Data science has emerged as a very strong, visible, and publicly recognized label for problem-solving, using large, ever-growing datasets and new data sources. The analysis and interpretation of these kinds of data include the adaptation of existing methods, and development of novel statistical methods for specific data science applications. The discussion on advantages, disadvantages, limitations and requirements of the use of alternative methodologies and data sources, in all areas of knowledge, is setting the stage for the debate in (inter)national communities of statisticians, computer scientists and other communities, all over the world.
To make the ISI a recognised association amongst data scientists in the broadest sense, the ISI Executive Committee set up a ‘ISI Data Science Working Group’ to discuss the best way to so. The group was chaired by Daniel Jeske and Jürgen Symanzik, and composed by association representatives, SIG representatives, and regional representatives. This resulted in the ISI Executive Committee and ISI Council to form this ISI SIG on Data Science.