Data lakes for digital humanities

J. Darmont, Cécile Favre, Sabine Loudcher, C. Noûs
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引用次数: 4

Abstract

Traditional data in Digital Humanities projects bear various formats (structured, semi-structured, textual) and need substantial transformations (encoding and tagging, stemming, lemmatization, etc.) to be managed and analyzed. To fully master this process, we propose the use of data lakes as a solution to data siloing and big data variety problems. We describe data lake projects we currently run in close collaboration with researchers in humanities and social sciences and discuss the lessons learned running these projects.
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数字人文的数据湖
数字人文项目中的传统数据具有多种格式(结构化、半结构化、文本化),需要进行大量的转换(编码和标记、词干提取、词序化等)才能进行管理和分析。为了充分掌握这一过程,我们提出使用数据湖来解决数据孤岛和大数据多样性问题。我们描述了我们目前与人文和社会科学研究人员密切合作的数据湖项目,并讨论了从这些项目中获得的经验教训。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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