This two-day intensive course aims to introduce participants to the fundamentals of data visualization using the open-source QGIS program and building towards the introduction of foundational spatially-centered approaches to identifying relationships and associations among population and environmental variables. Led by Dr. Jeremy R. Porter and Dr. Joel Capellan two of the highest-rated teachers at the Columbia University Mailman School of Public Health and the authors of many celebrated geospatial analysis publications and books, this workshop will integrate lectures with hands-on application. The workshop emphasizes the use of open-source software packages and publicly available environmental and demographic data as an example of potential applications of these data with spatially centered visualization and analytic techniques. The workshop is comprised of 4 components 1) visualization, 2) geo-processing, 3) cluster analysis, and 4) relationship identification. Within each component, a lecture is followed by an opportunity to put the methods learned into practice.
By the end of the workshop, participants will be familiar with the following topics:
- Principles of data visualization and analysis
- Sources and techniques for the acquisition and management of spatial data
- Methods and techniques for the visualization of spatial data
- Techniques for the identification of statistical spatial (and spatio-temporal) clusters
- Techniques for the incorporation of spatial information in more traditional regression methods of association and relationship identification among variables.
- Investigators at all career stages are welcome to attend, and we particularly encourage trainees, students, and early-stage investigators to participate.
- Workshop
- Information and Security Technologies
