STEM Program

Data Visualization: Using Data Models and Geographical Information to Design Web-Mapping Projects

Faculty Advisor: Associate Director of Spatial Structures in the Social Sciences, Brown University

Research Program Introduction

How do we retrieve and map geographic information from online sources? What data science and cartographic principles should we apply to visualize geographic information? Many considerations are involved, including the nature and availability of geographic information systems (GIS) and mapping platforms.

This course introduces students to basic geographic principles and data models that inform our understanding of space and place. During this course, students will work on a hands-on web mapping project to visualize the spatial distribution of variables of interest. This will be achieved through the step-by-step development of an interactive web map using open-source technologies. Students can later display these maps as part of their spatial data visualization portfolio. For the mapping assignments and final project, students will require access to the following open-source platforms: QGIS and GitHub. 

Students will also learn general and subject-specific research and academic writing methods used in universities and scholarly publications. Students will focus on individual topics and generate their own work products upon program completion.

Project Topics

  • Analyze and discuss spatial data models, geocoding, cartography, and map production. 

  • Build your own spatial data visualization portfolio.

  • Try hands-on web mapping projects to visualize the spatial distribution of variables of interest.

  • Experience step-by-step development of an interactive web map using open-source technologies.

  • Understand map projections, coordinate systems, quantitative and qualitative information representation, and web mapping.

  • Understand best practices and examples of leveraging GIS to address various societal inequities.

Program Details

  • Cohort size: 3 to 5 students

  • Workload: Around 4 to 5 hours per week (including class and homework time)

  • Target students: 9 to 12th graders interested in Data Science, GIS, Geography, Information Systems, Spatial Structures, Web-mapping, and more!

  • Schedule: TBD. Meetings will take place for around one hour per week, with a weekly meeting day and time to be determined one week before the class start date.