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FAIR Publishing Guidelines for Spectral Data and Chemical Structures in Support of Chemistry and Related Disciplinary Communities

FAIR 发布光谱数据和化学结构指南以支持化学和相关学科界

基本信息

批准号：
1838958
负责人：
Leah McEwen
金额：
$ 2.46万
依托单位：
Cornell University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-01 至 2020-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1838958&HistoricalAwards=false
关键词：
FAIR Publishing Guidelines Spectral Data

项目摘要

In this project the PIs will convene a community workshop to establish publishing guidelines for sharing machine-readable files of commonly reported chemical data classes. The workshop organizers seek involvement from researchers, publishers, funding agencies, libraries, database and repository managers, tool developers, chemical societies, and standards organizations. Topics to discuss include formulating value propositions for data (that is, what data should be kept and for how long), and formulating criteria and stakeholder roles to better support data that are Findable, Accessible, Interoperable, and Reusable (FAIR). Several outcomes are expected, including best-practice publishing guidelines specifying FAIR criteria for spectral and chemical structure data; and workflow models for capturing, managing and sharing these data in domain repositories. This workshop will build on momentum from the Research Data Alliance (RDA), the International Union of Pure and Applied Chemistry (IUPAC), the American Chemical Society (ACS) and other related scientific societies. This project is supported by the National Science Foundation?s Public Access Initiative which is managed by the NSF Office of Advanced Cyberinfrastructure on behalf of the Foundation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

在该项目中，PI将召开一次社区研讨会，以制定关于共享常见报告化学数据类别的机器可读文件的出版准则。研讨会组织者寻求研究人员、出版商、资助机构、图书馆、数据库和知识库管理人员、工具开发人员、化学学会和标准组织的参与。讨论的主题包括制定数据的价值主张（即应该保留哪些数据以及保留多长时间），以及制定标准和利益相关者角色，以更好地支持可查找、可扩展、可互操作和可重用（FAIR）的数据。预计将取得若干成果，包括最佳做法出版指南，其中规定了光谱和化学结构数据的FAIR标准;以及用于在域存储库中捕获、管理和共享这些数据的工作流程模型。本次研讨会将建立在研究数据联盟（RDA），国际纯粹与应用化学联合会（IUPAC），美国化学学会（ACS）和其他相关科学学会的势头。这个项目是由国家科学基金会资助的。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。