AIMDP: An Artificial Intelligence Modern Data Platform. Use case for Spanish national health service data silo Ortega-Calvo, Alberto S. Morcillo-Jiménez, Roberto Fernández Basso, Carlos Jesús Gutiérrez Batista, Karel Vila Miranda, María Amparo Martín Bautista, María José Data platform Artificial Intelligence Intelligent data analysis Big data Medical informatics Data silo The research reported in this paper was partially supported by the BIGDATAMED project, which has received funding from the Andalusian Government, Spain (Junta de Andalucía) under grant agreement No P18-RT-1765. In addition, this research has been partially supported by the Ministry of Universities through the EU-funded Margarita Salas programme NextGenerationEU. The huge amount of data being handled today in any environment, such as energy, economics or healthcare, makes data management systems key to extracting information, analysing and creating more efficient daily processes in these environments. However, the inability of current systems to take advantage of the data generated can waste good opportunities for analysing and extracting information from the data. Modern data platforms (MDP) appear suitable for supporting management systems and are able to perform future prospective analyses. This paper presents a data platform called Artificial Intelligence Modern Data Platform (AIMDP), based on Big Data, artificial intelligence for management, and efficient data handling. The different components of AIMDP intervene in the data acquisition phase and implement algorithms capable of analysing massive data collected from heterogeneous sources. In addition, the entire platform is geared towards data management and exploitation with a layer of security and data governance that allows the integrity and privacy of the databases to be maintained. The proposed platform is designed to be used by users who are not experts in data science. To this end, it implements a user-oriented workflow that has effectively been introduced in a use case of two Spanish hospitals to extract knowledge from their historical data, which had been siloed and had never been explored by any hospital researchers or doctors. 2025-06-12T10:27:48Z 2025-06-12T10:27:48Z 2023-02-06 journal article A.S. Ortega-Calvo, R. Morcillo-Jimenez, C. Fernandez-Basso et al. Future Generation Computer Systems 143 (2023) 248–264. https://doi.org/10.1016/j.future.2023.02.002 https://hdl.handle.net/10481/104615 10.1016/j.future.2023.02.002 eng http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional Elservier