Master data

Title: Quo Vadis modeling?
Subtitle: Findings of a community survey, an ad-hoc bibliometric analysis, and expert interviews on data, process, and software modeling
Abstract:

AbstractModels are the key tools humans use to manage complexity in description, development, and analysis. This applies to all scientific and engineering disciplines and in particular to the development of software and data-intensive systems. However, different methods and terminologies have become established in the individual disciplines, even in the sub-fields of Informatics, which raises the need for a comprehensive and cross-sectional analysis of the past, present, and future of modeling research. This paper aims to shed some light on how different modeling disciplines emerged and what characterizes them with a discussion of the potential toward a common modeling future. It focuses on the areas of software, data, and process modeling and reports on an analysis of the research approaches, goals, and visions pursued in each, as well as the methods used. This analysis is based on the results of a survey conducted in the communities concerned, on a bibliometric study, and on interviews with a prominent representative of each of these communities. The paper discusses the different viewpoints of the communities, their commonalities and differences, and identifies possible starting points for further collaboration. It further discusses current challenges for the communities in general and modeling as a research topic in particular and highlights visions for the future.

Keywords: Modeling and Simulation, Software
Publication type: Article in journal (Authorship)
Publication date: 10.10.2023 (Online)
Published by: Journal of Software & Systems Modeling
Journal of Software & Systems Modeling
to publication
 ( Springer International Publishing AG; )
Title of the series: -
Volume number: -
Issue: -
First publication: Yes
Version: -
Page: pp. 1 - 22

Versionen

Keine Version vorhanden
Publication date: 10.10.2023
ISBN (e-book): -
eISSN: 1619-1374
DOI: http://dx.doi.org/10.1007/s10270-023-01128-y
Homepage: -
Open access
  • Available online (open access)

Assignment

Organisation Address
Fakultät für Technische Wissenschaften
 
Institut für Artificial Intelligence und Cybersecurity
Universitätsstr. 65-67
A-9020 Klagenfurt
Austria
  -993705
   aics-office@aau.at
https://www.aau.at/en/aics/
To organisation
Universitätsstr. 65-67
AT - A-9020  Klagenfurt

Categorisation

Subject areas
  • 102 - Computer Sciences
Research Cluster No research Research Cluster selected
Citation index
  • Science Citation Index Expanded (SCI Expanded)
Information about the citation index: Master Journal List
Peer reviewed
  • Yes
Publication focus
  • Science to Science (Quality indicator: II)
Classification raster of the assigned organisational units:
working groups
  • Application Engineering

Cooperations

Organisation Address
RWTH Aachen
Templergraben 55
52062 Aachen
Germany
Templergraben 55
DE - 52062  Aachen
Technische Universität Wien
Karlsplatz 13
1040 Wien
Austria - Vienna
Karlsplatz 13
AT - 1040  Wien
Johannes Kepler Universität Linz
Altenberger Straße 69
4040 Linz
Austria - Upper Austria
Altenberger Straße 69
AT - 4040  Linz

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