Improving Data Science Projects by Enriching Analytical Models with Domain Knowledge

Heng Zhang; Utpal Roy; Jeffrey Saltz

doi:10.1109/BigData.2018.8622364

Improving Data Science Projects by Enriching Analytical Models with Domain Knowledge

Heng Zhang, Utpal Roy, Jeffrey Saltz

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

Domain knowledge is very important to support the development of analytic models. However, in today's data science projects, domain knowledge is typically documented, but not captured and integrated with the actual analytic model. This raises problems in interoperability and traceability of the relevant domain knowledge that is used to develop an analytic model. To address this challenge, this paper proposes a Knowledge Enriched Analytic Model (KEAM) to enrich analytic models with domain knowledge. To explore the proposed methodology and its benefits, a case study explores the utilization of KEAM to support the development of a Bayesian Network model within the smart manufacturing domain. The case study shows that the efficiency in developing an analytic model is improved by using the proposed KEAM.

Original language	English (US)
Title of host publication	Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018
Editors	Yang Song, Bing Liu, Kisung Lee, Naoki Abe, Calton Pu, Mu Qiao, Nesreen Ahmed, Donald Kossmann, Jeffrey Saltz, Jiliang Tang, Jingrui He, Huan Liu, Xiaohua Hu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2828-2837
Number of pages	10
ISBN (Electronic)	9781538650356
DOIs	https://doi.org/10.1109/BigData.2018.8622364
State	Published - Jan 22 2019
Event	2018 IEEE International Conference on Big Data, Big Data 2018 - Seattle, United States Duration: Dec 10 2018 → Dec 13 2018

Publication series

Name	Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018

Conference

Conference	2018 IEEE International Conference on Big Data, Big Data 2018
Country	United States
City	Seattle
Period	12/10/18 → 12/13/18

Keywords

analytic model
interoperability
knowledge
smart manufacturing
traceability

ASJC Scopus subject areas

Computer Science Applications
Information Systems

Access to Document

10.1109/BigData.2018.8622364

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Cite this

Zhang, H., Roy, U., & Saltz, J. (2019). Improving Data Science Projects by Enriching Analytical Models with Domain Knowledge. In Y. Song, B. Liu, K. Lee, N. Abe, C. Pu, M. Qiao, N. Ahmed, D. Kossmann, J. Saltz, J. Tang, J. He, H. Liu, & X. Hu (Eds.), Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018 (pp. 2828-2837). [8622364] (Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData.2018.8622364

Improving Data Science Projects by Enriching Analytical Models with Domain Knowledge. / Zhang, Heng; Roy, Utpal ; Saltz, Jeffrey.

Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018. ed. / Yang Song; Bing Liu; Kisung Lee; Naoki Abe; Calton Pu; Mu Qiao; Nesreen Ahmed; Donald Kossmann; Jeffrey Saltz; Jiliang Tang; Jingrui He; Huan Liu; Xiaohua Hu. Institute of Electrical and Electronics Engineers Inc., 2019. p. 2828-2837 8622364 (Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Zhang, H, Roy, U & Saltz, J 2019, Improving Data Science Projects by Enriching Analytical Models with Domain Knowledge. in Y Song, B Liu, K Lee, N Abe, C Pu, M Qiao, N Ahmed, D Kossmann, J Saltz, J Tang, J He, H Liu & X Hu (eds), Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018., 8622364, Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018, Institute of Electrical and Electronics Engineers Inc., pp. 2828-2837, 2018 IEEE International Conference on Big Data, Big Data 2018, Seattle, United States, 12/10/18. https://doi.org/10.1109/BigData.2018.8622364

Zhang H, Roy U , Saltz J. Improving Data Science Projects by Enriching Analytical Models with Domain Knowledge. In Song Y, Liu B, Lee K, Abe N, Pu C, Qiao M, Ahmed N, Kossmann D, Saltz J, Tang J, He J, Liu H, Hu X, editors, Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018. Institute of Electrical and Electronics Engineers Inc. 2019. p. 2828-2837. 8622364. (Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018). https://doi.org/10.1109/BigData.2018.8622364

Zhang, Heng ; Roy, Utpal ; Saltz, Jeffrey. / Improving Data Science Projects by Enriching Analytical Models with Domain Knowledge. Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018. editor / Yang Song ; Bing Liu ; Kisung Lee ; Naoki Abe ; Calton Pu ; Mu Qiao ; Nesreen Ahmed ; Donald Kossmann ; Jeffrey Saltz ; Jiliang Tang ; Jingrui He ; Huan Liu ; Xiaohua Hu. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 2828-2837 (Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018).

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