My research centers on (1) how data can be managed in situations where there are multiple databases and (2) how to manage data that is currently not well supported by databases. To that end, my students and I are currently exploring a number of topics, including: IDEAS2.0: Integrative Data-Enabled Approaches to Sustainability across Scales. Many communities have set aggressive economic, environmental and social sustainability targets. Meeting these ambitious targets requires better, faster and less expensive ways of evaluating different design options and tradeoffs against the most important performance measures (e.g., cost, energy consumption, quality of life). The problem is that the data and evidence needed to support this evaluation originates from many different sources, scales, and formats. This diversity of data makes it challenging for decision-makers to access the information they need, in the right format and at the right time in the collaborative decision-making process. Our long-term goal is to help organizations make better sustainability decisions. This is joint work with Sheryl Staub-French, Whitney Bai, and the rest of the IDEASS team. Making sense of data that is stored in relational databases or XML is difficult. For example, if civil engineers are trying to extract information about where two pieces of a building intersect, they may need to find 10 different elements in a schema that contains thousands of options. This project seeks to allow users to understand their schemas well enough to query them. This is joint work with Omar AlOmeir and Zainab Zolaktaf. In many situations, even if provenance information is available to describe where data is from, it's difficult to understand. In this project we are looking at how to make provenance information digestible so that it can be used in order to help data be trusted in applications such as financial and building design data. This is joint work with Omar AlOmeir.