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 Enterprise Modelling in the Age of Generative and Agentic AI track at ECIS 2026, Milano, Italia. Soon to be launched 3rd collection of OMiLAB DSML tools , Milano, Italia. 3rd Knowledge Graph-focused workshop at CAISE 2025, Vienna, Austria. DKE Special Issue - Large Language Models and Knowledge Graphs for Semantics-driven Systems Engineering Past events OMiLAB-KNOW Workshop @ at BIR 2024, Prague, Czech Rep. 2nd Knowledge Graph-focused workshop at CAISE 2024, Limassol, Cyprus. 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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