There are increasing concerns from the public on privacy, fairness, safety, and robustness issues of data analytics, data collection, data sharing, and decision making. The social awareness thrust team will present their cutting-edge research on socially aware data analytics that can address social concerns and enable big data analytics to promote social good and prevent social harm.
Data has a life cycle from planning to acquiring, cleansing, storing & sharing, integrating, application, and disposing. While AI and machine learning have taken the application of data to new levels, the other phases remain largely manually mediated processes. The research goal for the Data Life Cycle and Curation thrust is to develop fully automated processes for the other phases of the data life cycle. The presentation today describes some of the progress of the research finding ways to automate data cleansing and data integration phases of the data life cycle.