Data sharing by scientists: practices and perceptions.
Data sharing by scientists: practices and perceptions.
复制标题
DOI：
10.1371/journal.pone.0021101
复制
发表时间：
2011
期刊：
影响因子：
3.7
通讯作者：
Frame M
中科院分区：
文献类型：
--
作者：
Tenopir C;Allard S;Douglass K;Aydinoglu AU;Wu L;Read E;Manoff M;Frame M
21世纪的科学研究比过去更加数据密集和协作。研究研究人员的数据实践——数据可及性、发现、再利用、保存，特别是数据共享——是很重要的。数据共享是科学方法的重要组成部分，允许验证结果并从先前的结果扩展研究。共有1329名科学家参与了这项调查，探讨了当前的数据共享实践以及对数据共享障碍和推动因素的看法。由于各种原因，包括时间不足和缺乏资金，科学家没有将他们的数据以电子方式提供给其他人。大多数应答者对他们目前对数据或研究生命周期的初始和短期部分（收集他们的研究数据；搜索、描述或编目、分析和短期存储他们的数据）的过程感到满意，但对长期数据保存不满意。许多组织不为他们的研究人员提供短期和长期的数据管理支持。如果满足某些条件（如正式引用和共享转载），受访者同意他们愿意分享他们的数据。基于主要资助机构、学科、年龄、工作重点和世界区域，数据管理实践也存在显著差异和方法。有效数据共享和保存的障碍深深植根于研究过程的实践和文化以及研究人员本身。美国国家科学基金会和其他联邦机构对数据管理计划的新授权，以及全世界对共享和保存数据需求的关注，可能会导致变化。诸如美国国家科学基金会（nsf）赞助的DataNET（包括DataONE等项目）这样的大型项目将为这个问题带来关注和资源，并使科学家更容易应用可靠的数据管理原则。
Scientific research in the 21st century is more data intensive and collaborative than in the past. It is important to study the data practices of researchers – data accessibility, discovery, re-use, preservation and, particularly, data sharing. Data sharing is a valuable part of the scientific method allowing for verification of results and extending research from prior results. A total of 1329 scientists participated in this survey exploring current data sharing practices and perceptions of the barriers and enablers of data sharing. Scientists do not make their data electronically available to others for various reasons, including insufficient time and lack of funding. Most respondents are satisfied with their current processes for the initial and short-term parts of the data or research lifecycle (collecting their research data; searching for, describing or cataloging, analyzing, and short-term storage of their data) but are not satisfied with long-term data preservation. Many organizations do not provide support to their researchers for data management both in the short- and long-term. If certain conditions are met (such as formal citation and sharing reprints) respondents agree they are willing to share their data. There are also significant differences and approaches in data management practices based on primary funding agency, subject discipline, age, work focus, and world region. Barriers to effective data sharing and preservation are deeply rooted in the practices and culture of the research process as well as the researchers themselves. New mandates for data management plans from NSF and other federal agencies and world-wide attention to the need to share and preserve data could lead to changes. Large scale programs, such as the NSF-sponsored DataNET (including projects like DataONE) will both bring attention and resources to the issue and make it easier for scientists to apply sound data management principles.