dataviz.cafe
By: George S.
Tags: Open Source, Data Visualization, Open Data, Creative Coding, Design

dataviz.cafe

Find the right tool to visualize your data

This article was co-authored by Andrea B. and George S.

Dataviz.cafe is a public resource curated by IQT Labs for anyone interested in open-source software for data visualization. With over 700 software packages — summarized and tagged by data type, programming language, and other keywords — dataviz.cafe is designed to help people find free visualization tools for a wide variety of use-cases.

Above: the dataviz.cafe interface

In recent years, the open-source community has developed hundreds of highly performant visualization authoring tools. As a result, the quality and variety of data visualization tools in circulation today is staggering. Even as the paid software segment enjoys continued growth and accelerated commercial consolidation, free and open-source software (FOSS) is tackling important visualization problems. These range from general-purpose charting, mapmaking, and dashboarding to more specialized use-cases like displaying brain structures, tracking satellite trajectories, and visualizing load patterns on electrical grids.

While visually captivating and technologically exciting, the abundance of tool options and the rapid pace of change in the field has a downside: information overload. As a consequence, it can be challenging to keep track of capabilities and to make thoughtful, informed decisions about what visualization software to use. Enter dataviz.cafe.

Built with data scientists, visualization designers, web developers, and creative coders in mind, dataviz.cafe is a curated catalog of over 700 open-source visualization tools and software packages that can support a multiplicity of individual needs and use-cases.

In assembling dataviz.cafe, we sought to reflect the diverse array of visualization programming languages in use today, from JavaScript to Python (the two most well-represented languages in the context of the dataviz.cafe tool catalog), to R-based visualization tools, to iOS, Ruby, PHP, and C++. To be as inclusive as possible, we also included low-code DIY visualization tools, like Chart Tool, which cater to less technically-oriented newcomers working in a web browser with non-sensitive data.

The dataviz.cafe website organizes tools and software packages into five categories, based on the type of data they visualize: geospatial, network, quantitative/numerical, text, and miscellaneous. Tools that span multiple categories are cross-listed under all appropriate data types. Each entry has a summary and tags by data type, programming language, and topical keywords. Users who visit dataviz.cafe can explore the entire collection, they can use the data type buttons to filter results, or they can use the search bar to find tools for a specific programming language (“JavaScript,” “Python,” “R-project,” etc.), chart type (e.g. “Sankey” or “treemap”), or keyword (e.g. “bio” or “machine learning”).

Given the popularity of D3.js visualizations, when users type “D3” into the keyword search box, D3.js will appear, along with D3-derived and D3-compatible libraries and modules. (The same is true for jQuery-, Angular-, and React-based visualizations in JavaScript, as well as for PyTorch, Keras, and TensorFlow, which underpin several Python-based visualization tools included in the collection.)