We describe our proposed demonstration of GeoDeepDive, a system that helps geoscientists discover information and knowledge buried in the text, tables, and figures of geology journal articles. This requires solving a host of classical data management challenges including data acquisition (e.g., from scanned documents), data extraction, and data integration. SIGMOD attendees will see demonstrations of three aspects of our system: (1) an end-to-end system that is of a high enough quality to perform novel geological science, but is written by a small enough team so that each aspect can be manageably explained; (2) a simple feature engineering system that allows a user to write in familiar SQL or Python; and (3) the effect of different sources of feedback on result quality including expert labeling, distant supervision, traditional rules, and crowd-sourced data.

Current user interfaces for online video consumption are mostly browser based, lean forward, require constant interaction and provide a fragmented view of the total content available. For easier consumption, the user interface and interactions need to be redesigned for less interruptive and lean back experience. In this paper, we describe Personalized Video, an application that converts the online video experience into a personalized lean back experience. It has been implemented on the Windows platform and integrated with intuitive user interactions like gesture and face recognition. It also supports group personalization for concurrent users.