Conceptual Modeling Systems: A Vision for the Future of Conceptual Modeling

Roman Lukyanenko; Binny M. Samuel; Veda C. Storey; Arnon Sturm

Conceptual Modeling Systems: A Vision for the Future of Conceptual Modeling

Roman Lukyanenko
, Binny M. Samuel
, Veda C. Storey
, Arnon Sturm

Research output: Contribution to journal › Conference article › peer-review

Abstract

Although conceptual modeling has been integral to information systems development and use, much of its potential remains underutilized. This is evidenced by the lack of a broad adoption of modeling concepts beyond traditional database design and process modeling applications. In this paper, we propose a fundamentally new perspective on conceptual modeling that integrates artificial intelligence (AI) components with conceptual modeling. This perspective enables us to go beyond passive conceptual modeling representations, such as diagrams, to design conceptual modeling systems that have the capability to learn and evolve.

Original language	English
Journal	CEUR Workshop Proceedings
Volume	3211
State	Published - 1 Jan 2022
Event	2022 ER Forum and PhD Symposium, ER-Forum-PhD 2022 co-located with 41st International Conference on Conceptual Modeling, ER 2022 - Virtual, Online Duration: 17 Oct 2022 → 17 Oct 2022

Keywords

Conceptual modeling
artificial intelligence
conceptual model systems (CMS)

ASJC Scopus subject areas

General Computer Science

Cite this

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title = "Conceptual Modeling Systems: A Vision for the Future of Conceptual Modeling",

abstract = "Although conceptual modeling has been integral to information systems development and use, much of its potential remains underutilized. This is evidenced by the lack of a broad adoption of modeling concepts beyond traditional database design and process modeling applications. In this paper, we propose a fundamentally new perspective on conceptual modeling that integrates artificial intelligence (AI) components with conceptual modeling. This perspective enables us to go beyond passive conceptual modeling representations, such as diagrams, to design conceptual modeling systems that have the capability to learn and evolve.",

keywords = "Conceptual modeling, artificial intelligence, conceptual model systems (CMS)",

author = "Roman Lukyanenko and Samuel, \{Binny M.\} and Storey, \{Veda C.\} and Arnon Sturm",

note = "Publisher Copyright: {\textcopyright} 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).; 2022 ER Forum and PhD Symposium, ER-Forum-PhD 2022 co-located with 41st International Conference on Conceptual Modeling, ER 2022 ; Conference date: 17-10-2022 Through 17-10-2022",

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TY - JOUR

T1 - Conceptual Modeling Systems

T2 - 2022 ER Forum and PhD Symposium, ER-Forum-PhD 2022 co-located with 41st International Conference on Conceptual Modeling, ER 2022

AU - Lukyanenko, Roman

AU - Samuel, Binny M.

AU - Storey, Veda C.

AU - Sturm, Arnon

PY - 2022/1/1

Y1 - 2022/1/1

N2 - Although conceptual modeling has been integral to information systems development and use, much of its potential remains underutilized. This is evidenced by the lack of a broad adoption of modeling concepts beyond traditional database design and process modeling applications. In this paper, we propose a fundamentally new perspective on conceptual modeling that integrates artificial intelligence (AI) components with conceptual modeling. This perspective enables us to go beyond passive conceptual modeling representations, such as diagrams, to design conceptual modeling systems that have the capability to learn and evolve.

AB - Although conceptual modeling has been integral to information systems development and use, much of its potential remains underutilized. This is evidenced by the lack of a broad adoption of modeling concepts beyond traditional database design and process modeling applications. In this paper, we propose a fundamentally new perspective on conceptual modeling that integrates artificial intelligence (AI) components with conceptual modeling. This perspective enables us to go beyond passive conceptual modeling representations, such as diagrams, to design conceptual modeling systems that have the capability to learn and evolve.

KW - Conceptual modeling

KW - artificial intelligence

KW - conceptual model systems (CMS)

UR - https://www.scopus.com/pages/publications/85138735745

M3 - Conference article

SN - 1613-0073

VL - 3211

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

Y2 - 17 October 2022 through 17 October 2022

ER -

Conceptual Modeling Systems: A Vision for the Future of Conceptual Modeling

Abstract

Keywords

ASJC Scopus subject areas

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