OMiLAB FSEGA: open models for Business Informatics
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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:


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:

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