In this talk I will discuss three challenges: (a) providing explanations through support for causal queries ("Why"), (b) tracing and correcting errors at their source (post-factum data cleaning), and (c) integrating database systems with constrained optimization capabilities ("How"). First, I will show how to apply causal reasoning to tuple provenance in order to determine the causes of query results, and their responsibility. I will present extensive analysis of the data complexity for the case of conjunctive queries, and focus on a complete dichotomy between NP-hard and PTIME cases for the problem of computing responsibility. This concrete characterization of PTIME cases is crucial in scaling up to the challenges of Big Data. Second, I will demonstrate the applicability of the causality framework in a practical setting. I will use a mobile sensing application to show that ranking provenance tuples by their degrees of responsibility identifies errors more effectively than other schemes. Finally, I will present the Tiresias system, the first how-to query engine, which seamlessly integrates database systems with constrained problem solving capabilities. The contributions of the system are threefold: (a) a declarative interface for defining how-to queries over a database, (b) translation rules from the declarative statements to the constrained problem specification, and (c) a suite of data-specific optimizations that allow scaling to large data sizes. Initial results of our prototype system implementation show order-of-magnitude speedups to state-of-the-art solver runtimes, which indicates that there are significant gains in pushing this functionality within the database engine. I will conclude with a summary of my contributions, and discuss my future steps with the Tiresias system, and the bigger vision of reverse data management.
Bio: Alexandra Meliou is a postdoctoral research associate with Dan Suciu in the database group of the University of Washington. She received her Ph.D degree in 2009 from the University of California, Berkeley, and is a 2008 Siebel Scholar. Her interests are in data and information management with a focus on issues of data provenance. Currently, she is working on extending the capabilities of database systems to support business decisions and strategy planning queries.