Teaching staff from eight Spanish universities, coordinated by the Universitat Jaume I in Castelló, have contributed to improving legal certainty in the management of information by public administrations and to reconciling the right to data protection with the duty of transparency and the fight against corruption. They have done so by proposing regulatory improvements after analysing, comparing and identifying legal gaps in the various national and regional regulations governing these matters.
The study of the application of the General Data Protection Regulation (GDPR) in the public sphere has made it possible to identify the challenges faced by administrations in implementing these fundamental rights, to design training initiatives to convey this knowledge to those working within them, and to improve the public service they provide to citizens. In addition, the team has provided regulatory tools to ensure compatibility between guaranteeing access to public information and protecting personal data.
In the opinion of the research team, “by ensuring that data protection is not used as a pretext to restrict transparency, access to information of general interest has been strengthened, enabling society to participate more actively in public affairs”. They also highlight as one of the most significant contributions in the field of data protection “the identification of mechanisms to strengthen the protection of individuals who report corruption”.
The impact of the project “Reconciling the right to data protection with compliance by public authorities with the duty of transparency and the fight against corruption (DATATRANSCO)”, funded by the Ministry of Science, Innovation and Universities, has extended beyond the public administration and legal sectors to others such as technology and artificial intelligence. The research team has incorporated into its analysis and comparison the European Artificial Intelligence Regulation (AI Act), adopted in 2024, which includes requirements regarding transparency and explainability (understanding how an algorithm works).
