Big data of different types, such as texts and images, are rapidly generated from the internet
and other applications. Dealing with this data using traditional methods is not practical since …

Context: Machine learning is increasingly used in a wide set of applications ranging from
recommendation engines to autonomous systems through business intelligence and smart …

The development and operation of critical software that contains machine learning (ML)
models requires diligence and established processes. Especially the training data used …

The increasing complexity of modern systems poses numerous challenges at all stages of
system development and operation. Continuous software and system engineering …

Modelling is considered as a universal approach to define and simplify real-world
applications through appropriate abstraction. Model-driven system engineering identifies …

This research focuses on the key technologies of network-based collaboration for
Geospatial Artificial Intelligence (GeoAI) services. This paper proposes a geospatial …

As the complexity and scale of big data applications increase, traditional testing
methodologies often fall short in ensuring system reliability and performance. This paper …

Within the last decade, big data became a promising trend for many application areas,
offering immense potential and a competitive edge for various organizations. As the …

For more than a decade now, data has been considered as the new digital oil when it comes
to IT projects. Be it as a basis for the development of new ideas and business processes or …

Resumen en español Con la reciente proliferación de análisis de big data (BDA), las
empresas recopilan y transforman datos para realizar análisis predictivos a una escala que …