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A methodology to evaluate important dimensions of information quality in systems

Ion George Todoran 1, 2 Laurent Lecornu 3, 1 Ali Khenchaf 4, 5 Jean-Marc Le Caillec 2, 1
2 Lab-STICC_TB_CID_SFIIS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
3 Lab-STICC_TB_CID_DECIDE
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
4 Lab-STICC_ENSTAB_CID_TOMS ; REMS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (UMR 3192), STIC - Pôle STIC [Brest]
Abstract : Assessing the quality of the information proposed by an information system has become one of the ma- jor research topics in the last two decades. A quick literature survey shows that a significant number of information quality frameworks are proposed in different domains of application: management information systems, web information systems, information fusion systems, etc. Unfortunately, they do not provide a feasible methodology that is both simple and intuitive to be implemented in practice. In order to address this need, we present in this paper a new information quality methodology. Our methodology makes use of existing frameworks and proposes a three-step process capable of tracking the quality changes through the system. In the first step and as a novelty compared to existing studies, we propose decomposing the information system into its elementary modules. Having access to each module allows us to locally define the information quality. Then, in the second step we model each processing module by a quality transfer function, capturing the module's influence over the information quality. In the third step we make use of the previous two steps in order to estimate the quality of the entire information system. Thus, our method- ology allows informing the end user on both output quality and local quality. The proof of concept of our methodology has been carried out considering two applications: an automatic target recognition system and a diagnosis coding support system.
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https://hal.archives-ouvertes.fr/hal-01185476
Contributeur : Bibliothèque Télécom Bretagne <>
Soumis le : jeudi 20 août 2015 - 12:14:58
Dernière modification le : mercredi 24 juin 2020 - 16:19:29

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Ion George Todoran, Laurent Lecornu, Ali Khenchaf, Jean-Marc Le Caillec. A methodology to evaluate important dimensions of information quality in systems. Journal of data and information quality, ACM, 2015, 6 (2-3), pp.art.n°11 -. ⟨10.1145/2744205⟩. ⟨hal-01185476⟩

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