Examining the Challenges of Scientific Workflows
Abstract
Workflows have emerged as a paradigm for representing and managing complex distributed computations and are used to accelerate the pace of scientific progress. A recent National Science Foundation workshop brought together domain, computer, and social scientists to discuss requirements of future scientific applications and the challenges they present to current workflow technologies.
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Scientific knowledge can also be used to advance other aspects of data science, such as the design of scientific workflows or the generation of model simulations.
“Scientific knowledge can also be used to advance other aspects of data science, e.g., the design of scientific work-flows [83], [84] or the generation of model simulations [85].”
From Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data (2017) · cites this paper as [84]
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- Authors
- Gil, Y., Deelman, E., Ellisman, M., Fahringer, T., Fox, G., Gannon, D., Goble, C., Livny, M., Moreau, L., & Myers, J.
- Affiliations
- University of Southern California (US)
- University of California San Diego (US)
- Universität Innsbruck (AT)
- Indiana University (US)
- University of Manchester (GB)
- University of Wisconsin System (US)
- University of Southampton (GB)
- National Center for Supercomputing Applications (US)
- ORCID
- Venue
- Computer
- Published
- 2007-12
- Volume
- 40
- Issue
- 12
- Pages
- 24-32
- ISSN
- 0018-9162 (ISSN-L)
- OpenAlex
- W2115570304
- Cited by
- 518
- References
- 0
- Citations by year
- 2026: 4 · 2025: 6 · 2024: 7 · 2023: 7 · 2022: 7 · 2021: 9 · 2020: 22 · 2019: 15 · 2018: 16 · 2017: 33 · 2016: 20 · 2015: 37 · 2014: 44 · 2013: 43 · 2012: 40
- FWCI
- 110.64
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Computer (publishedVersion)
- ePrints Soton (University of Southampton) (acceptedVersion)
- Research Explorer (The University of Manchester) (submittedVersion, public-domain)
- Funders
- National Science Foundation
- Engineering and Physical Sciences Research Council (EP/D044324/1)
- Division of Information and Intelligent Systems
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
- Physical Sciences › Computer Science › Computer Networks and Communications › Distributed and Parallel Computing Systems
- Social Sciences › Business, Management and Accounting › Management Information Systems › Business Process Modeling and Analysis
- Keywords
- scientific workflows, workflow technology, distributed computing, workflow management, scientific applications
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