Comparative Analysis of Process Models for Data Science Projects

Damian Kutzias; Claudia Dukino; Falko Kötter; Holger Kett

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Paper

Comparative Analysis of Process Models for Data Science Projects

Topics: Data Science; Planning and Scheduling

In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, 1052-1062, 2023 , Lisbon, Portugal

Authors: Damian Kutzias ¹ ; Claudia Dukino ¹ ; Falko Kötter ² and Holger Kett ¹

Affiliations: ¹ Fraunhofer IAO, Fraunhofer Institute for Industrial Engineering IAO, Germany ; ² Baden-Württemberg Cooperative State University, Germany

Keyword(s): Data Science, Process Models, Methodology, Project Management, Artificial Intelligence.

Abstract: When adopting data science technology into practice, enterprises need proper tools and process models. Data science process models guide the project management by providing workflows, dependencies, requirements, relevant challenges and questions as well as suggestions of proper tools for all tasks. Whereas process models for classic software development have evolved for a comparably long time and therefore have a high maturity, data science process models are still in rapid evolution. This paper compares existing data science process models using literature analysis, and identifies the gap between existing models and relevant challenges by performing interviews with experts.

CC BY-NC-ND 4.0

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Paper citation in several formats:

Kutzias, D.; Dukino, C.; Kötter, F. and Kett, H. (2023). Comparative Analysis of Process Models for Data Science Projects. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-623-1; ISSN 2184-433X, SciTePress, pages 1052-1062. DOI: 10.5220/0011895200003393

@conference{icaart23,
author={Damian Kutzias. and Claudia Dukino. and Falko Kötter. and Holger Kett.},
title={Comparative Analysis of Process Models for Data Science Projects},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2023},
pages={1052-1062},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011895200003393},
isbn={978-989-758-623-1},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Comparative Analysis of Process Models for Data Science Projects
SN - 978-989-758-623-1
IS - 2184-433X
AU - Kutzias, D.
AU - Dukino, C.
AU - Kötter, F.
AU - Kett, H.
PY - 2023
SP - 1052
EP - 1062
DO - 10.5220/0011895200003393
PB - SciTePress