A Distributed Infrastructure to Support Scientific Experiments

Classe, Tadeu Moreira de; Braga, Regina; David, José; Campos, Fernanda; Arbex, Wagner

doi:10.1007/s10723-017-9401-7

Cited by 10 publications

(5 citation statements)

References 31 publications

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“…The BlockFlow architecture, available at 13 , was divided into two modules: on-chain, and off-chain 14 . The off-chain module comprises the RESTful API web service, Client, Wrapper, and Model layers.…”

Section: Implementation Technologiesmentioning

confidence: 99%

“…Raft is the consensus protocol used. 7 Request flows to the Client layer (i) start peers, (ii) create channels, (iii) create identities, (iv) install chaincode, (v) instantiate chaincode Source: Prepared by the author 13 https:// github. com/ Raian eQC/ block flow-trust-prove nance.…”

Section: Implementation Technologiesmentioning

confidence: 99%

“…The advancement of modern science increasingly depends on interaction between scientists and the effective use of collective intelligence. Scientists are being gradually driven to collaborate and share information in distributed scenarios, as well as to reuse data from their peers [2,6,13,35,61]. Over the last decade, the data-oriented science paradigm has become a widespread reality [32][33][34].…”

Section: Introductionmentioning

confidence: 99%

“…It is not our aim to detail E-SECO platform. In[2] and[13] a detailed specification of E-SECO is provided.…”

mentioning

confidence: 99%

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A Blockchain-Based Architecture for Trust in Collaborative Scientific Experimentation

et al. 2022

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In scientific collaboration, data sharing, the exchange of ideas and results are essential to knowledge construction and the development of science. Hence, we must guarantee interoperability, privacy, traceability (reinforcing transparency), and trust. Provenance has been widely recognized for providing a history of the steps taken in scientific experiments. Consequently, we must support traceability, assisting in scientific results’ reproducibility. One of the technologies that can enhance trust in collaborative scientific experimentation is blockchain. This work proposes an architecture, named BlockFlow, based on blockchain, provenance, and cloud infrastructure to bring trust and traceability in the execution of collaborative scientific experiments. The proposed architecture is implemented on Hyperledger, and a scenario about the genomic sequencing of the SARS-CoV-2 coronavirus is used to evaluate the architecture, discussing the benefits of providing traceability and trust in collaborative scientific experimentation. Furthermore, the architecture addresses the heterogeneity of shared data, facilitating interpretation by geographically distributed researchers and analysis of such data. Through a blockchain-based architecture that provides support on provenance and blockchain, we can enhance data sharing, traceability, and trust in collaborative scientific experiments.

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Section: Implementation Technologiesmentioning

confidence: 99%

Section: Implementation Technologiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…It is not our aim to detail E-SECO platform. In[2] and[13] a detailed specification of E-SECO is provided.…”

mentioning

confidence: 99%

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A Blockchain-Based Architecture for Trust in Collaborative Scientific Experimentation

et al. 2022

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“…The importance of collaboration among researchers has led the development of social environments that support the whole lifecycle of experiments in scientific scenarios. E-ScienceNet [Classe at al. 2017] aims to provide support for geographically distributed researchers in the processes of creating, implementing and sharing experiments.…”

Section: Introductionmentioning

confidence: 99%

Functional Requirements for Developing ERAS - A Portal to Support Collaborative Geomechanical Simulations*

Lima¹,

Lemos²,

Pereira³

et al. 2018

Anais Do Brazilian E-Science Workshop (BreSci)

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One of the most important tasks in geomechanical research is executing analytical and numerical simulations to understand geomechanical phenomena. In order to attain this objective, researchers have to prepare data to perform the simulations, build the models that define the appropriate physical representation and the mathematical modeling of the problem, run a computer system capable of simulating the phenomenon, and visualize and interpret the results. This paper presents the main functional requirements to support the development of solutions that encompass the simulation of geomechanical problems, taking into account a collaborative environment with access to an efficient computer infrastructure. The paper also describes ERAS, a portal developed according to these requirements, highlighting the advantages it brings to researchers in this area. Resumo. Uma das tarefas mais importantes na pesquisa de geomecânica é a execução de simulação numérica e analítica para compreensão dos fenômenos geomecânicos. Com este objetivo, os pesquisadores preparam os dados para realizar as simulações do problema em questão; constroem o modelo que define a representação física apropriada e a modelagem matemática do problema; executam a computação capaz de simular o fenômeno estudado; e visualizam e interpretam os resultados. Este artigo apresenta os principais requisitos funcionais para apoio ao desenvolvimento de soluções que envolvam simulação de problemas geomecânicos, considerando um ambiente colaborativo com acesso a uma infraestrutura computacional eficiente. O artigo também apresenta o ERAS, um portal que está sendo desenvolvido de acordo com estes requisitos, destacando as vantagens que ele traz aos pesquisadores da área.

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