Workshop on Supporting Scientific Discovery through Norms and Practices for Software and Data Citation and Attribution

通过软件和数据引用和归属的规范和实践支持科学发现研讨会

• 批准号: 1448360
• 负责人: Stanley Ahalt
• 金额: $ 9.99万
• 依托单位: University of North Carolina at Chapel Hill
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1448360&HistoricalAwards=false
• 关键词: Workshop; Supporting; Scientific; Discovery; through

Scientific researchers, and particularly academic researchers, are embedded in a reputation economy. Tenure, promotion, and acclaim are achieved through influential research. There are few incentives for scientists to share data and software, and tenure and promotion decisions lack consideration of such activities; and to compound the problem, there are disincentives such as risking the loss of attribution. Some scientists distrust the public access model for software and data, and prefer to share data and software only by personal request, which assures attribution through personal contact and implicit social contract. There is also a lack of well-developed metrics with which to assess the impact and quality of scientific software and data. New practices and incentives are needed in the research community for software and data citation and attribution, so that data producers, software and tool developers, and data curators are credited for their contributions. This workshop will facilitate a national, interdisciplinary exploration of new norms and practices for software and data citation and attribution, with the goal of informing the Science of Science and Innovation Policy (SciSIP) and Software Infrastructure for Sustained Innovation (SI2) NSF programs. Social and technical challenges facing current software development and data generation efforts will be identified and participants will explore viable methods and metrics to support software and data attribution in the scientific research community. This workshop will address registration of software and data, repositories for software and data, methods for tracking software and data usage, software and data annotation, collecting and curating metadata on software and data, ensuring appropriate attribution by software and data users, alternatives to traditional publication models for attribution, adaptation of commercial models for software and data attribution, proportioning attribution metrics to match degree of effort and role in software development and data generation, and establishing reward metrics for open science. Workshop outcomes will include actionable plans to enable the broader research community to implement the software and data attribution practices that are identified and advanced by the participants of the workshop.

科学研究人员，尤其是学术研究人员嵌入了声誉经济中。权限，晋升和好评是通过有影响力的研究实现的。科学家几乎没有激励措施共享数据和软件，而任期和晋升决策缺乏对此类活动的考虑。为了使问题更加复杂，存在诸如冒着归因损失的风险。一些科学家不信任公共访问模型对软件和数据的不信任，并且只能通过个人请求共享数据和软件，这可以通过个人联系和隐性社会合同来确保归因。还缺乏发达的指标来评估科学软件和数据的影响和质量。 在研究社区中需要进行新的实践和激励措施，以供软件，数据引用和归因，以便数据生产者，软件和工具开发人员以及数据策展人的贡献都被认为。该研讨会将促进针对软件和数据引文和归因的新规范和实践的国家跨学科探索，目的是为科学与创新政策科学（SCISIP）和软件基础架构提供信息，以实现持续创新（SI2）NSF计划。将确定当前软件开发和数据生成工作面临的社会和技术挑战，参与者将探索可行的方法和指标，以支持科学研究社区中的软件和数据归因。该研讨会将解决软件和数据的注册，软件和数据存储库，用于跟踪软件和数据使用的方法，软件和数据注释，收集和策划软件和数据上的元数据，确保软件和数据用户的适当归因，传统的替代方案出版归因模型，用于软件的商业模型和数据归因的商业模型，将归因指标比例为符合努力和在软件开发和数据生成中的作用的程度以及为开放科学建立奖励指标。研讨会的成果将包括可行的计划，以使更广泛的研究社区能够实施由研讨会参与者确定和提出的软件和数据归因实践。