Redes de investigación


Datos en abierto para instalaciones científico técnicas singulares basadas en aceleradores

Responsable: Joaquín José Gómez Camacho
Tipo de Proyecto/Ayuda: Plan Estatal 2021-2023 – Redes de Investigación
Referencia: RED2022-134332-I
Fecha de Inicio: 01-06-2023
Fecha de Finalización: 31-05-2026

Empresa/Organismo financiador/es:

  • Ministerio de Ciencia e Innovación

Socios:

  • Consorcio para la Construcción, Equipamiento y Explotación del Laboratorio de Luz Sincrotrón (Nicolás Soler)
  • Universidad Autónoma de Madrid (Gastón García López)

Equipo:

Contratados:

  • Técnicos/Personal Administrativo:
    • Carla Tatiana Muñoz Chimbo
    • Raúl Varela Ferrando

Resumen del proyecto:

Proyecto OPENDATA4ICTS

 

 

 

 

 

Referencia: RED2022-134332-I
Área: Ciencias Físicas
Subárea: Física de partículas y nuclear
Titulo: Datos en Abierto para Instalaciones Científico Técnicas Singulares Basadas en Aceleradores
Tipo: Redes ICTS

 

The optimal use of research infrastructures requires that the wider scientific community has adequate access to the data produced. This requires that data are produced and stored in a way that makes them easy to access. For that purpose, the FAIR principles (Findability, Accessibility, Interoperability, Reusability) have been stated and developed.

The accelerator-based ICTS, CNA and CMAM, which form the distributed network IABA, produce an important set of data in each accelerator experiment carried out. Typically, these experiments generate a set of counts in different detectors of a detector array, which should be complemented with data from the accelerator diagnostics. Such wealth of data is often lost after each analysis, in such a way that users only refer to a count rate, where some background subtraction and fitting are performed. In many other cases, data are stored in specific formats that make any reuse initiative impractical. Proper storage of the raw data obtained from accelerator-based experiments, along with the relevant metadata, would be highly beneficial. It would allow systematic analysis of data from different experiments, detector arrays, and facilities. This, in turn, would improve data analysis procedures by leveraging historical data from previous experiments.

 

https://cna.us.es/index.php/es/investigacion/proyectos-seleccionados/1254-proyecto-opendata


Vicerrectorado de Investigación. Universidad de Sevilla. Pabellón de Brasil. Paseo de las Delicias s/n. Sevilla