A key problem is to identify high-level things — organizations and activities — based on low-level data — people, places, things, and events. By "organization", I mean a set of interrelated people and things with some internal cohesion (e.g. a business or terrorist cell). By "activity", I mean a set of interrelated people, place, things, and events with some internal cohesion (e.g., the development of a new product or the planning of a terrorist attack). In contrast to traditional data mining, where both the data and the inferences are about individuals. The goal here is to use data at both levels to make inferences about compositions of things that exist only at a higher level.