We live in the era of Big Data, which is characterized by an unprecedented increase in information generated from many sources including (i) massive simulations for science and engineering, (ii) sensing devices for experiments and diagnostics, and (iii) records of people's activities left actively or passively primarily on the web. This is a gift to many disciplines in science and engineering since it will undoubtedly lead to a wide range of new amazing discoveries. This is also changing the nature of scientific investigation, combining theory, experiments, and simulations with the so-called "fourth paradigm" of data-driven discovery. Interdisciplinary work, traditionally confined to a few heroic efforts, will become a central requirement in most research activities since progress can only be achieved with a combination of intense computing infrastructures and domain expertise. For example, computational efforts can only validated in the proper application context, such as in climate modeling, biology, economics, and social sciences, to name just a few.

In this talk I will discuss some of the experiences in Big Data discovery that have driven the activities at the Center for Extreme Data Management Analysis and Visualization. The technical work, for example, is systematically reshaped to involve integrated use of multiple computer science techniques such as data management, analytics, high performance computing, and visualization. Research agendas are motivated by grand challenges, for instance, the development of new, sustainable energy sources, or predicting and understanding climate change. Furthermore, such efforts rely on multi-disciplinary partnerships with teams that extend across academia, government laboratories and industry. Overall, the great opportunities of Big Data research come with great challenges in terms of how we reshape scientific investigation, collaborations across disciplines, and how we educate the future generations of scientists and engineers.