Data-driven Discovery： A New Era of Exploiting the Literature and Data

• 作者: Kyle Stirling Ying Ding
• 来源期刊: 数据与情报科学学报：英文版
• 学科: 社会科学
• 关键词: 数据 情报科学
• 年，卷（期）: 2016,（4）
• 页码范围: 1-9
• 页数: 9页
• 分类号: G2

摘要

In the current data-intensive era, the traditional hands-on method ofconducting scientific research by exploring related publications to generate a testablehypothesis is well on its way of becoming obsolete within just a year or two.Analyzing the literature and data to automatically generate a hypothesis mightbecome the de facto approach to inform the core research efforts of those trying tomaster the exponentially rapid expansion of publications and datasets. Here,viewpoints are provided and discussed to help the understanding of challengesof data-driven discovery.