Public Group active 2 months ago

DVG – Data Visualization Group

Data Visualization Group (i.e., DVG) is a place for students, faculty, and staff who are interested in sharing topics, theories, methods, and techniques related to data visualization. Data visualization is a graphical representation of data. Done well, visual elements such as charts, graphs, and maps are just a few data visualization tools that can provide viewers an accessible way of understanding the represented information. In a world increasingly governed by Big Data, data visualization can assist decision-makers in their analyses.
In this working group, members are encouraged to discuss and share theories, methods, and projects that include but are not limited to data preprocessing, data explanation, data exploration, theories of data visualization, real-world examples, and ongoing work. We will explore the fundamentals of data visualization including design principles, best practices, dashboards, visualization tools, ethics, and more.
This is a new working group, and topics will be based on participation and interest. Virtual meetings are free, open to all GC Community members of all skill levels, disciplines, and backgrounds.

Admins:

`Mapping User Group Group Sessions – Spring 2023

  • Hi, everyone.

    As we prepare to begin our biweekly meetings for the Mapping User Group during the spring semester, I would like to get your feedback on what times would be best for us to meet, and what topics we should cover. I believe over the past semester and on DRI, we had attendance from a few people that have ongoing mapping projects, so I believe these working sessions could be very helpful if we focus on very concrete skills and goals in each. I am planning on bringing one tutorial/script per session, that we can go over to learn new GIS tools. I am also inclined to move more into using R for mapping, since it fits well with the need that most of us have in our project: merge our own data that we generate in our research with existing spatial data in order to create maps. My initial thoughts on possible tutorials in R for our next meetings are: 1) using ggplot and sf package for basic mapping (focusing on tools to customize our maps); 2) using the SF package functions to perform geoprocessing of vector data; 3) using the raster and rayshader package to visualize Raster data; 3) using tidyverse to manipulate both our data and vector files to create new spatial files for mapping; 4) combining packages to simultaneously analyze vector and raster data in R; 5) create interactive maps using the leaflet package in R. As usual, feel free to suggest other topics for us to cover.

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