The Lives and After Lives of Data
The Lives and After Lives of Data
复制标题
数据的生命和来世
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
C. Borgman
中科院分区：
文献类型：
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作者：
C. Borgman
数据科学中最难以捉摸的术语是“数据”。虽然经常被视为计算对象，但数据是一个历史悠久的理论概念。数据存在于知识基础设施中，这些知识基础设施管理着如何创建、管理和解释数据。通过比较数据生命周期的模型，关于数据的隐含假设变得明显。在线性模型中，数据从生命周期的开始到结束经历了各个阶段，这表明数据可以根据需要重新创建。数据在使用和再使用的良性循环中流动的循环模型更适合于可能无限期保留价值的不可替代的观测数据。例如，在天文学中，上一代望远镜的观测结果可能成为下一代望远镜的校准和建模数据，无论是数字巡天还是玻璃板。通过投资于知识基础设施，特别是数字管理和保存，可以提高数据的价值和可重用性。决定保留哪些数据、为什么保留、如何保留以及保留多长时间，是我们当今面临的挑战。关键词sastronomy，策展，数据，数字策展，生命周期，观察，保存，再利用，科学，管理
The most elusive term in data science is ‘data.’ While often treated as objects to be computed upon, data is a theory-laden concept with a long history. Data exist within knowledge infrastructures that govern how they are created, managed, and interpreted. By comparing models of data life cycles, implicit assumptions about data become apparent. In linear models, data pass through stages from beginning to end of life, which suggest that data can be recreated as needed. Cyclical models, in which data flow in a virtuous circle of uses and reuses, are better suited for irreplaceable observational data that may retain value indefinitely. In astronomy, for example, observations from one generation of telescopes may become calibration and modeling data for the next generation, whether digital sky surveys or glass plates. The value and reusability of data can be enhanced through investments in knowledge infrastructures, especially digital curation and preservation. Determining what data to keep, why, how, and for how long, is the challenge of our day.Keywordsastronomy, curation, data, digital curation, life cycles, observations, preservation, reuse, science, stewardship