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Little science confronts the data deluge: habitat ecology, embedded sensor networks, and digital libraries

机译:几乎没有科学面对数据洪流:栖息地生态,嵌入式传感器网络和数字图书馆

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摘要

e-Science promises to increase the pace of science via fast, distributed access to computational resources, analytical tools, and digital libraries. "Big science" fields such as physics and astronomy that collaborate around expensive instrumentation have constructed shared digital libraries to manage their data and documents, while "little science" research areas that gather data through hand-crafted fieldwork continue to manage their data locally. As habitat ecology researchers begin to deploy embedded sensor networks, they are confronting an array of challenges in capturing, organizing, and managing large amounts of data. The scientists and their partners in computer science and engineering make use of common datasets but interpret the data differently. Studies of this field in transition offer insights into the role of digital libraries in e-Science, how data practices evolve as science becomes more instrumented, and how scientists, computer scientists, and engineers collaborate around data. Among the lessons learned are that data on the same variables are gathered by multiple means, that data exist in many states and in many places, and that publication practices often drive data collection practices. Data sharing is embraced in principle but little sharing actually occurs, due to interrelated factors such as lack of demand, lack of standards, and concerns about publication, ownership, data quality, and ethics. We explore the implications of these findings for data policy and digital library architecture. Research reported here is affiliated with the Center for Embedded Networked Sensing.
机译:e-Science承诺通过对计算资源,分析工具和数字图书馆的快速,分布式访问来加快科学发展的步伐。围绕昂贵的仪器进行协作的物理和天文学等“大科学”领域已经建立了共享的数字图书馆来管理其数据和文档,而通过手工野外工作收集数据的“小科学”研究领域则继续在本地管理其数据。随着栖息地生态学研究人员开始部署嵌入式传感器网络,他们在捕获,组织和管理大量数据方面面临着一系列挑战。科学家及其在计算机科学与工程领域的合作伙伴利用通用数据集,但对数据的解释不同。对这一转型领域的研究提供了有关数字图书馆在电子科学中的作用,随着科学技术的发展,数据实践如何发展以及科学家,计算机科学家和工程师如何围绕数据进行协作的见解。在获得的经验教训中,可以通过多种方式收集有关同一变量的数据,该数据存在于许多州和许多地方,并且发布实践通常会推动数据收集实践。原则上包含数据共享,但是由于相互关联的因素(例如缺乏需求,缺乏标准以及对发布,所有权,数据质量和道德的担忧),实际上很少共享。我们探索这些发现对数据政策和数字图书馆体系结构的影响。此处报告的研究隶属于嵌入式网络传感中心。

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