MADISE: Method Engineering-based Approach for Enhancing Decision-Making in Information Systems Engineering

The goal of this work is to offer an approach for enhancing decision-making in information systems engineering based on the Method Engineering principles. In order to achieve this goal, we have developed the MADISE (MAke Decisions in Information Systems Engineering) approach. The MADISE approach includes four following elements: the DM ontology, the DM method family, the MADISE configuration process, and the MADISE methodological repository. The DM Ontology (DMO) is an ontology of decision-making knowledge, which allows representing DM concepts in a structured manner. The main goal of DMO is formalizing DM situation and specifying requirements for DM. The DM Method Family is a collection of DM method components organized into a family for their easier usage in practice. DM components represent detailed guidelines for DM activities associated to the specific context of their use. The Method Family Configuration Process is a ME process helping IS engineers to customize DM method family. This process guides the selection and assembly of DM components into an application method adapted to a given situation. The Methodological Repository is a repository, which provides IS engineers with a methodological support for realizing DM activities. For the needs of the MADISE approach, some fundamentals of the ME science are developed. Firstly, the concept of method family is proposed. Secondly, an approach for contextualization of method components is developed. Thirdly, an indicator-based guidance methodology is suggested for customizing method families according to a given situation. These elements are applied to DM methods in order to achieve the main research goal.

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Source https://theses.hal.science/tel-00763922
Author Kornyshova, Elena
Maintainer CCSD
Last Updated May 31, 2026, 17:30 (UTC)
Created May 31, 2026, 17:30 (UTC)
Identifier tel-00763922
Language en
Rights https://about.hal.science/hal-authorisation-v1/
contributor Centre de Recherche en Informatique de Paris 1 (CRI) ; Université Paris 1 Panthéon-Sorbonne (UP1)
creator Kornyshova, Elena
date 2011-12-13T00:00:00
harvest_object_id 0838f93c-8c49-40de-9a17-9214a9d55043
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2023-12-19T00:00:00
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