GEMA (Generation and Evaluation of Models for dAta Quality)
Financed by: JJCM Consejería de Educación y Cultura y Deportes, y Fondos FEDER
Total amount: 153.871 €
Identifier Code: SBPLY/17/180501/000293
Data is the fundamental element of digital transformation or disruption. In fact, the technological advances we have been experiencing in recent years, such as cloud computing, internet of things and social networks, have caused the amount of data generated by and made available to organizations to increase exponentially and accumulate at an unprecedented speed.
All the strategic sectors identified in the RIS3 of Castilla-La Mancha (agri-food, tourism, environment and energy, bio-economy, etc.) as well as the transversal factors of the region's intelligent specialisation strategy (Health, ICT, Logistics Innovation, etc.) are not unrelated to this fact, since all of them depend on the data and the quality that these data have in order to optimise their competitiveness and good functioning.
In recent years, several data quality standards and reference models have been defined, both for data governance and data management processes and for the quality of the data itself (ISO 8000, DMM, DCAM, ISO/IEC 25012, etc.). However, in order for any data quality reference model to be useful, it is necessary to adapt it to the specific contexts of the different fields to which it is applied (banking, insurance, health, public administration, agrifood sector, etc.) since there are legislative, regulatory, technological, security, etc. conditioning factors that make it necessary to modify and particularise the processes of data governance, management and quality based on a common reference framework and, on some occasions, it is even necessary to introduce some new processes or regulations and dimensions that affect the data themselves.
In order to manage these adaptations, the project "GEMA" (Generation and Evaluation of Quality Models of dAtos) is proposed. Its main objective is: "Define and validate techniques to generate, adapt, evaluate and improve data quality models ".
1) Marcela F. Genero Bocco      2) Mario Piattini Velthuis
3) Ismael Caballero Muñoz-Reja
4) Ana Isabel Gómez Carretero, Estudiante de Doctorado
5) Javier Verdugo Lara
6) Bibiano Rivas García, Estudiante de Doctorado
7) Fernándo Gualo Cejudo, Estudiante de Doctorado
8) Francisco Pino Correa
Marcela Genero Bocco
Doctora en Informática Catedrática de Universidad Universidad de Castilla-La Mancha
Mario Gerardo Piattini Velthuis
Doctor en Informática y Director del Grupo Alarcos Catedrático de Universidad Universidad de Castilla-La Mancha
Ismael Caballero Muñoz-Reja
Doctor en Informática Profesor Contratado Doctor Universidad de Castilla-La Mancha