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.
Aiming to make the ISI a recognised association amongst data scientists in the broadest sense.
Objectives and expected products
- To strengthen the collaboration between statisticians, computer scientists and other communities in the field of data science.
- To provide a ‘big tent’ to all ISI members, and other colleagues interested in data science and data analytics, to sit under.
- To emphasise the importance of data science in the activities promoted by the ISI and its associations.
- To foster capacity building on data science, including computational skills among statisticians, and statistical skills among computational scientists.
- To coordinate and to promote, in collaboration with the ISI and its Associations, specific activities in the field of data science.
Liaison with the ISI PO