Mosaic

D3

The JavaScript library for bespoke data visualization

A checklist for designing and improving the visualization of scientific data

Creating clear and engaging scientific figures is crucial to communicate complex data. In this Comment, I condense principles from design, visual perception and data visualization research in a checklist that can help researchers to improve their data visualization, by focusing on clarity, accessibility and design best practices.

An Award-winning Data Visualization Designer

Visual Cinnamon | Data Visualization Design & Data Art | Data made insightful, effective & beautiful through data visualization and data art

Introducing Observable Canvases

A new way to explore, visualize, and collaborate with data — all in one shared canvas.

Hive Plots - Linear Layout for Network Visualization - Visually Interpreting Network Structure and Content Made Possible

the hive plot is a perceptually uniform and scalable linear layout visualization for network visual analytics

Chart Design Principles | Hands-On Data Visualization

Tell your story and show it with data, using free and easy-to-learn tools on the web. This introductory book teaches you how to design interactive charts and customized maps for your website, beginning with easy drag-and-drop tools, such as Google Sheets, Datawrapper, and Tableau Public. You will also gradually learn how to edit open-source code templates built with Chart.js, Highcharts, and Leaflet on GitHub. Follow along with the step-by-step tutorials, real-world examples, and online resources. This book is ideal for students, non-profit organizations, small business owners, local governments, journalists, academics, or anyone who wants to tell their story and show the data. No coding experience is required.

Drawing a map of distributed data systems — Martin Kleppmann’s blog

How we created an illustrated guide to help you find your way through the data landscape.

Dremel: interactive analysis of web-scale datasets: Proceedings of the VLDB Endowment: Vol 3, No 1-2

Dremel is a scalable, interactive ad-hoc query system for analysis of read-only nested data. By combining multi-level execution trees and columnar data layout, it is capable of running aggregation queries over trillion-row tables in seconds. The system ...

Your Data Fits in Memory (GraphD Part 1)

We need a fast way to query multiple potentially large sets of data on-demand at interactive speeds. Sometimes the easiest solution to a hard problem is to build the right tool for the job.

VisQuill – Reactive Geometry for Interactive Data Visualization

VisQuill lets you explore data through interactive visuals or build your own using a reactive geometry SDK. Create geospatial and interactive visual systems with real-time updates.

The poster to accompany Designing Data-Intensive Applications (DDIA)

Each chapter in Designing Data-Intensive Applications is accompanied by a map. And we’ve turned those maps into a beautiful poster.

Observable Canvases | Explore and visualize data together

Observable’s collaborative data canvas helps you explore data, perform analysis, and build expressive charts and dashboards.

Sigma.js

a JavaScript library aimed at visualizing graphs of thousands of nodes and edges

On power, aesthetics, materiality and change in data visualization

Notes from the Information+ Conference at MIT/Northeastern University, Boston.

ggtime: A Grammar of Temporal Graphics

Visualizing changes over time is fundamental to learning from the past and anticipating the future. However, temporal semantics can be complicated, and existing visualization tools often struggle to accurately represent these complexities. It is common to use bespoke plot helper functions designed to produce specific graphics, due to the absence of flexible general tools that respect temporal semantics. We address this problem by proposing a grammar of temporal graphics, and an associated software implementation, 'ggtime', that encodes temporal semantics into a declarative grammar for visualizing temporal data. The grammar introduces new composable elements that support visualization across linear, cyclical, quasi-cyclical, and other granularities; standardization of irregular durations; and alignment of time points across different granularities and time zones. It is designed for interoperability with other semantic variables, allowing navigation across the space of visualizations while preserving temporal semantics.