EAGER-ORCID: Investigating ORCID as an accelerator of science of science policy
EAGER-ORCID:研究 ORCID 作为科学政策科学的加速器
基本信息
- 批准号:1149307
- 负责人:
- 金额:$ 26万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2011
- 资助国家:美国
- 起止时间:2011-10-01 至 2012-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The ability to attribute the results of scholarship to individual scholars is a fundamental enabler of a rigorous and data-driven science of science policy; it enables the automated linkage of research inputs to research outputs in an accurate and consistent manner. The research explores whether a new researcher identification and profile system can provide the basis for an automated attribution system.The goals are to refine and deploy a profile system by working with a small number of US research institutions and the federal government to explore how this system works in practice when used to acquire and provide access to information about US researchers. This research is suitable for the EAGER program because it is simultaneously high risk (there are many ways in which a researcher identity system can fail, including technical, institutional, and sociological) and high reward (it can fundamentally change the way in which scientific activity is documented).Intellectual Merit: The attribution problem is extremely complex. There are technical challenges such as how to generate unique researcher identifiers, match those identifiers with research outputs such as publications and patents and maintain large numbers of researcher profiles in a reliable and efficient manner. There are human computer interface issues, such as privacy concerns and user-friendly claiming mechanisms. There are also substantive social issues such as incentivizing and rewarding participation as well as achieving network effects.Broader impacts: The researcher identifier and profile system to be developed and evaluated in this project has benefits well beyond science policy. Researcher profiles can be used to streamline grant application, publication manuscript, and employment application processes. Researchers could use the approach to include all their contributions to the scholarly record, such as peer review, data curation, and software development. By making data about research and researchers more visible, profiles can also help researchers locate potential collaborators and develop networks. Research institutions can use such profiles to help them to evaluate the research outputs associated with specific research teams, departments, and/or institutions, and to support the job recruitment process. In all cases, profiles will enable the identification of strong areas of research and to track the publications of their faculty. Scholarly societies could use profiles to enhance their public member profiles. Publishers could use profiles to track authors and reviewers in their journal submission systems, with the ability to screen effectively for conflicts of interest. Reliable linkage among articles by the same authors and their collaborators could help promote the discovery of related scholarly works.
将学术成果归功于个别学者的能力是严格和数据驱动的科学政策科学的基本推动力;它使研究投入与研究产出能够以准确和一致的方式自动联系起来。 该研究探讨了一个新的研究人员识别和配置文件系统是否可以为自动归因系统提供基础。其目标是通过与少数美国研究机构和联邦政府合作,完善和部署一个配置文件系统,以探索该系统在获取和提供美国研究人员信息时的实际工作方式。 这项研究适合EAGER计划,因为它同时具有高风险(研究人员身份系统可能会在许多方面失败,包括技术,机构和社会学)和高回报(它可以从根本上改变科学活动的记录方式)。智力优点:归因问题非常复杂。 存在着技术挑战,例如如何生成独特的研究人员标识符,将这些标识符与出版物和专利等研究成果相匹配,并以可靠和有效的方式维护大量研究人员的个人资料。 还有人机界面问题,如隐私问题和用户友好的索赔机制。 还有一些实质性的社会问题,如激励和奖励参与以及实现网络效应。更广泛的影响:本项目中开发和评估的研究人员识别和档案系统的好处远远超出了科学政策。研究人员的个人资料可以用来简化赠款申请,出版手稿和就业申请过程。研究人员可以使用这种方法将他们的所有贡献纳入学术记录,例如同行评审,数据管理和软件开发。通过使研究和研究人员的数据更加可见,配置文件还可以帮助研究人员找到潜在的合作者并建立网络。研究机构可以使用这些配置文件来帮助他们评估与特定研究团队,部门和/或机构相关的研究成果,并支持招聘过程。在所有情况下,配置文件将能够确定强有力的研究领域,并跟踪其教师的出版物。学术团体可以使用个人资料来提高其公众成员的个人资料。 出版商可以使用配置文件在其期刊提交系统中跟踪作者和审稿人,并能够有效地筛选利益冲突。同一作者及其合作者的文章之间的可靠链接可以帮助促进相关学术著作的发现。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Ian Foster其他文献
GreenFaaS: Maximizing Energy Efficiency of HPC Workloads with FaaS
GreenFaaS:利用 FaaS 最大限度提高 HPC 工作负载的能源效率
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Alok V. Kamatar;Valerie Hayot;Y. Babuji;André Bauer;Gourav Rattihalli;Ninad Hogade;D. Milojicic;Kyle Chard;Ian Foster - 通讯作者:
Ian Foster
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies
DeepSpeed4Science 计划:通过复杂的人工智能系统技术实现大规模科学发现
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
S. Song;Bonnie Kruft;Minjia Zhang;Conglong Li;Shiyang Chen;Chengming Zhang;Masahiro Tanaka;Xiaoxia Wu;Jeff Rasley;A. A. Awan;Connor Holmes;Martin Cai;Adam Ghanem;Zhongzhu Zhou;Yuxiong He;Christopher Bishop;Max Welling;Tie;Christian Bodnar;Johannes Brandsetter;W. Bruinsma;Chan Cao;Yuan Chen;Peggy Dai;P. Garvan;Liang He;E. Heider;Pipi Hu;Peiran Jin;Fusong Ju;Yatao Li;Chang Liu;Renqian Luo;Qilong Meng;Frank Noé;Tao Qin;Janwei Zhu;Bin Shao;Yu Shi;Wen;Gregor Simm;Megan Stanley;Lixin Sun;Yue Wang;Tong Wang;Zun Wang;Lijun Wu;Yingce Xia;Leo Xia;Shufang Xie;Shuxin Zheng;Jianwei Zhu;Pete Luferenko;Divya Kumar;Jonathan Weyn;Ruixiong Zhang;Sylwester Klocek;V. Vragov;Mohammed Alquraishi;Gustaf Ahdritz;C. Floristean;Cristina Negri;R. Kotamarthi;V. Vishwanath;Arvind Ramanathan;Sam Foreman;Kyle Hippe;T. Arcomano;R. Maulik;Max Zvyagin;Alexander Brace;Bin Zhang;Cindy Orozco Bohorquez;Austin R. Clyde;B. Kale;Danilo Perez;Heng Ma;Carla M. Mann;Michael Irvin;J. G. Pauloski;Logan Ward;Valerie Hayot;M. Emani;Zhen Xie;Diangen Lin;Maulik Shukla;Thomas Gibbs;Ian Foster;James J. Davis;M. Papka;Thomas Brettin;Prasanna Balaprakash;Gina Tourassi;John P. Gounley;Heidi Hanson;T. Potok;Massimiliano Lupo Pasini;Kate Evans;Dan Lu;D. Lunga;Junqi Yin;Sajal Dash;Feiyi Wang;M. Shankar;Isaac Lyngaas;Xiao Wang;Guojing Cong;Peifeng Zhang;Ming Fan;Siyan Liu;A. Hoisie;Shinjae Yoo;Yihui Ren;William Tang;K. Felker;Alexey Svyatkovskiy;Hang Liu;Ashwin Aji;Angela Dalton;Michael Schulte;Karl Schulz;Yuntian Deng;Weili Nie;Josh Romero;Christian Dallago;Arash Vahdat;Chaowei Xiao;Anima Anandkumar;R. Stevens - 通讯作者:
R. Stevens
An optical microscopy system for 3 D dynamic imagingRandy
用于 3D 动态成像的光学显微镜系统Randy
- DOI:
- 发表时间:
2007 - 期刊:
- 影响因子:0
- 作者:
R. Hudson;John N. Aarsvold;Chin;Jie Chen;Peter Davies;T. Disz;Ian Foster;Melvin Griem;Man K Kwong;B. Lin - 通讯作者:
B. Lin
Review of low-cost self-driving laboratories in chemistry and materials science: the “frugal twin” concept
化学与材料科学低成本自动驾驶实验室综述:“节俭双胞胎”概念
- DOI:
10.1039/d3dd00223c - 发表时间:
2024-05-15 - 期刊:
- 影响因子:5.600
- 作者:
Stanley Lo;Sterling G. Baird;Joshua Schrier;Ben Blaiszik;Nessa Carson;Ian Foster;Andrés Aguilar-Granda;Sergei V. Kalinin;Benji Maruyama;Maria Politi;Helen Tran;Taylor D. Sparks;Alán Aspuru-Guzik - 通讯作者:
Alán Aspuru-Guzik
Exploring Benchmarks for Self-Driving Labs using Color Matching
使用颜色匹配探索自动驾驶实验室的基准
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Tobias Ginsburg;Kyle Hippe;Ryan Lewis;Aileen Cleary;D. Ozgulbas;Rory Butler;Casey Stone;Abraham Stroka;Rafael Vescovi;Ian Foster - 通讯作者:
Ian Foster
Ian Foster的其他文献
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{{ truncateString('Ian Foster', 18)}}的其他基金
Collaborative Research: NSF Workshop on Automated, Programmable and Self Driving Labs
合作研究:NSF 自动化、可编程和自动驾驶实验室研讨会
- 批准号:
2335910 - 财政年份:2023
- 资助金额:
$ 26万 - 项目类别:
Standard Grant
Frameworks: Garden: A FAIR Framework for Publishing and Applying AI Models for Translational Research in Science, Engineering, Education, and Industry
框架:Garden:用于发布和应用人工智能模型进行科学、工程、教育和工业转化研究的公平框架
- 批准号:
2209892 - 财政年份:2022
- 资助金额:
$ 26万 - 项目类别:
Standard Grant
Collaborative Research: OAC Core: ScaDL: New Approaches to Scaling Deep Learning for Science Applications on Supercomputers
协作研究:OAC 核心:ScaDL:在超级计算机上扩展深度学习科学应用的新方法
- 批准号:
2107511 - 财政年份:2021
- 资助金额:
$ 26万 - 项目类别:
Standard Grant
NSF Convergence Accelerator Track D: The Data Hypervisor: Orchestrating Data and Models
NSF 融合加速器轨道 D:数据管理程序:编排数据和模型
- 批准号:
2040718 - 财政年份:2020
- 资助金额:
$ 26万 - 项目类别:
Standard Grant
Collaborative Research: Frameworks: funcX: A Function Execution Service for Portability and Performance
协作研究:框架:funcX:可移植性和性能的函数执行服务
- 批准号:
2004894 - 财政年份:2020
- 资助金额:
$ 26万 - 项目类别:
Standard Grant
Virtual Data Set Services Enabling New Science at NSF Facilities
虚拟数据集服务在 NSF 设施中实现新科学
- 批准号:
1841531 - 财政年份:2018
- 资助金额:
$ 26万 - 项目类别:
Standard Grant
Framework: Software: HDR Globus Automate: A Distributed Research Automation Platform
框架:软件:HDR Globus Automate:分布式研究自动化平台
- 批准号:
1835890 - 财政年份:2018
- 资助金额:
$ 26万 - 项目类别:
Standard Grant
EAGER: Designing the OSN Software Platform
EAGER:设计 OSN 软件平台
- 批准号:
1836357 - 财政年份:2018
- 资助金额:
$ 26万 - 项目类别:
Standard Grant
BD Spokes: SPOKE: MIDWEST: Collaborative: Integrative Materials Design (IMaD): Leverage, Innovate, and Disseminate
BD 辐条:辐条:中西部:协作:集成材料设计 (IMaD):利用、创新和传播
- 批准号:
1636950 - 财政年份:2017
- 资助金额:
$ 26万 - 项目类别:
Standard Grant
Collaborative Research: CyberSEES:Type 2: Framework to Advance Climate, Economics, and Impact Investigations with Information Technology (FACE-IT)
合作研究:CyberSEES:类型 2:利用信息技术推进气候、经济和影响调查的框架 (FACE-IT)
- 批准号:
1331922 - 财政年份:2013
- 资助金额:
$ 26万 - 项目类别:
Standard Grant
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ORCID DE 2 – Consolidation of the ORCID Information Infrastructure in Germany
ORCID DE 2 – 德国 ORCID 信息基础设施的整合
- 批准号:
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