Open Source Linux Data Visualization Software - Page 5
Sort By:
Data Visualization Software for Linux
View 64 business solutions-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
Forever Free Full-Stack Observability | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
-
1
Analyze and visualize tours in many variations, which are recorded with a GPS device, bike-, exercise- or ergometer-computer. Some highlights: Tools are available to adjust recorded data, GPS tours can be visualized in customizable maps, ...
-
2
Architecture as a code
Visualize, collaborate, and evolve the software architecture
Architecture as a code is an open-source modeling language and toolkit that enables software teams to describe, visualize, collaborate on, and maintain software architecture as code. Inspired by the C4 Model and other architectural DSLs, LikeC4 lets you define your system’s structure in a textual DSL and then automatically generate consistent diagrams that reflect that design, ensuring that architecture documentation stays in sync with source code changes. The project includes command-line tooling, IDE integrations, live preview servers, and diagram exporters, letting developers instantly see architectural diagrams update as the model evolves. By treating architecture as code, teams benefit from version control, live collaboration, consistency across diagrams, and the ability to treat architectural change with the same tooling and workflows used for code. -
3
ForwardDiff.jl
Forward Mode Automatic Differentiation for Julia
ForwardDiff implements methods to take derivatives, gradients, Jacobians, Hessians, and higher-order derivatives of native Julia functions (or any callable object, really) using forward mode automatic differentiation (AD). While performance can vary depending on the functions you evaluate, the algorithms implemented by ForwardDiff generally outperform non-AD algorithms (such as finite-differencing) in both speed and accuracy. Functions like f which map a vector to a scalar are the best case for reverse-mode automatic differentiation, but ForwardDiff may still be a good choice if x is not too large, as it is much simpler. The best case for forward-mode differentiation is a function that maps a scalar to a vector. -
4
Jupyter Dock
Perform molecular docking protocols interactively
Jupyter Dock is a set of Jupyter Notebooks for performing molecular docking protocols interactively, as well as visualizing, converting file formats and analyzing the results. These notebooks are Python 3 compatible. Each protocol and Jupyter notebook has its own test folder for testing and reproducibility evaluation. For all notebooks, the demonstration includes the use of AutoDock Vina and Ledock. When available, some alternatives are mentioned in the protocol. Jupyter Dock's initial goal was to provide a set of pythonic protocols for molecular docking. Nonetheless, there is a dearth of docking tools in Python for all of the steps and protocols (i.e. pocket search for blind docking). Furthermore, the majority of well-known and widely used molecular docking software have been developed as stand-alone executables or as components of software suites. -
Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
-
5
MLJBase.jl
Core functionality for the MLJ machine learning framework
Repository for developers that provides core functionality for the MLJ machine learning framework. MLJ is a Julia framework for combining and tuning machine learning models. This repository provides core functionality for MLJ. -
6
Manopt.jl
Optimization on Manifolds in Julia
Optimization Algorithm on Riemannian Manifolds. A framework to implement arbitrary optimization algorithms on Riemannian Manifolds. Library of optimization algorithms on Riemannian manifolds. Easy-to-use interface for (debug) output and recording values during an algorithm run. Several tools to investigate the algorithms, gradients, and optimality criteria. -
7
Matplot++
Matplot++: A C++ Graphics Library for Data Visualization
Data visualization can help programmers and scientists identify trends in their data and efficiently communicate these results with their peers. Modern C++ is being used for a variety of scientific applications, and this environment can benefit considerably from graphics libraries that attend the typical design goals toward scientific data visualization. Besides the option of exporting results to other environments, the customary alternatives in C++ are either non-dedicated libraries that depend on existing user interfaces or bindings to other languages. Matplot++ is a graphics library for data visualization that provides interactive plotting, means for exporting plots in high-quality formats for scientific publications, a compact syntax consistent with similar libraries, dozens of plot categories with specialized algorithms, multiple coding styles, and supports generic backends. -
8
ReservoirComputing.jl
Reservoir computing utilities for scientific machine learning (SciML)
ReservoirComputing.jl provides an efficient, modular and easy-to-use implementation of Reservoir Computing models such as Echo State Networks (ESNs). For information on using this package please refer to the stable documentation. Use the in-development documentation to take a look at not-yet-released features. -
9
TIGRE
TIGRE: Tomographic Iterative GPU-based Reconstruction Toolbox
TIGRE is an open-source toolbox for fast and accurate 3D tomographic reconstruction for any geometry. Its focus is on iterative algorithms for improved image quality that have all been optimized to run on GPUs (including multi-GPUs) for improved speed. It combines the higher-level abstraction of MATLAB or Python with the performance of CUDA at a lower level in order to make it both fast and easy to use. TIGRE is free to download and distribute: use it, modify it, add to it, and share it. Our aim is to provide a wide range of easy-to-use algorithms for the tomographic community "off the shelf". We would like to build a stronger bridge between algorithm developers and imaging researchers/clinicians by encouraging and supporting contributions from both sides to TIGRE. -
AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
-
10
The Julia Programming Language
High-level, high-performance dynamic language for technical computing
Julia is a fast, open source high-performance dynamic language for technical computing. It can be used for data visualization and plotting, deep learning, machine learning, scientific computing, parallel computing and so much more. Having a high level syntax, Julia is easy to use for programmers of every level and background. Julia has more than 2,800 community-registered packages including various mathematical libraries, data manipulation tools, and packages for general purpose computing. Libraries from Python, R, C/Fortran, C++, and Java can also be used. -
11
just-dashboard
Dashboards using YAML or JSON files
Dashboards using YAML or JSON files. Create a public GitHub gist with a file named dashboard.yml or dashboard.json (depending on your preferred format) As your dashboard is just data, you can generate it instead of repeating yourself. You can do that by generating the YAML or JSON file yourself, or you can use jq queries in your YAML file. And one with a dashboard that contains a component that can fetch the data from other other gist and turn it into 3 different charts. Using the same principle, you can also loads parts from your dashboard from other files, or just JSON/CSV data for specific charts. Suppose you are only interested in comparing foods by how much they contain of a single macronutrient. However, you want to be able to decide which macronutrient. -
12
plotly.js
JavaScript charting library behind Plotly and Dash
Plotly JavaScript Open Source Graphing Library. Built on top of d3.js and stack.gl, Plotly.js is a high-level, declarative charting library. plotly.js ships with over 40 chart types, including 3D charts, statistical graphs, and SVG maps. plotly.js is free and open source and you can view the source, report issues or contribute on GitHub. For plotly.js to build with Webpack you will need to install ify-loader@v1.1.0+ and add it to your webpack.config.json. This adds Browserify transform compatibility to Webpack which is necessary for some plotly.js dependencies. When users hover over a figure generated with plotly.js, a modebar appears in the top-right of the figure. This presents users with several options for interacting with the figure. When users hover over a figure generated with plotly.js, a modebar appears in the top-right of the figure. This presents users with several options for interacting with the figure. -
13
MathMod
MathMod is a mathematical modeling software
MathMod is a portable interactive plotting and graphing program for Windows, Linux, MacOSX and many other platforms. MathMod allows to plot 3D mathematical surfaces, described by implicit or parametric equations, and offers a very large database of model samples that can be generated with it. It's Free and Open Source. Change-log for MathMod-13.0 (15/11/2025) 1) Scripts generator to add thickness to iso/parametric surfaces 2) Undo/Redo commands for navigating through previous scripts 3) New scripts, Bug-fixes, code optimization and documentation update For a complete list of changes made during the course of development, please visit: https://github.com/users/parisolab/projects/2 -
14
GTS provides a set of useful functions to deal with 3D surfaces meshed with interconnected triangles including collision detection, multiresolution models, constrained Delaunay triangulations and robust set operations (union, intersection, differences).
-
15
OSHMI - Open Substation HMI
SCADA HMI for substations, IoT and automation applications
Now with IEC61850 support! This project combines existing open source projects and tools to create a very capable, mobile and cloud-friendly HMI system that can rival proprietary software. This approach makes it possible to join forces of each project (Chromium, SVG/HTML5, PHP, Lua, SQLite, Inkscape, Lib61850, OpenDNP3, Nginx, Vega, PostgreSQL, Grafana,…) to achieve a great set of open, evergreen, modular and customizable tools for building great HMIs for automation projects. This is not a toy project! It's been actually used in dozens of substations up to 230kV level and also in control centers with configurations up to 70.000 tags. Feel free to ask questions in the "Discussion" section. Help sponsoring OSHMI here https://github.com/sponsors/riclolsen. >>> Have a look also at my new SCADA project here: https://github.com/riclolsen/json-scada -
16
An easy to use application to design your kitchen garden or your house farm. Helps you plan your plants ( vegetables, fruit trees, herbs, flowers ) so that it respects the rules of crop rotation and companion planting. Based on square foot gardening. Requires Java 8.
-
17
Mobile Robot Programming Toolkit (MRPT)
**MOVED TO GITHUB** ==> https://github.com/MRPT/mrpt
**MOVED TO GITHUB** ==> https://github.com/MRPT/mrpt The Mobile Robot Programming Toolkit (MRPT) is an extensive, cross-platform, and open source C++ library aimed for robotics researchers to design and implement algorithms about Localization, SLAM, Navigation, computer vision. http://www.mrpt.org/ -
18
TESTIMAGES
Testing images for scientific purposes
The TESTIMAGES archive is a huge and free collection of sample images designed for analysis and quality assessment of different kinds of displays and image processing techniques. The archive includes more than 2 million images originally acquired and divided in three different categories: SAMPLING and SAMPLING_PATTERNS (aimed at testing resampling algorithms), COLOR (aimed at testing color rendering on different displays) and PATTERNS (aimed at testing the rendering of standard geometrical patterns). Please cite the following papers when using any image in this archive: * ASUNI N, GIACHETTI A, "TESTIMAGES: A Large Data Archive For Display and Algorithm Testing", Journal of Graphics Tools, Volume 17, Issue 4, 2015, pages 113-125, DOI:10.1080/2165347X.2015.1024298 * ASUNI N, GIACHETTI A, "TESTIMAGES: a large-scale archive for testing visual devices and basic image processing algorithms", STAG - Smart Tools & Apps for Graphics Conference, 2014. -
19
pfstools - a set of programs for reading, writing, manipulating and viewing high-dynamic range (HDR) images and video frames. pfscalibration - photometric calibration of cameras and HDR images from multiple exposures. pfstmo - tone mapping operators.
-
20
AlphaPlot
Interactive scientific graphing and data analysis software.
Alpha Plot can generate different types of 2D and 3D plots (such as line, scatter, bar, pie, and surface plots) from data that is either imported from ASCII files, entered by hand, or calculated using formulas. The data is held in spreadsheets which are referred to as tables with column-based data (typically X and Y values for 2D plots) or matrices (for 3D plots). The spreadsheets as well as graphs and note windows are gathered in a project and can be organized using folders. The built-in analysis operations include column/row statistics, (de)convolution, FFT and FFT-based filters. Scripting Console support in-place evaluation of mathematical expressions and scrtipting interface to ECMAScript like dynamic scripting language(java script). The GUI of the application uses the Qt toolkit. Periodic test builds are available here http://alphaplot.sourceforge.net/test-build.html -
21
ChainRulesCore
AD-backend agnostic system defining custom forward and reverse rules
AD-backend agnostic system defining custom forward and reverse mode rules. This is the light weight core to allow you to define rules for your functions in your packages, without depending on any particular AD system. The ChainRulesCore package provides a light-weight dependency for defining sensitivities for functions in your packages, without you needing to depend on ChainRules itself. This will allow your package to be used with ChainRules.jl, which aims to provide a variety of common utilities that can be used by downstream automatic differentiation (AD) tools to define and execute forward-, reverse-, and mixed-mode primitives. -
22
Distributions.jl
A Julia package for probability distributions and associated functions
A Julia package for probability distributions and associated functions. -
23
Excalidraw MCP
Fast and streamable Excalidraw MCP App
Excalidraw-MCP is an open-source Model Context Protocol (MCP) application and server that connects the visual power of Excalidraw’s hand-drawn diagram editor with AI-driven workflows, enabling agents like Claude, ChatGPT, VS Code, and other MCP-compatible hosts to generate and manipulate diagrams programmatically. Rather than being just a static whiteboard, Excalidraw-MCP serves diagrams in real time using an MCP backend and streams interactive visual output back to the client, letting AI tools create shapes, connectors, text, and entire diagrams as part of conversational or task-based sessions. Its design supports fast, streamable rendering with smooth viewport control and optional fullscreen editing so that diagrams feel live and fluid as they evolve. Users can deploy it locally or via services like Vercel, then configure their MCP host to point at the Excalidraw-MCP endpoint, so prompts like “draw an architecture diagram” yield immediate visual results within chat. -
24
HDF5.jl
Save and load data in the HDF5 file format from Julia
HDF5 stands for Hierarchical Data Format v5 and is closely modeled on file systems. In HDF5, a "group" is analogous to a directory, a "dataset" is like a file. HDF5 also uses "attributes" to associate metadata with a particular group or dataset. HDF5 uses ASCII names for these different objects, and objects can be accessed by Unix-like pathnames, e.g., "/sample1/tempsensor/firsttrial" for a top-level group "sample1", a subgroup "tempsensor", and a dataset "firsttrial". For simple types (scalars, strings, and arrays), HDF5 provides sufficient metadata to know how each item is to be interpreted. For example, HDF5 encodes that a given block of bytes is to be interpreted as an array of Int64, and represents them in a way that is compatible across different computing architectures. However, to preserve Julia objects, one generally needs additional type information to be supplied, which is easy to provide using attributes. -
25
HomotopyContinuation.jl
A Julia package for solving systems of polynomials
HomotopyContinuation.jl is a Julia package for solving systems of polynomial equations by numerical homotopy continuation. Many models in the sciences and engineering are expressed as sets of real solutions to systems of polynomial equations. We can optimize any objective whose gradient is an algebraic function using homotopy methods by computing all critical points of the objective function. An important special case is when the objective function is the euclidean distance to a given point. An example of an non-algebraic objective function whose derivative is algebraic is the Kullback–Leibler divergence. Homotopy continuation methods allow us to study the conformation space of molecules as for example cyclooctane (CH₂)₈. This molecule consists of eight carbon atoms aligned in a ring, and eight hydrogen atoms, each of which is attached to one of the carbon atoms.
