Data science has become an important emerging scientific field and the data-driven research paradigm is now key in various disciplines such as statistics, computing or engineering, but also in other fields within the public or private sector. Data Science is considered an interdisciplinary field that involves scientific methods, processes and systems to extract information or knowledge from different types of data, whether structured or unstructured. To do so, it makes use of mathematical and statistical knowledge, engineering and software development as well as specific knowledge of the field in which it is applied. In this way, it is possible to approach a problem from an interdisciplinary point of view.
Data science addresses new and related scientific challenges, spanning the entire data lifecycle, from data capture, creation, storage, retrieval, sharing, analysis, optimisation and visualisation, to integrative analysis across complex heterogeneous and interdependent resources for better decision making, collaboration and ultimately value. Data analysis, as a fundamental stage of the process, employs different techniques and methods drawn from many fields within mathematics and computer science, such as statistics, data mining, artificial intelligence and machine learning, pattern recognition, natural language understanding and big data manipulation.
Coordinators: Fernando Aguilar, Diego Ramiro and Begoña Aguado