim [in: Knowledge Discovery, Knowledge Engineering and Knowledge Management]In the APPRIS project an Early-Warning-System (EWS) is developed applying semantic technologies, namely an enterprise ontology and an inference engine, for the assessment of procurement risks. Our approach allows for analyzing internal resources (e.g. ERP and CRM data) and external sources (e.g. entries in the Commercial Register and newspaper reports) to assess known risks, but also for identifying black swans, which hit enterprises with no warning but potentially large impact. For proof of concept we developed a prototype that allows for integrating data from various information sources, of various information types (structured and unstructured), and information quality (assured facts, news); automatic identification, validation and quantification of risks and aggregation of assessment results on several granularity levels. The motivating scenario is derived from three business project partners real requirements for an EWS.04B - Beitrag Konferenzschrift
- PublikationSemantically enriched obligation management(04.10.2012) Thönssen, Barbara; Lutz, Jonas [in: Proceedings of 4th Conference on Knowledge Management and Information Sharing (KMIS2012)]04B - Beitrag Konferenzschrift
- PublikationImproving supply-chain-management based on semantically enriched risk descriptions(04.10.2012) Emmenegger, Sandro; Laurenzini, Emanuele; Thönssen, Barbara [in: Proceedings of 4th Conference on Knowledge Management and Information Sharing (KMIS2012)]04B - Beitrag Konferenzschrift
- PublikationMining of Agile Business Processes(21.03.2011) Brander, Simon; Hinkelmann, Knut; Martin, Andreas; Thönssen, Barbara [in: Proceedings of the AAAI 2011 Spring Symposium]Organizational agility is a key challenge in today's business world. The Knowledge-Intensive Service Support approach tackles agility by combining process modeling and business rules. In the paper at hand, we present five approaches of process mining that could further increase the agility of processes by improving an existing process model.04B - Beitrag Konferenzschrift
- PublikationRefining Process Models through the Analysis of Informal Work Practice(2011) Brander, Simon; Hinkelmann, Knut; Hu, Bo; Martin, Andreas; Riss, Uwe; Thönssen, Barbara; Witschel, Hans FriedrichThe work presented in this paper explores the potential of leveraging the traces of informal work and collaboration in order to improve business processes over time. As process executions often differ from the original design due to individual preferences, skills or competencies and exceptions, we propose methods to analyse personal preferences of work, such as email communication and personal task execution in a task management application. Outcome of these methods is the detection of internal substructures (subtasks or branches) of activities on the one hand and the recommendation of resources to be used in activities on the other hand, leading to the improvement of business process models. Our first results show that even though human intervention is still required to operationalise these insights it is indeed possible to derive interesting and new insights about business processes from traces of informal work and infer suggestions for process model changes.04B - Beitrag Konferenzschrift
- PublikationAI for Business Agility(2011) Hinkelmann, Knut; Thönssen, Barbara [in: Papers from the AAAI Spring Symposium, 21-23 March 2011]04B - Beitrag Konferenzschrift
- PublikationFormalizing low-level governance instruments for a more holistic approach to automatic metadata generation(2011) Thönssen, Barbara [in: Proceedings of the 5th International Conference on Methodologies, Technologies and Tools enabling e-Government]04B - Beitrag Konferenzschrift
- PublikationAn Enterprise Ontology building the Bases for Automatic Metadata Generation(02.01.2010) Thönssen, Barbara [in: Proceedings of the 4th International Conference on Metadata and Semantics, MTSR]04B - Beitrag Konferenzschrift