R. Saidi “Getting into digital – where should we start?”

Rabie Saidi, European Bioinformatics Institute, UK

Abstract

The 2030 Agenda aims to accomplish a number of goals ranging from broadening the public participation and improving the quality of life for disadvantaged communities, to creating a better business environment and improving the productivity and efficiency of government agencies. Leveraging Data Science as engine and FAIR data as fuel would strengthen the achievement of these goals. Data Science provides efficient methods and systems to extract knowledge and information from datasets, which are then translated into meaningful actions. Theoretical foundations of Data Science are often in the intersection of statistics, mathematics and computer Science. As Data Science becomes increasingly influential, inevitably there will be significant levels of national and global debate over how best it can be used for the understanding and development of economies, governments and societies. Although Data science can even make sense of "hard to use" data, it would be way more beneficial if data were made available  according the FAIR principles. The FAIR principles (Findable, Accessible, Interoperable, Reusable) work as a guideline to facilitate the access to and reuse of data by humans and machines. The European Commission has taken up these principles and asks all projects funded by the H2020 program to follow them. These principles provide guidance for data management and are relevant to all stakeholders in digital ecosystems. They directly address data producers and data publishers to promote maximum use of data.

WASD 2019 FLYER
WASD 2019 FLYER

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