.png){kind=icon}
返回
Prospecting (in) the data sciences
.png){kind=icon}
OA
AI
DOI：10.1177/2053951720906849.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Data science is characterized by engaging heterogeneous data to tackle real world questions and problems. But data science has no data of its own and must seek it within real world domains. We call this search for data prospecting and argue that the dynamics of prospecting are pervasive in, even characteristic of, data science. Prospecting aims to render the data, knowledge, expertise, and practices of worldly domains available and tractable to data science method and epistemology. Prospecting precedes data synthesis, analysis, or visualization, and is constituted by the upstream work of discovering disordered or inaccessible data resources, thereafter to be ordered and rendered available for computation. Through this work, data science positions itself in the middle of all things-capable of engaging this, that, or any domain-and thus prospecting is a key driver of data science's ongoing formation as a universal(izing) science.
Keyword:
Infrastructure
data science
logic of domains
Big Data hubs and spokes
science policy
science studies
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
5.9
论文数:
718
被引数:
5.3K
机构
引用论文
分享收藏Effects of Rare Earth Elements on Properties of Ni-Base Superalloy Powders and Coatings.png)
CoatingsOAAI
CoatingsIF0
OAAI分享收藏Power system stability analysis under increasing penetration of photovoltaic power plants with synchronous power controllers具有同步功率控制器的光伏电站渗透率增加下的电力系统稳定性分析OAAI
OAAI分享收藏
查看更多内容