Towards Principled Data Science Assessment - The Personal Data Science Process (PdsP)

Ismael Caballero, Laure Berti-Equille, Mario Piattini

2015

Abstract

With the Unstoppable Advance of Big Data, the Role of Data Scientist Is Becoming More Important than Ever before, in This Position Paper, We Argue That Scientists Should Be Able to Acknowledge the Importance of Data Quality Management in Data Science and Rely on a Principled Methodology When Performing Tasks Related to Data Management, in Order to Quantify How Much a Data Scientist Is Able to Perform the Core of Data Management Activities We Propose the Personal Data Science Process (PdsP), Which Includes Five Staged Qualifications for Data Science Professionals, the Qualifications Are based on Two Dimensions: Personal Data Management Maturity (PDMM) and Personal Data Science Performance (PDSPf), the First One Is Defined According to Dgmr, a Data Management Maturity Model, Which Include Processes Related to the Areas of Data Management: Data Governance, Data Management, and Data Quality Management, the Second One, PDSPf, Is Grounded on PSP (Personal Software Process) and Cover the Personal Skills and Knowledge of Data Scientist When Participating in a Data Science Project, These Dimensions Will Allow to Developing a Measure of How Well a Data Scientist Can Contribute to the Success of the Organization in Terms of Performance and Skills Appraisal.

Paper Citation

in Harvard Style

Caballero I., Berti-Equille L. and Piattini M. (2015). Towards Principled Data Science Assessment - The Personal Data Science Process (PdsP) . In Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-096-3, pages 374-378. DOI: 10.5220/0005463703740378

in Bibtex Style

@conference{iceis15,
author={Ismael Caballero and Laure Berti-Equille and Mario Piattini},
title={Towards Principled Data Science Assessment - The Personal Data Science Process (PdsP)},
booktitle={Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2015},
pages={374-378},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005463703740378},
isbn={978-989-758-096-3},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Towards Principled Data Science Assessment - The Personal Data Science Process (PdsP)
SN - 978-989-758-096-3
AU - Caballero I.
AU - Berti-Equille L.
AU - Piattini M.
PY - 2015
SP - 374
EP - 378
DO - 10.5220/0005463703740378