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Title: Globus platform-as-a-service for collaborative science applications

Journal Article · · Concurrency and Computation. Practice and Experience
DOI:https://doi.org/10.1002/cpe.3262· OSTI ID:1233224
 [1];  [1];  [1];  [1]
  1. Argonne National Lab. and Univ. of Chicago, Chicago, IL (United States). Computation Inst.

Globus, developed as Software-as-a-Service (SaaS) for research data management, also provides APIs that constitute a flexible and powerful Platform-as-a-Service (PaaS) to which developers can outsource data management activities such as transfer and sharing, as well as identity, profile and group management. By providing these frequently important but always challenging capabilities as a service, accessible over the network, Globus PaaS streamlines web application development and makes it easy for individuals, teams, and institutions to create collaborative applications such as science gateways for science communities. We introduce the capabilities of this platform and review representative applications.

Research Organization:
Argonne National Laboratory (ANL), Argonne, IL (United States)
Sponsoring Organization:
USDOE; National Science Foundation (NSF); National Institutes of Health (NIH)
Grant/Contract Number:
AC02-06CH11357; OCI-1053575; OCI-0534113l; 5U24RR025736
OSTI ID:
1233224
Journal Information:
Concurrency and Computation. Practice and Experience, Vol. 27, Issue 2; ISSN 1532-0626
Publisher:
WileyCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 21 works
Citation information provided by
Web of Science

References (16)

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conference May 2011
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Cited By (4)

Cloud architecture for plant phenotyping research
  • Debauche, Olivier; Mahmoudi, Sidi Ahmed; De Cock, Nicolas
  • Concurrency and Computation: Practice and Experience, Vol. 32, Issue 17 https://doi.org/10.1002/cpe.5661
journal January 2020
Cloud computing for genomic data analysis and collaboration journal January 2018
Managing, Analysing, and Integrating Big Data in Medical Bioinformatics: Open Problems and Future Perspectives journal January 2014
Methodological challenges and analytic opportunities for modeling and interpreting Big Healthcare Data journal February 2016

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