Federated interoperability model for the exchange of data in the Peruvian justice sector

• Autores: Salazar-Pimpincos, Jaime, Mauricio Sánchez, David
• Formato: artículo
• Fecha de Publicación: 2018
• Institución: Universidad Nacional Mayor de San Marcos
• Repositorio: Revistas - Universidad Nacional Mayor de San Marcos
• Lenguaje: español
• OAI Identifier: oai:ojs.csi.unmsm:article/15381
• Enlace del recurso: https://revistasinvestigacion.unmsm.edu.pe/index.php/rpcsis/article/view/15381
• Nivel de acceso: acceso abierto
• Materia: Justice Information System; Interoperability; Federated System; Real-time data exchange; Sistema de información de Justicia; Interoperabilidad; Sistema Federado; Intercambio de datos en tiempo real

The information that flows in the justice system, particularly in Peru, is not shared in real time due to the heterogeneity of its information systems and platforms, generating excessive delay in the judicial process. For this reason, they have been developing interoperability models for this sector for more than a decade, highlighting the European model e-CODEX that integrates fourteen countries with diverse and heterogeneous systems and platforms. However, these models generate information duplication and present difficulty in their implementation due to the legal regulations and standards required. Here, we propose an interoperability model based on data federation for the Peruvian justice sector, this will allow to have information in real time, distributed, without duplicity, transparent to the user and easy to implement for heterogeneous and inherited systems and platforms. The proposal is based on the e-CODEX architecture, adapting and adding the concept of federation, it consists of three layers: physical, logic, applications and a standardization group. Simulating the process of registration of detainees, where four institutions interact, we demonstrate that the average times of 20 and 15 days for the registration operation and the exchange of information per process respectively decrease to zero, besides eliminating errors generated by the transcription of data.