New science on the Open Science Grid

Pordes, R.; Altunay, Mine; Avery, P.; Bejan, Alina; Blackburn, K.; Blatecky, Alan; Gardner, R.; Kramer, Bill; Livny, Miron; McGee, John; Potekhin, M.; Quick, Rob; Olson, D. A.; Roy, Alain; Sehgal, Chander; Wenaus, T.; Wilde, Mike; Würthwein, F.

doi:10.1088/1742-6596/125/1/012070

Cited by 11 publications

(9 citation statements)

References 3 publications

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“…Advances in open science and all the related technologies that facilitated the open paradigm (Pordes et al. ; Cribb and Sari ), have vastly enriched the meaning of being open in the context of GIS. By synthesizing the most recent literature on various open initiatives, the open culture, especially in the context of open science, has multiple meanings, which typically includes the following: open data, open software, open hardware, open standards, open publication, open research, open funding, and open education/learning.…”

Section: The Emerging Open Culture and The Meaning Of Open Gismentioning

confidence: 99%

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Opportunities and Impediments for Open GIS

Sui

2014

Transactions in GIS

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The field of GIS (S for Systems, Sciences, Services, and Studies) is at a cross-road in the early 2010s. Aiming to link the multiple visions for the next phase of GIS development, this article suggests that the emerging open GIS should serve as a guiding concept. Contextualized in the broader literature of open science, this article proposes open GIS should include eight dimensions related to data, software, hardware, standards, research, publication, funding, and education. For the GIS community, open GIS offers four exciting opportunities: (1) technology-driven opportunities for addressing challenges posed by the (spatial) big data deluge; (2) application-led opportunities for confronting the problems of a rapidly changing planet; (3) curiosityinspired, crowd-powered opportunities for the development of an open and geographic citizen science; and (4) education-focused opportunities for implementing the vision of a spatial university. Although there are academic, legal, social/political, and environmental impediments for the practice of open GIS, open GIS will become increasingly important in shaping our research and educational agendas in the future.What's past is prologue; what's already happened merely sets the stage for what is to come.

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Section: The Emerging Open Culture and The Meaning Of Open Gismentioning

confidence: 99%

“…Recent advances in open science grid (Pordes et al. ), open cloud (Nelson, ), open distributed processing (Dunfey et al. ; Linington et al.…”

Section: The Emerging Open Culture and The Meaning Of Open Gismentioning

confidence: 99%

Opportunities and Impediments for Open GIS

Sui

2014

Transactions in GIS

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“…We define open services as self-contained processing applications embedded and reusable in a cloud platform environment. The brainlife.io platform allows running said Apps to process data available within the platform itself [66][67][68] . The concept of open service is akin to that of the Brain Imaging Data Structure Applications 69 as also introduced previously by others 70 .…”

Section: Background and Summarymentioning

confidence: 99%

The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services

Avesani¹,

McPherson²,

Hayashi³

et al. 2018

Preprint

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We describe the Open Diffusion Data Derivatives (O3D) repository: an integrated collection of preserved brain data derivatives and processing pipelines, published together using a single digital-object-identifier. The data derivatives were generated using modern diffusion-weighted magnetic resonance imaging data (dMRI) with diverse properties of resolution and signal-to-noise ratio. In addition to the data, we publish all processing pipelines (also referred to as open cloud services). The pipelines utilize modern methods for neuroimaging data processing (diffusion-signal modelling, fiber tracking, tractography evaluation, white matter segmentation, and structural connectome construction). The O3D open services can allow cognitive and clinical neuroscientists to run the connectome mapping algorithms on new, user-uploaded, data. Open source code implementing all O3D services is also provided to allow computational and computer scientists to reuse and extend the processing methods. Publishing both data-derivatives and integrated processing pipeline promotes practices for scientific reproducibility and data upcycling by providing open access to the research assets for utilization by multiple scientific communities.

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“…2) Open Science Grid : The Open Science Grid (OSG) [3] is a collaborative activity, where stakeholders come together to pool resources and build a shared environment for the common benefit of all stakeholders. The largest contributors of resources and also the largest users of the OSG are from the High Energy Physics community, specifically associated with the Large Hadron Collider (LHC), ATLAS and CMS (Compact Muon Solenoid) experiments.…”

Section: Production Grid Infrastructurementioning

confidence: 99%

Critical perspectives on large-scale distributed applications and production Grids

Jha

Parashar

Rana

et al. 2009

2009 10th IEEE/ACM International Conference on Grid Computing

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Abstract-It is generally accepted that the ability to develop large-scale distributed applications that are extensible and independent of infrastructure details has lagged seriously behind other developments in cyberinfrastructure. As the sophistication and scale of distributed infrastructure increases, the complexity of successfully developing and deploying distributed applications increases both quantitatively and in qualitatively newer ways. In this manuscript, we trace the evolution of a representative set of "state-of-the-art" distributed applications and production infrastructure; in doing so we aim to provide insight into the evolving sophistication of distributed applications -from simple generalizations of legacy static high-performance to applications composed of multiple loosely-coupled and dynamic components. The ultimate aim of this work is to highlight that even accounting for the fact that developing applications for distributed infrastructure is a difficult undertaking, there are suspiciously few novel and interesting distributed applications that utilize production Grid infrastructure. Along the way, we aim to provide an appreciation for the fact that developing distributed applications and the theory and practise of production Grid infrastructure have often not progressed in phase. Progress in the next phase and generation of distributed applications will require stronger coupling between the design and implementation of production infrastructure and the theory of distributed applications, including but not limited to explicit support for distributed application usage modes and advances that enable distributed applications to scale-out.

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New science on the Open Science Grid

Cited by 11 publications

References 3 publications

Opportunities and Impediments for Open GIS

Opportunities and Impediments for Open GIS

The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services

Critical perspectives on large-scale distributed applications and production Grids

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