EDISON Data Science Framework (EDSF): Addressing Demand for Data Science and Analytics Competences for the Data Driven Digital Economy

Abstract

Emerging data driven economy including industry, research and business, requires new types of specialists that are capable to support all stages of the data lifecycle from data production and input to data processing and actionable results delivery, visualisation and reporting, which can be jointly defined as the Data Science professions family. Data Science is becoming a new recognised field of science that leverages the Data Analytics methods with the power of the Big Data technologies and Cloud Computing that both provide a basis for effective use of the data driven research and economy models. Data Science research and education require a multi-disciplinary approach and data driven/centric paradigm shift. Besides core professional competences and knowledge in Data Science, increasing digitalisation of Science and Industry also requires new type of workplace and professional skills that rise the importance of critical thinking, problem solving and creativity required to work in highly automated and dynamic environment. The education and training of the data related professions must reflect all multi-disciplinary knowledge and competences that are required from the Data Science and handling practitioners in modern, data driven research and the digital economy. In modern conditions with the fast technology change and strong skills demand, the Data Science education and training should be customizable and delivered in multiple forms, also providing sufficient lab facilities for practical training. This paper discusses aspects of building customizable and interoperable Data Science curricula for different types of learners and target application domains. The proposed approach is based on using the EDISON Data Science Framework (EDSF) initially developed in the EU funded Project EDISON and currently being maintained by the EDISON Community Initiative.