Abstract | ||
---|---|---|
Scientific workflows—models of computation that capture the orchestration of scientific codes to conduct in silico research—are gaining recognition as an attractive alternative to script-based orchestration. Even so, researchers developing scientific workflow technologies still face fundamental challenges, including developing the underlying science of scientific workflows. You can classify scientific-workflow environments according to three major phases of in silico research: discovery, production, and distribution. On the basis of this classification, scientists can make more-informed decisions regarding the adoption of particular workflow environments. |
Year | DOI | Venue |
---|---|---|
2008 | 10.1109/MS.2008.92 | IEEE Software |
Keywords | Field | DocType |
natural sciences computing,workflow management software,in silico research,scientific software,scientific workflows,script-based orchestration,programming environments and construction tools,software construction,workflow management | Data science,Scientific software,Systems engineering,Software engineering,Computer science,Collaborative software,Software construction,Orchestration (computing),Workflow,Software development | Journal |
Volume | Issue | ISSN |
25 | 4 | 0740-7459 |
Citations | PageRank | References |
13 | 0.57 | 10 |
Authors | ||
4 |
Name | Order | Citations | PageRank |
---|---|---|---|
David Woollard | 1 | 18 | 2.34 |
Nenad Medvidovic | 2 | 4926 | 344.86 |
Yolanda Gil | 3 | 4491 | 413.53 |
Chris A. Mattmann | 4 | 200 | 25.39 |