The Virtual Data Collaboratory: A Regional Cyberinfrastructure for Collaborative Data-Driven Research

Parashar, Manish; Simonet, Anthony; Rodero, Iván; Ghahramani, Forough; Agnew, Grace; Jantz, Ron; Honavar, Vasant

doi:10.1109/mcse.2019.2908850

Cited by 11 publications

(4 citation statements)

References 8 publications

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“…Finally, the DMZ and DTNs have been used to develop a federated data collaboration architecture, where DTNs are used to support access to data within a collaboratory. Specifically, the Virtual Data Collaboratory (VDC) project [3] implements a data-DMZ that supports data sharing and data-driven collaborations through DTNs. It also integrates data from other sources such as LF.…”

Section: An Intelligent Data Discovery and Delivery Framework For Lfmentioning

confidence: 99%

“…However, as the number of such LF and their scale increases along with corresponding growth in the number, distribution, and diversity of their users, ensuring that LF data can be discovered, accessed, integrated, and analyzed in a timely manner is resulting in significant demands on LF cyberinfrastructure (CI) [3]. For example, the Ocean Observatory Initiative (OOI) [4] integrates over 1,250 instruments, producing over 25,000 data items and over 100,000 data products.…”

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confidence: 99%

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Toward Democratizing Access to Facilities Data: A Framework for Intelligent Data Discovery and Delivery

2022

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Data collected by large-scale instruments, observatories, and sensor networks, i.e., science facilities, are key enablers of scientific discoveries in many disciplines. However, ensuring that these data can be accessed, integrated, and analyzed in a democratized and timely manner remains a challenge. In this article, we explore how state-of-the-art techniques for data discovery and access can be adapted to facility data and develop a conceptual framework for intelligent data access and discovery.

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Section: An Intelligent Data Discovery and Delivery Framework For Lfmentioning

confidence: 99%

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confidence: 99%

Toward Democratizing Access to Facilities Data: A Framework for Intelligent Data Discovery and Delivery

2022

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“…Location of high-precision GPS sensor from the UNAVCO network in contiguous United States. The inset highlights the main Virtual Data Collaboratory Hubs (Parashar et al, 2017). …”

Section: Use Case Scenariosmentioning

confidence: 99%

Towards a computing continuum: Enabling edge-to-cloud integration for data-driven workflows

Balouek-Thomert

Renart

Zamani

et al. 2019

The International Journal of High Performance Computing Applica

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Dramatic changes in the technology landscape marked by increasing scales and pervasiveness of compute and data have resulted in the proliferation of edge applications aimed at effectively processing data in a timely manner. As the levels and fidelity of instrumentation increases and the types and volumes of available data grow, new classes of applications are being explored that seamlessly combine real-time data with complex models and data analytics to monitor and manage systems of interest. However, these applications require a fluid integration of resources at the edge, the core, and along the data path to support dynamic and data-driven application workflows, that is, they need to leverage a computing continuum. In this article, we present our vision for enabling such a computing continuum and specifically focus on enabling edge-to-cloud integration to support data-driven workflows. The research is driven by an online data-driven tsunami warning use case that is supported by the deployment of large-scale national environment observation systems. This article presents our overall approach as well as current status and next steps.

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“…Even the same teacher may give different scores to the same essay depending on their mood. In order to solve these problems, various online examination systems have been established [5]. For students who need to correct their answers to objective questions instead of wiping their answer cards, they only need to click on the corrected answer and the answer that needs to be corrected is corrected.…”

Section: Introductionmentioning

confidence: 99%

Construction of Intelligent Evaluation Platform Based on Random Matrix iWrite College English Writing

Gao

Xiao-da

et al. 2022

Mathematical Problems in Engineering

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The advantages of iWrite English writing teaching and marking system 3.0 and the case study of English writing in higher education based on this system have a positive effect on forming a new model of English writing teaching in higher education under the background of Internet + and improving and solving the main problems of English writing teaching in higher education. Although the current intelligent marking systems have made a lot of achievements, they have not fundamentally solved the problem of the rationality of intelligent marking of subjective questions. In order to better perceive the sense of speech in English essays in depth and improve the rationality problem of intelligent marking, this study proposes a quantification of N-element sense of speech value based on correlation analysis and a scoring fitting algorithm for English essays based on rationality enhancement. The quantification of perceptual value is done by obtaining the N components of the composition and calculating their support in the corpus. In the daily teaching work, teachers should actively cooperate with the marking system to improve their own teaching level and explore ways and methods of students’ writing training, so as to cultivate more English talents. In addition, word features, sentence features, and chapter structure features were extracted from the essays to fit the English essay scores. Since not all students were able to complete the essays according to the requirements of the questions, a streaming scoring model was used to separate the normal essays from the low-scoring essays. The low-scoring essays were scored using the k-nearest neighbor algorithm, while the normal essays were fitted to the test takers’ scores using the support vector regression algorithm. Statistically, it was found that the essay scores also showed a certain normal distribution. The standard support vector regression algorithm is prone to data skewing problems, so this study addresses this problem by using a rationality enhancement method, which gives a corresponding penalty factor according to the distribution of the data set.

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The Virtual Data Collaboratory: A Regional Cyberinfrastructure for Collaborative Data-Driven Research

Cited by 11 publications

References 8 publications

Toward Democratizing Access to Facilities Data: A Framework for Intelligent Data Discovery and Delivery

Toward Democratizing Access to Facilities Data: A Framework for Intelligent Data Discovery and Delivery

Towards a computing continuum: Enabling edge-to-cloud integration for data-driven workflows

Construction of Intelligent Evaluation Platform Based on Random Matrix iWrite College English Writing

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