Presenter: Wendy Guan

In: Urban Data Science Lab, School of Architecture, Texas A&M University

Abstract: In the era of the 4th industrial revolution, place and time are embedded in data from many sources, critical in solving global problems. However, spatiotemporal data handling is often costly and time consuming, requiring advanced skills. Analytical results are hard to reuse and difficult to share among researchers with different domain knowledge and varying technical skills. The Spatial Data Lab project (SDL) is aimed at solving these problems by re-engineering the lifecycle of spatiotemporal research with a workflow-based platform. It builds workflows with KNIME to integrate heterogeneous data, replicate analytical procedures, automate visualization updates, provide web access to HPC, and make spatiotemporal research reproducible, replicable and expandable. The integrated solution includes data, tools, models, visualizable results, documentation and publications, packaged as case studies, allowing researchers to find, learn, use, modify, improve, and re-contribute back to the Lab. This talk will present some recent developments of SDL, showcase the Geospatial Analytics Extension in KNIME, and discuss future directions of the project and collaboration opportunities.

Slides