Track 2: Customized Multi-tier Assistance, Training, and Computational Help (MATCH) for End User ACCESS to CI

轨道 2：为最终用户访问 CI 提供定制的多层协助、培训和计算帮助 (MATCH)

• 批准号: 2138286
• 负责人: Shelley Knuth
• 金额: $ 999.57万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2027-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2138286&HistoricalAwards=false
• 关键词: Track; Customized; Multi; tier; Assistance

Customized Multi-tier Assistance, Training, and Computational Help (MATCH) provides End User Support services as part of the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program. NSF-supported computational cyberinfrastructure (CI) has been highly successful in advancing science and engineering over the last few decades. The use of CI has become ubiquitous in research, from traditional fields such as bioinformatics, computational chemistry and astrophysics, to new areas including text interpretation, visual arts and other humanities. This shift is not only happening in large research labs at major institutions, but also increasingly at smaller institutions where researchers are also looking to make use of CI resources. Along with that success, there have been significant changes to the makeup and size of the user community, improvements to the underlying compute, storage, and networking platforms used, and radically different methods by which researchers and CI professionals communicate. These changes require a rethinking of the role of user support services and how they are delivered. To address this, MATCH proposes a new model for implementing user support services that will encourage cost-effective, scalable support that can reach a broader community. The MATCH project develops new approaches, content, services, technologies, and expertise to make it easier for NSF CI users to find and utilize the specific level and type of support needed to effectively carry out their research. With this strategy, the MATCH project expands the reach and impact of NSF CI, serving both traditional and new members of the research computing and data community.The MATCH approach comprises three major themes: (1) leverage modern information delivery systems to simplify user interfaces; (2) leverage experts from the community to develop training materials and instructions that can dramatically reduce the user learning curve for several increasingly important CI computational techniques; and (3) employ a matchmaking service that will maintain a database of specialist mentors and student mentees that can be matched with projects to provide the domain-specific expertise needed to leverage ACCESS resources. Specifically, MATCH employs a new ACCESS MATCH Portal (AMP) that will serve as the single front door for end users to obtain guided support and assistance. Expert-monitored Q&A platforms will ensure user questions are accurately answered and addressed in a timely fashion, and easy-to use user interfaces such as Open OnDemand and Pegasus will be enhanced and improved to further simplify CI use and provide context directed help when problems are encountered. The system matches community experts with user needs to create documentation and other training materials or provides personal interactions that address the current real world needs of ACCESS users. By restructuring end user support, MATCH creates a multi-level infrastructure capable of scaling to assist a growing research community with increasingly specialized support needs, enabling new discoveries at the forefront of science and society.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.

定制的多层帮助，培训和计算帮助（Match）提供最终用户支持服务，这是高级网络基础结构协调生态系统的一部分：服务与支持（访问）计划。在过去的几十年中，NSF支持的计算网络基础设施（CI）在推进科学和工程方面非常成功。从生物信息学，计算化学和天体物理学等传统领域到包括文本解释，视觉艺术和其他人文科学在内的新领域，CI的使用已变得无处不在。这种转变不仅在主要机构的大型研究实验室发生，而且在研究人员也希望利用CI资源的较小机构中越来越多。除了这一成功之外，用户社区的化妆和大小，所使用的基础计算，存储和网络平台的改进以及研究人员和CI专业人员进行交流的截然不同的方法。这些更改需要重新思考用户支持服务的作用及其提供方式。为了解决这个问题，Match提出了一个新的模型，用于实施用户支持服务，以鼓励可以实现更广泛社区的具有成本效益，可扩展的支持。比赛项目开发了新的方法，内容，服务，技术和专业知识，以使NSF CI用户更容易找到并利用有效进行研究所需的特定水平和支持。通过这种策略，比赛项目扩大了NSF CI的影响力和影响，为研究计算和数据社区的传统成员和新成员提供服务。该匹配方法包括三个主要主题：（1）利用现代信息传递系统来简化用户界面； （2）利用社区的专家来开发培训材料和说明，这些材料和说明可以大大减少几种日益重要的CI计算技术的用户学习曲线； （3）采用一项对接服务，该服务将维护专业导师和学生导师的数据库，这些数据库可以与项目相匹配，以提供利用访问资源所需的特定领域专业知识。具体而言，Match采用了新的访问匹配门户（AMP），该门户将作为最终用户获得指导支持和帮助的单个前门。专家监控的问答平台将确保用户问题准确地回答和及时解决，并易于使用用户界面，例如开放式Ondemand和Pegasus，并改进了Pegasus，以进一步简化CI的使用，并在遇到问题时提供有关上下文的有针对性的帮助。该系统将社区专家与用户相匹配，需要创建文档和其他培训材料，或提供个人互动，以满足访问用户的当前现实世界需求。通过重组最终用户支持，Match创建了一个多级基础架构，能够扩展能够扩展研究社区，以满足越来越专业的支持需求，从而使新发现处于科学和社会的最前沿。这一奖项反映了NSF的法定任务，并通过使用该基金会的知识分子功能和广泛的影响来评估NSF的法定任务，并被认为是值得的。

项目成果

The Multi-Tier Assistance, Training, and Computational Help (MATCH) Project, a Track 2 NSF ACCESS Initiative

多层援助、培训和计算帮助 (MATCH) 项目，属于 NSF ACCESS 计划的第 2 轨

• DOI: 10.22369/issn.2153-4136/13/2/4
• 发表时间: 2022
• 期刊: The Journal of Computational Science Education
• 作者: Knuth, Shelley L.;Ma, Julie;Adams, Joel C.;Chalker, Alan;Deelman, Ewa;Freeborn, Layla;Gazula, Vikram;Goodhue, John;Griffioen, James;Hudak, David
• 通讯作者: Hudak, David