OMiLAB FSEGA: open models for Business Informatics

OMiLAB FSEGA: open models for Business Informatics
What is OMiLAB? Home Events Activities Publications Researchers Photos Results Contact Latest News 2nd Knowledge Graph-focused workshop at CAISE 2024, Limassol, Cyprus. Past events The BEE-UP Tutorial and presentation of teaching experiences in the Symposium on Conceptual Modeling Education at ER 2023 conference, Lisbon, Portugal. The BEE-UP Tutorial was presented at MODELS 2023 conference, Vasteras, Sweden. 1st Workshop on "Domain-specific Modeling Methods and Tools - OMiLAB Nodes experience & knowledge exchange" at BIR 2023, Ascoli Piceno, Italy. Deadline: 06 August 2023 1st Knowledge Graph-focused workshop at CAISE 2023, Zaragoza, Spain. Deadline: 07 March 2023 Enterprise Modeling Track at ECIS 2023, Kristiansand, Norway, during 11-16 June 2023	OMiLAB FSEGA: open models for Business Informatics Research focus of OMiLAB-FSEGA: The recent literature brought into discussion a reframing of Conceptual Modeling and its shifting role in the Digital-first Era, from “representation” to “mediation”. This shift is seen as a manifestation of the “ontological reversal” phenomenon. For more details, see the papers: Recker et al., From Representation to Mediation: A New Agenda for Conceptual Modeling Research in a Digital World Baskerville et al., Digital First: The Ontological Reversal and New Challenges for Information Systems Research We aim to operationalize this notion with the help of the Purpose-Specificity Framework for modeling methods that, instead of working within the traditional dichotomy of „general purpose” vs. „domain-specific”, treat purpose and specificity as orthogonal dimensions. This generates a design space for modeling methods, allowing them to shift agilely according to (possibly evolving) „modeling method requirements” that must be explicitly managed as a distinct category of requirements. Knowledge Graphs can act as a mediator between the human-oriented representations captured in diagrammatic models and machine behavior that becomes “aware” of those models. For more details see the chapter Buchmann, R. A., The Purpose-Specificity Framework for Domain-Specific Modeling Methods. The engineering methodology underlying our research is based on: the Agile Modeling Method Engineering (AMME) framework its extension for producing model-driven software artefacts with knowledge graphs as mediators: the Model-Aware Software Engineering (MASE) approach
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