Data Accessibility, Reproducibility and Trustworthiness with LAGO Data Repositories

Mayo-García, Rafael; Núñez, Luis A.; Asorey, H.; Rodríguez-Pascual, Manuel; Ramirez, Dennis Cazar; Torres-Niño, L.

doi:10.22323/1.236.0672

Cited by 3 publications

(1 citation statement)

References 10 publications

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“…Cada vez más, será indispensable adhesión a protocolos de registro de datos durante la investigación. Se confía en un investigador o un grupo de investigación basado en la meticulosidad y seguimiento estricto de estos protocolos de descubrimiento con los cuales respalda o respaldan sus resultados [37]. La confianza en la consulta automática entre repositorios de datos y entre aplicaciones y repositorio se fundamentará en la calidad de los metadatos consecuencia del seguimiento de los protocolos.…”

Section: Conclusionesunclassified

Academia, datos y reproducibilidad de la ciencia

Martínez-Méndez¹,

Núñez²

2020

revuin

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La pandemia de COVID-19 ha catalizado una serie de prácticas académicas y cuando la superemos, la geografía y, sobre todo la dinámica de los grupos de investigación será otra. Quizá seremos máseficaces, peroel rasgo que será másindeleble de ese cambio lo constituirá la incorporación cotidiana de prácticas de ciencia abierta, repetible y reproducible. El cambio cualitativo de la investigación a la “e-investigación”, describe nuevas formas de producción y diseminación del conocimiento e impone nuevas metodologías para manejar, administrar, analizar y preservar este “diluvio de datos”. La repetibilidad y la reproducibilidad de los resultados científicos en la ciencia centrada en datos ha sido detectado como un un problema creciente. Las publicaciones académicas están llamadas a transformarse, exigiendo acceso a los datos y aplicaciones computacionales que soportan los resultados. En esta nota editorial comentamos y reflexionamos sobre algunas de las metodologíasy herramientas que se disponen para promover la repetibilidad/reproducibilidad de los experimentos. Discutimos el enfoque metodológico que emerge del Instituto Turing del Reino Unido. Presentamos una evaluaciónde las herramientas para construir repositorios de datos que existen actualmente.

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Section: Conclusionesunclassified

Academia, datos y reproducibilidad de la ciencia

Martínez-Méndez¹,

Núñez²

2020

revuin

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The data acquisition system of the Latin American Giant Observatory (LAGO)

Haro¹,

Arnaldi²,

Alvarez³

et al. 2016

Nuclear Instruments and Methods in Physics Research Section A:

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LAGO is an extended cosmic ray observatory composed of water-Cherenkov detectors (WCD) placed throughout Latin America. It is dedicated to the study of various issues related to astrophysics, space weather and atmospheric physics at the regional scale. In this paper we present the design and implementation of the front-end electronics and the data acquisition system for readout of the WCDs of LAGO. The system consists of preamplifiers and a digital board sending data to a computer via an USB interface. The analog signals are acquired from three independent channels at a maximum rate of $ 1.2 Â 10 5 pulses per second and a sampling rate of 40 MHz. To avoid false trigger due to baseline fluctuations, we present in this work a baseline correction algorithm that makes it possible to use WCDs to study variations of the environmental radiation. A data logging software has been designed to format the received data. It also enables an easy access to the data for an off-line analysis, together with the operational conditions and environmental information. The system is currently used at different sites of LAGO.

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The Latin American Giant Observatory: A Successful Collaboration in Latin America Based on Cosmic Rays and Computer Science Domains

Asorey

Núñez

Suárez-Durán

et al. 2016

2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)

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In this work the strategy of the Latin American Giant Observatory (LAGO) to build a Latin American collaboration is presented. Installing Cosmic Rays detectors settled all around the Continent, from Mexico to the Antarctica, this collaboration is forming a community that embraces both high energy physicist and computer scientists. This is so because the data that are measured must be analytical processed and due to the fact that a priori and a posteriori simulations representing the effects of the radiation must be performed. To perform the calculi, customized codes have been implemented by the collaboration. With regard to the huge amount of data emerging from this network of sensors and from the computational simulations performed in a diversity of computing architectures and e-infrastructures, an effort is being carried out to catalog and preserve a vast amount of data produced by the waterCherenkov Detector network and the complete LAGO simulation workflow that characterize each site. Metadata, Permanent Identifiers and the facilities from the LAGO Data Repository are described in this work jointly with the simulation codes used. These initiatives allow researchers to produce and find data and to directly use them in a code running by means of a Science Gateway that provides access to different clusters, Grid and Cloud infrastructures worldwide.

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Data Accessibility, Reproducibility and Trustworthiness with LAGO Data Repositories

Cited by 3 publications

References 10 publications

Academia, datos y reproducibilidad de la ciencia

Academia, datos y reproducibilidad de la ciencia

The data acquisition system of the Latin American Giant Observatory (LAGO)

The Latin American Giant Observatory: A Successful Collaboration in Latin America Based on Cosmic Rays and Computer Science Domains

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