14 Open Source Software – MVR Geospatial Data Science User Guide

14.1 Languages

Definition: A lightweight conda distribution that installs only the conda package manager and the conda-forge channel by default.
Purpose: Bootstrap a minimal, reproducible Python environment for non-geospatial projects without the overhead of a full Anaconda installation.
Audience: Data scientists who need to quickly set up a clean Python environment.
URL: conda-forge.org

Definition: A cross-platform JavaScript runtime built on Chrome’s V8 engine that executes JavaScript outside a browser.
Purpose: Build and run JavaScript-based full-stack web applications and developer tooling.
Audience: Developers building web applications or working with JavaScript-based data visualization tools.
URL: nodejs.org

Definition: A language and environment for statistical computing and graphics, maintained by the R Core Team.
Purpose: Perform statistical analysis, data manipulation, and visualization; author reproducible reports and Shiny applications.
Audience: All USACE geospatial data scientists using R-based workflows.
URL: r-project.org

Definition: A collection of build tools required to compile R packages from source on Windows.
Purpose: Install R packages that require compilation, including those with C, C++, or Fortran code.
Audience: R users on Windows who need to build packages from source.
URL: cran.r-project.org/bin/windows/Rtools

Definition: A source-available code editor produced by Microsoft, built on the MIT-licensed Code - OSS project, with broad language and extension support.
Purpose: Write, debug, and manage code across multiple languages using a lightweight, highly extensible editor with a large extension ecosystem.
Audience: Developers and data scientists who need a general-purpose editor that supports Python, JavaScript, R, and other languages beyond what Positron or RStudio cover.
URL: code.visualstudio.com

Definition: A VS Code-based integrated development environment (IDE) designed specifically for data science workflows.
Purpose: Write, run, and debug R and Python code in a unified IDE with first-class support for both languages.
Audience: Data scientists who work across R and Python and want a modern, extensible IDE.
URL: positron.posit.co

Definition: An open source IDE built for the R language, produced by Posit.
Purpose: Write and execute R code, manage projects, and author Quarto and R Markdown documents in a dedicated R environment.
Audience: Data scientists primarily working in R who prefer a purpose-built R IDE.
URL: posit.co/products/open-source/rstudio

Definition: A Windows port of the Git distributed version control system, bundled with Git Bash, Git GUI, and Git Credential Manager.
Purpose: Track code changes, manage branches, sign commits, and collaborate on repositories hosted on GitHub or other Git platforms.
Audience: All USACE geospatial data scientists who maintain code in Git repositories.
URL: gitforwindows.org

Definition: An open source object-relational database system with over 35 years of active development.
Purpose: Store, query, and manage structured geospatial and tabular data using SQL; extend with PostGIS for spatial data support.
Audience: Data scientists and analysts who need a robust, production-grade relational database.
URL: postgresql.org

Definition: An open source administration and development platform for PostgreSQL databases.
Purpose: Administer PostgreSQL servers, design schemas, write and run SQL queries, and inspect database objects through a graphical interface.
Audience: Data scientists and database administrators who work with PostgreSQL.
URL: pgadmin.org

Definition: An open source, daemonless container engine and desktop GUI for building and running OCI containers.
Purpose: Build and deploy data science applications and toolchains inside Linux containers without requiring root privileges.
Audience: Data scientists who need reproducible, portable computing environments that work consistently across machines.
URL: podman.io

Definition: An open source geographic information system (GIS) platform for viewing, editing, and analyzing spatial data.
Purpose: Perform GIS analysis, visualize spatial datasets, and build map products without proprietary software overhead.
Audience: GIS analysts who need a full-featured desktop GIS, and advanced analysts who use the QGIS Python API for scripting.
URL: qgis.org

Definition: An open source technical publishing system that supports Python, R, Julia, and JavaScript.
Purpose: Author reproducible reports, books, websites, and presentations that weave together prose, code, and output in a single document.
Audience: All USACE geospatial data scientists who produce technical documents or share analytical results.
URL: quarto.org

Definition: An open source server platform for hosting Shiny web applications built in R.
Purpose: Self-host and share interactive Shiny applications on an internal or public web server without a commercial SaaS platform.
Audience: Data scientists who need to deploy Shiny apps on infrastructure they control.
URL: posit.co/products/open-source/shinyserver

Definition: A free, open source reference management tool for collecting, organizing, citing, and sharing research sources.
Purpose: Manage bibliographic references and generate citations for technical reports and Quarto documents.
Audience: All USACE geospatial data scientists who cite methods, data sources, or standards in their work.
URL: zotero.org

Definition: A free, open source ontology editor developed at Stanford University with full support for OWL 2 and description logic reasoners.
Purpose: Develop and maintain ontologies for knowledge representation, semantic data integration, and knowledge-based applications.
Audience: Data scientists and knowledge engineers working on semantic data modeling or Army Vantage ontology workflows.
URL: protege.stanford.edu | Install via app-portal.usace.army.mil