2014 IEEE 10th International Conference on E-Science 2014
DOI: 10.1109/escience.2014.56
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Experiences with User-Centered Design for the Tigres Workflow API

Abstract: Scientific data volumes have been growing exponentially. This has resulted in the need for new tools that enable users to operate on and analyze data. Cyberinfrastructure tools, including workflow tools, that have been developed in the last few years has often fallen short of user needs and suffered from lack of wider adoption. User-centered Design (UCD) process has been used as an effective approach to develop usable software with high adoption rates. However, UCD has largely been applied for user-interfaces … Show more

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Cited by 21 publications
(25 citation statements)
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References 22 publications
(18 reference statements)
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“…Case study: Possible shapes of workflows are virtually infinite, however four major patterns, namely split, merge, sequence and parallel have been recognised to cover the basic needs of many scientific computational pipelines [13]. We consequently decided to conduct the experiments of Sections V-A, V-B and V-C using a diamond shape depicted in Fig.…”
Section: Resultsmentioning
confidence: 99%
“…Case study: Possible shapes of workflows are virtually infinite, however four major patterns, namely split, merge, sequence and parallel have been recognised to cover the basic needs of many scientific computational pipelines [13]. We consequently decided to conduct the experiments of Sections V-A, V-B and V-C using a diamond shape depicted in Fig.…”
Section: Resultsmentioning
confidence: 99%
“…The approach we used to develop FRAMES involved a combination of agile development principles and scientist-centered design (Ramakrishnan et al, 2014). Agile development uses short incremental development cycles with reassessment of priorities and solicitation of feedback after each cycle.…”
Section: Methodsmentioning
confidence: 99%
“…Though provenance tools have been created, such as Harvard's PASS system [MRBH+09], and though provenance standards are beginning to be created, such as via W3C [PROV], these tools and standards need to be embedded within data centers in a way that is clearly cognizant of the use environments, particularly including performance issues, and be expressly examined for their applicability to the unique challenges of extreme scale scientific computing integrity. Therefore, the nuanced provenance information must be captured to enable reproduction and perhaps even replay via an executable scientific workflow such as the DOEfunded Tigres project [RPH+14].…”
Section: Robust and Reliable Scientific Reproducibilitymentioning
confidence: 99%