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

Volume 13, Issue 2 (December 2022), pp. 17–20

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@article{jocse-13-2-4,
  author={Shelley L. Knuth and Julie Ma and Joel C. Adams and Alan Chalker and Ewa Deelman and Layla Freeborn and Vikram Gazula and John Goodhue and James Griffioen and David Hudak and Andrew Pasquale and Dylan Perkins and Alana Romanella and Mats Rynge},
  title={The Multi-Tier Assistance, Training, and Computational Help (MATCH) Project, a Track 2 NSF ACCESS Initiative},
  journal={The Journal of Computational Science Education},
  year=2022,
  month=dec,
  volume=13,
  issue=2,
  pages={17--20},
  doi={https://doi.org/10.22369/issn.2153-4136/13/2/4}
}

NSF-supported cyberinfrastructure (CI) has been highly successful in advancing science and engineering over the last few decades. During that time, there have been significant changes in the size and composition of the participating community, the architecture and capacity of compute, storage, and networking platforms, and the methods by which researchers and CI professionals communicate. These changes require rethinking the role of research support services and how they are delivered. To address these changes and support an expanding community, MATCH is implementing a model for research support services in ACCESS that comprises three major themes: 1) leverage modern information delivery systems and simplify user interfaces to provide cost-effective, scalable support to a broader community of researchers, 2) engage experts from the community to develop training materials and instructions that can dramatically reduce the learning curve, 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. A new ACCESS Support Portal (ASP) will serve as the single front door for researchers to obtain guided support and assistance. The ASP will leverage emerging, curated tag taxonomies to identify and match inquiries with knowledge base content and expertise. Expert-monitored question and answer platforms will be created to ensure researcher questions are accurately answered and addressed in a timely fashion, and easy-to-use interfaces such as Open OnDemand and Pegasus will be enhanced to simplify CI use and provide context-aware directed help. The result will be a multi-level support infrastructure capable of scaling to serve a growing research community with increasingly specialized support needs, resulting in research discoveries previously hindered by researchers' inability to effectively utilize NSF CI resources. This paper will cover the components of the MATCH project and discuss how MATCH will engage and work with the ACCESS community.