Rich data streams coupled with computational tools are contributing to an inflection point in our global knowledge society. Researchers are increasingly able to harness large datasets to generate new insights that can guide decision-making. For example, organizations regularly capture transactions and operational data, and sensor networks (including global positioning system [GPS] data from smartphones) support a wide spectrum of applications, from detecting traffic flows to capturing levels of moisture in vineyards. Similarly, the shift of commerce, science, education, art, and entertainment to the Web is resulting in unprecedented quantities of data about human activities. Algorithmic tools, including approaches for discovering and visualizing important dependencies, influences, and relationships amidst a sea of complex interactions, as well as methods for constructing and using predictive models that help unearth patterns that we cannot see directly, can transform data into insights in the form of rich visualizations and recommendations for action. Such tools have provided “optics” into potential illnesses lurking behind a patient's symptoms, the locations and durations of traffic jams in a city, usage patterns and impacts of home appliances on energy consumption and costs, and so on. In this session, speakers will describe how computing research is enabling a “data to knowledge to action” pipeline that is increasingly critical for facilitating a 21st century global knowledge society.