Daniel Kriesels blog about data science, bahn mining and xerox printer

Dark sky was a great example of embedded dataviz in an everyday app. I really liked how the article presents use cases and links them to information to present, a good reference to help junior UX and other team members understand UI/UX use case articulation.

Dark sky was a great example of embedded dataviz in an everyday app. I really liked how the article presents use cases and links them to information to present, a good reference to help junior UX and other team members understand UI/UX use case articulation.

model2data turns data models into analytics-ready datasets. - JB-Analytica/model2data

MediaInfo is a convenient unified display of the most relevant technical and tag data for video and audio files.

On different ways to visualize file system usage.

Easy Data Preparation with latest LLMs-based Operators and Pipelines. - OpenDCAI/DataFlow

GraphQL is a query language for APIs and a runtime for fulfilling those queries with your existing data.

The world’s largest open-source open-data library. Mirrors Sci-Hub, Library Genesis, Z-Library, and more.

A CRDT stack with browser and server storage, with supporting backends.

This open course bridges GIS and data science with practical labs in R and Python.

Topics span vector and raster data, spatial weights, ESDA, clustering, and networks.

Aalto’s BDA course puts the full Gelman et al. workflow online, from priors and posteriors to Stan, hierarchical models, and cross-validation.

Lectures, assignments, and code are all open. This is a real course.

Great interview with Michael Friendly on how the history of data visualization became a research discipline. He walks through the discoveries, forgotten figures, and organizing ideas behind the Milestones Project, and shows how those ideas still shape how we design and read charts today.

Why data visualization matters, and how to make charts more effective, clear, transparent, and sometimes, beautiful.

Saloni Dattani walks through a practical checklist for making visualizations clearer, more honest, and easier to read, with tons of real redesigns and trade-offs you’ll recognize immediately.

This is a thoughtful teardown of a bad temperature chart, followed by nine well-justified redesigns with full ggplot examples.

Line charts, anomaly bands, distributions, and heatmaps show how encoding choices shape interpretation in practice.

The data professions (data science, analysis, engineering, etc.) are highly technical fields, and much online discussion (in particular, on this blog!), conference presentations and classes focus on technical aspects of data work or on the results of data analyses. These discussions are necessary for teaching important aspects of the data trade, but they often ignore the fact that data and analytics work takes place in an interpersonal and organizational context.

An interactive visualization opens up new ways of exploring and sheds a new light onto the evolution of Leonardo Da Vinci’s thoughts