LAGOVirtual: A Collaborative Environment for the Large Aperture GRB Observatory

TL;DR

The paper describes the development of LAGOVirtual, a collaborative platform for data sharing, simulation, and preservation in the Large Aperture GRB Observatory, enhancing collaboration across multiple high-altitude sites.

Contribution

It introduces a prototype platform based on DSpace for organizing and sharing data and metadata among LAGO collaborators, integrating synthetic data generation and distributed data storage.

Findings

Successful implementation of a hierarchical data repository structure

Enabling multi-site data sharing and collaboration

Support for synthetic data simulation and storage

Abstract

We present the LAGOVirtual Project: an ongoing project to develop platform to collaborate in the Large Aperture GRB Observatory (LAGO). This continental-wide observatory is devised to detect high energy (around 100 GeV) component of Gamma Ray Bursts, by using the single particle technique in arrays of Water Cherenkov Detectors (WCD) at high mountain sites (Chacaltaya, Bolivia, 5300 m a.s.l., Pico Espejo, Venezuela, 4750 m a.s.l., Sierra Negra, Mexico, 4650 m a.s.l). This platform will allow LAGO collaboration to share data, and computer resources through its different sites. This environment has the possibility to generate synthetic data by simulating the showers through AIRES application and to store/preserve distributed data files collected by the WCD at the LAGO sites. The present article concerns the implementation of a prototype of LAGO-DR adapting DSpace, with a hierarchical structure (i.e. country, institution, followed by collections that contain the metadata and data files), for the captured/simulated data. This structure was generated by using the community, sub-community, collection, item model; available at the DSpace software. Each member institution-country of the project has the appropriate permissions on the system to publish information (descriptive metadata and associated data files). The platform can also associate multiple files to each item of data (data from the instruments, graphics, postprocessed-data, etc.).