Data-driven science

From Science Europe Data Glossary

Definition: data-driven (or data intensive) science is a suggested new approach to science and scholarship, in which scientific progress is expected to stem from the discovery of patterns in huge volumes data.

Explanation: data intensive science has been proclaimed a transformation or new (fourth) paradigm of scientific endeavor. This idea was originally put forward by Jim Grey of Microsoft Research. The first three paradigms being empirical, theoretical, and computational, the characteristics of the fourth paradigm were that the new data-intensive science (which Grey called e-Science) is characterized by unification of theory, experiment, and simulation. Information-sharing and collaboration on a grand scale were made possible by network technologies.

References: Tony Hey et al. (eds.), The Fourth Paradigm: Data-Intensive Scientific Discovery (Microsoft Research, 2009),; Michael L. Nelson, 'Data-Driven Science: A New Paradigm?', in: EDUCAUSE Review, vol. 44, no. 4 (July/August 2009): 6–7,;

See also: science 2.0; data science; open science