NSF PILOT STUDY

Cyberinfrastructure Center of Excellence

Publications

  • NEON IdM Experiences - Working with the CI CoE Pilot to Solve Identity Management Challenges
    Abstract: This paper details experience from collaborative efforts between the NSF Cyberinfrastructure Center of Excellence (CI CoE) Pilot’s Identity Management Working Group and staff from the National Ecological Observatory Network (NEON) to develop improvements to the NEON Data Portal as well as the products of these collaborative efforts.
    Venue: 2019 NSF Cybersecurity Summit for Large Facilities and Cyberinfrastructure
    Authors: R. Kiser, T. Fleury, C. Laney, J. Sampson, S. Sons
    [link]
    [PDF]
  • Cyberinfrastructure Center of Excellence Pilot: Connecting Large Facilities Cyberinfrastructure
    Abstract: The National Science Foundation’s Large Facilities are major, multi-user research facilities that operate and manage sophisticated and diverse research instruments and platforms (e.g., large telescopes, interferometers, distributed sensor arrays) that serve a variety of scientific disciplines, from astronomy and physics to geology and biology and beyond. Large Facilities are increasingly dependent on advanced cyberinfrastructure (i.e., computing, data, and software systems; networking; and associ- ated human capital) to enable the broad delivery and analysis of facility-generated data. These cyberinfrastructure tools enable scientists and the public to gain new insights into fundamental questions about the structure and history of the universe, the world we live in today, and how our environment may change in the coming decades. This paper describes a pilot project that aims to develop a model for a Cyberinfrastructure Center of Excellence (CI CoE) that facilitates community building and knowledge sharing, and that disseminates and applies best practices and innovative solutions for facility CI.
    Venue: Escience 2019
    Authors: E. Deelman, A. Mandal, V. Pascucci, S. Sons, J. Wyngaard, C. F. Vardeman II, S. Petruzza, I. Baldin, L. Christopherson, R. Mitchell, L. Pottier, M. Rynge, E. Scott†, K Vahi, M. Kogank, J. A. Mann, T. Gulbransen, D. Allen, D. Barlow, S. Bonarrigo, C. Clark, L. Goldman, T. Goulden, P. Harvey, D. Hulsander, S. Jacobs, C. Laney, I. Lobo-Padilla, J. Sampson, J. Staarmann, S. Stone
    [PDF]
  • Exploration of Workflow Management Systems Emerging Features from Users Perspectives
    Abstract: There has been a recent emergence of new workflowapplications focused on data analytics and machine learning.This emergence has precipitated a change in the workflowmanagement landscape, causing the development of new data-oriented workflow management systems (WMSs) as opposed tothe earlier standard of task-oriented WMSs. In this paper, wesummarize three general workflow use-cases and explore theunique requirements of each use-case in order to understandhow WMSs from both workflow management models (task-driven workflow management models and data-driven workflowmanagement models) meet the requirements of each workflowuse-case from the user’s perspective. We analyze the applicabilityof the two main workflow models by carefully describing eachmodel and by providing an examination of the different variationsof WMSs that fall under the task-driven model. To illustratethe strengths and weaknesses of each workflow managementmodel, we summarize the key features of four production-readyWMSs: Pegasus, Makeflow, Apache Airflow, and Pachyderm.Of these production-ready WMSs, three belong to the task-driven workflow management model (i.e., Pegasus, Makeflow,Apache Airflow) and one belongs to the data-driven workflowmanagement model (i.e., Pachyderm). To deepen our analysisof the four WMSs examined in this paper, we implement threereal-world use-cases to highlight the specifications and featuresof each WMS. The application of these real-world use-casesdemonstrates how each workflow management model operateswith the different applications. We present our final assessmentof each WMS after considering the following factors: usability,performance, ease of deployment, and relevance. The purpose ofthis work is to offer insights from the user’s perspective into theresearch challenges that WMSs currently face due to the evolvingworkflow landscape.
    Venue: 14th WORKS Workshop
    Authors: R. Mitchell, L. Pottier, S. Jacobs, R. Ferreira da Silva, M. Rynge, K. Vahi, E. Deelman
    [link]
    [PDF]