Name
Abstract | ||
|---|---|---|
Recent years have seen a dramatic increase in research and development of scientific workflow systems. These systems promise to make scientists more productive by automating data-driven and compute-intensive analyses. Despite many early achievements, the long-term success of scientific workflow technology critically depends on making these systems useable by ''mere mortals'', i.e., scientists who have a very good idea of the analysis methods they wish to assemble, but who are neither software developers nor scripting-language experts. With these users in mind, we identify a set of desiderata for scientific workflow systems crucial for enabling scientists to model and design the workflows they wish to automate themselves. As a first step towards meeting these requirements, we also show how the collection-oriented modeling and design (comad) approach for scientific workflows, implemented within the Kepler system, can help provide these critical, design-oriented capabilities to scientists. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1016/j.future.2008.06.013 | Future Generation Comp. Syst. |
Keywords | Field | DocType |
software development,collection,workflow,scripting language,resilience | Data science,Workflow design,Workflow technology,Computer science,Knowledge management,Software,Kepler,Workflow engine,Workflow,Distributed computing | Journal |
Volume | Issue | ISSN |
25 | 5 | 0167-739X |
Citations | PageRank | References |
73 | 3.72 | 34 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Timothy M. McPhillips | 1 | 442 | 31.41 |
| Shawn Bowers | 2 | 1223 | 86.44 |
| Daniel Zinn | 3 | 198 | 13.43 |
| Bertram Ludäscher | 4 | 1879 | 239.67 |