面向未来数据科学家的数据科学基础

Jiangping Chen, B. R. Ayala, Duha Alsmadi, Guonan Wang
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引用次数: 5

摘要

数据经常与另外两个概念一起讨论:信息和知识。然而,数据的概念似乎没有信息或知识的概念那么模糊。数据被认为是符号,或者是尚未处理的原始事实(Ackoff, 1989;Coronel, Morris, & Rob, 2012, p.5)。相比之下,信息有许多不同的定义,如信息作为一种东西,有信息的东西,一个过程,或等同于知识(Buckland, 1991;洛,1997;Saracevic, 1999;马登,2000)。知识也没有一个公认的定义。Davenport和Prusak(1998)认为知识是“一个由有框架的经验、价值观、背景信息和专家见解组成的流动混合体,它为评估和整合新的经验和信息提供了一个框架。”(Davenport & Prusak, 1998, p.5)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fundamentals of Data Science for Future Data Scientists
Data have been frequently discussed along with two other concepts: information and knowledge. However, the concept of data seems less ambiguous than that of information or knowledge. Data are considered to be symbols, or raw facts which have not yet been processed (Ackoff, 1989; Coronel, Morris, & Rob, 2012, p.5). In contrast, information has a number of different definitions, such as information as a thing, something informative, a process, or equivalent to knowledge (Buckland, 1991; Losee, 1997; Saracevic, 1999; Madden, 2000). Knowledge also does not have an agreed-upon definition. Davenport and Prusak (1998) viewed knowledge as “a fluid mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new experiences and information.” (Davenport & Prusak, 1998, p.5).
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