Toward Foundations for Data Science and Analytics: A Knowledge Framework for Professional Standards
Toward Foundations for Data Science and Analytics: A Knowledge Framework for Professional Standards
复制标题
迈向数据科学和分析的基础：专业标准的知识框架
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Hamit Hamutcu
中科院分区：
文献类型：
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作者：
U. Fayyad;Hamit Hamutcu
随着行业竞相利用数据的力量，对数据科学专业人员的需求正在以越来越快的速度增长。然而，几乎每个组织都有一种独特的方式来定义数据科学以及相关技能和知识的角色。这导致了雇主、学术和培训机构以及现有和有抱负的数据科学专业人员的混乱行业格局。本文是分析和数据科学标准倡议（IADSS）撰写的系列文章中的第一篇。我们回顾了数据科学的历史，我们可以追溯到1974年，以及数据科学作为行业专业的出现，其次是数据科学专业人员通常与知识和技能相关的分类，指出缺乏详细和一致的主题处理。然后，我们提出了一个数据科学知识框架，我们相信它可以支持行业标准化，并为数据科学专业人员建立测量和评估方法。
As the industry is racing to harness the power of data, demand for data science professionals is growing at an increasing rate. However, almost every organization has a unique way of defining roles in data science and associated skills and knowledge. This has resulted in a confusing industry landscape for employers, academic and training institutions, and existing and aspiring data science professionals. This article is the first in a series authored by Initiative for Analytics and Data Science Standards (IADSS). We review the history of data science, which we trace back to 1974, and the emergence of data science as a profession in the industry, followed by a classification of knowledge and skills commonly associated with data science professionals, pointing to a lack of detailed and consistent treatment of the topic. We then present a Data Science Knowledge Framework, that we believe can support industry standardization and building measurement and assessment methodologies for data science professionals.
DOI：
10.1073/pnas.1901326117
发表时间：
2020-02-25
影响因子：
11.1
作者：
Yu, Bin;Kumbier, Karl
通讯作者：
Kumbier, Karl