数据科学的科学性与科学问题的分析

doi:10.11896/jsjkx.231100121

Abstract

Abstract: As an emerging academic field,the scientific nature of data science has garnered attention,and its scientific questions have not been clearly defined.This paper explores the scientific nature of data science from four aspects:scientific research paradigms and methodologies,falsifiability and reproducibility,scientific spirit and rapid iteration,and scientific research agenda and theoretical framework.It also answers the question of why data science is an emerging science.Building upon this foundation and incorporating concepts such as the DIKW model(data-information-knowledge-wisdom pyramid or hierarchy),the DMP model(data-model-problem model),the statistical and machine learning methodologies of data science,and the processes and activities in data science.This paper presents seven core scientific questions in data science:the precedence of explanation or data,problem alignment with data or data alignment with problems,prioritizing trust in data or models,emphasizing performance or interpre-tability,data partitioning strategies,solving unknown data problems with known data,and the role of humans within or outside the loop.Finally,four recommendations for data science research are proposed:a focus on theoretical research within data science itself,the further separation and specialization of data science in terms of science,technology,and engineering,strengthening the theory and practice of data science empowered by artificial intelligence,and fostering collaboration between the discipline of data science and data science within other disciplines.

Key words: Data science, Scientific nature, Scientific questions, DIKW model

CLC Number:

TP391

CHAO Lemen. Exploring the Scientific Nature and Scientific Questions of Data Science[J].Computer Science, 2024, 51(1): 26-34.

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