The goal of this NCGIA-Varenius workshop and research initiative was to find new automated methods for filtering large amounts of raw geographic data into more user-consumable forms of knowledge. This includes: i) spatial data mining; ii) content-based and knowledge-based retrieval; iii) development of multi-media spatial data types; iv) on-line analytic processing; v) refinement of non-parametric statistics; vi) incorporation of computational intelligence techniques (such as neural networks and AI expert systems) into spatial data analysis. A key objective of the "geographic knowledge discovery" (GKD) workshop was to bring together the diverse stakeholders in GKD and spatial data mining. This report provides an overview of the workshop, lists the workshop participants, and provides the position papers submitted in response to the open Call for Participation. The final section summarizes workshop presentations and discussion.

There is long-standing scientific interest in understanding purposeful movement by animals and humans. Traditionally, collecting data on individual moving entities was difficult and time-consuming, limiting scientific progress. The growth of location-aware and other geospatial technologies for capturing, managing and analyzing moving objects data are shattering these limitations, leading to revolutions in animal movement ecology and human mobility science. Despite parallel transitions towards massive individual-level data collected automatically via sensors, there is little scientific cross-fertilization across the animal and human divide. There are potential synergies from converging these separate domains towards an integrated science of movement. This paper discusses the data-driven revolutions in the animal movement ecology and human mobility science, their contrasting worldviews and, as examples of complementarity, transdisciplinary questions that span both fields. We also identify research challenges that should be met to develop an integrated science of movement trajectories.