Open Data Science
Open Data Science
复制标题
开放数据科学
DOI：
10.1007/978-3-030-01768-2_3
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Leo Lahti
中科院分区：
文献类型：
--
作者：
Leo Lahti
数据、方法和协作网络的日益开放为研究、公民科学和工业创造了新的机会。尽管现在可以通过程序界面、压缩档案和可下载电子表格访问开放许可的科学、政府和机构数据集，但开放数据流的全部潜力的实现关键取决于有针对性的数据分析方法的可用性，以及能够从这些数字资源中获得价值的用户社区。可互操作的软件库已成为现代统计数据分析的核心要素，弥合了理论与实践之间的差距，而开放的开发人员社区已成为研究软件开发的强大驱动力。从十年的社区参与中汲取见解，我提出了开放数据科学的概念，它指的是由开放数据，开放方法和开放协作实现的新形式的研究。
The increasing openness of data, methods, and collaboration networks has created new opportunities for research, citizen science, and industry. Whereas openly licensed scientific, governmental, and institutional data sets can now be accessed through programmatic interfaces, compressed archives, and downloadable spreadsheets, realizing the full potential of open data streams depends critically on the availability of targeted data analytical methods, and on user communities that can derive value from these digital resources. Interoperable software libraries have become a central element in modern statistical data analysis, bridging the gap between theory and practice, while open developer communities have emerged as a powerful driver of research software development. Drawing insights from a decade of community engagement, I propose the concept of open data science, which refers to the new forms of research enabled by open data, open methods, and open collaboration.
影响因子：
5.8
作者：
Carpenter, Bob;Gelman, Andrew;Riddell, Allen
通讯作者：
Riddell, Allen