Developing an ontology for data science projects to facilitate the design process of a canvas

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

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Developing an ontology for data science projects to facilitate the design process of a canvas. / Thiée, Lukas-Walter.

Wirtschaftsinformatik 2022 Proceedings. 2021.

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

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Bibtex

@inbook{494b6422549a4f32956fbc61b8aa98b1,
title = "Developing an ontology for data science projects to facilitate the design process of a canvas",
abstract = "Data science projects can become very complex, due to the complexity of their content, but also due to the nature and composition of their stake-holders. There are several approaches to remedy this, e.g., canvases, which support ideation and common understanding. However, previous approach-es are limited to single details or abstract too much, so that it is difficult to carry out entire projects successfully based on them. This paper describes one part of the design process, namely the derivation of the underlying on-tology, of a new canvas that integrates both the overall project and detail steps. The ontology is mainly derived from CRISP-DM, literature review and project work.",
author = "Lukas-Walter Thi{\'e}e",
year = "2021",
month = nov,
day = "26",
language = "English",
booktitle = "Wirtschaftsinformatik 2022 Proceedings",

}

RIS

TY - CHAP

T1 - Developing an ontology for data science projects to facilitate the design process of a canvas

AU - Thiée, Lukas-Walter

PY - 2021/11/26

Y1 - 2021/11/26

N2 - Data science projects can become very complex, due to the complexity of their content, but also due to the nature and composition of their stake-holders. There are several approaches to remedy this, e.g., canvases, which support ideation and common understanding. However, previous approach-es are limited to single details or abstract too much, so that it is difficult to carry out entire projects successfully based on them. This paper describes one part of the design process, namely the derivation of the underlying on-tology, of a new canvas that integrates both the overall project and detail steps. The ontology is mainly derived from CRISP-DM, literature review and project work.

AB - Data science projects can become very complex, due to the complexity of their content, but also due to the nature and composition of their stake-holders. There are several approaches to remedy this, e.g., canvases, which support ideation and common understanding. However, previous approach-es are limited to single details or abstract too much, so that it is difficult to carry out entire projects successfully based on them. This paper describes one part of the design process, namely the derivation of the underlying on-tology, of a new canvas that integrates both the overall project and detail steps. The ontology is mainly derived from CRISP-DM, literature review and project work.

UR - https://aisel.aisnet.org/wi2022/ai/ai/13/

M3 - Article in conference proceedings

BT - Wirtschaftsinformatik 2022 Proceedings

ER -