Software and Tools for GIS and Data Visualization

Geographic Information Systems (GIS)

QGIS

QGIS is a professional GIS application that is built on top of and proud to be itself Free and Open Source Software (FOSS). QGIS is a user friendly Open Source Geographic Information System (GIS) licensed under the GNU General Public License. QGIS is an official project of the Open Source Geospatial Foundation (OSGeo). It runs on Linux, Unix, Mac OSX, Windows and Android and supports numerous vector, raster, and database formats and functionalities.

Website: https://qgis.org
Platform: Windows, macOS, Linux, Android
Use it for: General GIS, cartography, spatial analysis, plugins like TimeManager and Processing toolbox

Grass GIS

GRASS, Geographic Resources Analysis Support System, is a powerful computational engine for raster, vector, and geospatial processing. It supports terrain and ecosystem modeling, hydrology, data management, and imagery processing. With a built-in temporal framework and Python API, it enables advanced time series analysis and rapid geospatial programming, optimized for large-scale analysis on various hardware configurations. GRASS GIS (Geographic Resources Analysis Support System) is a powerful spatial modeling tool with support for raster, vector, and temporal data.

Website: https://grass.osgeo.org
Platform: Windows, macOS, Linux
Use it for: Hydrology, terrain analysis, temporal data modeling, scripting with Python

Geoda

GeoDa is a free and open source software tool that serves as an introduction to spatial data science. It is designed to facilitate new insights from data analysis by exploring and modeling spatial patterns. GeoDa is a user-friendly application that introduces spatial data science through spatial autocorrelation and regression modeling.

Website: https://grass.osgeo.org
Platform: Windows, macOS, Linux
Use it for: Hydrology, terrain analysis, temporal data modeling, scripting with Python


Data Visualization

Flourish

Flourish lets users create interactive visualizations with minimal coding, ideal for storytelling and journalism. Flourish was created to enable everyone to tell stories with data. Launched in 2018, the tool is used by a huge community of creators to inform tens of millions of viewers every day.

While Flourish offers a free tier, it is not open-source. For fully open alternatives, see below.

Website: https://flourish.studio
Use it for: Charts, maps, scrollytelling, presentations

Rawgraphs

RAWGraphs is an open source data visualization framework built with the goal of making the visual representation of complex data easy for everyone.
Primarily conceived as a tool for designers and vis geeks, RAWGraphs aims at providing a missing link between spreadsheet applications (e.g. Microsoft Excel, Apple Numbers, OpenRefine) and vector graphics editors (e.g. Adobe Illustrator, Inkscape, Figma).
RAWGraphs is an open source framework for visualizing complex datasets directly from spreadsheets and CSV files.

Website: https://rawgraphs.io
Platform: Web-based, self-hostable
Use it for: Alluvial diagrams, treemaps, scatterplots, circular plots
Codebase: GitHub - RAWGraphs


Statistical and Data Science Tools

RStudio Desktop

RStudio is a powerful IDE for R and Python. While the core IDE is open source, RStudio now exists under the Posit brand with both open and pro versions.

Website: https://posit.co
Platform: Windows, macOS, Linux
Use it for: Statistical computing, spatial modeling (via sf, terra, tmap, leaflet, etc.)


Other Useful Tools

OpenRefine

A powerful tool for cleaning messy datasets, especially tabular data.

  • Website: https://openrefine.org
  • Platform: Web-based, runs locally
  • Use it for: Data cleaning, transformation, reconciling datasets

Inkscape

Free and open source vector graphics editor. Useful for refining maps exported from QGIS or RAWGraphs.

  • Website: https://inkscape.org
  • Platform: Windows, macOS, Linux
  • Use it for: Map post-processing, infographic design

JupyterLab

An open-source notebook environment for coding, visualization, and documentation in Python and R.

  • Website: https://jupyter.org
  • Use it for: Data analysis, Python scripting, integrating with geopandas, matplotlib, folium, etc.

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