Atlas · Tomesphere

A curl mountain movie

Daniel Stenberg, curl's creator, shares a visualization called 'the mountain' that tracks known vulnerabilities in curl across its entire history from 1998 to 2026. He created a script that renders the vulnerability chart for every month since curl's inception, producing a movie showing how the vulnerability count grew over time. Currently, curl 7.34.0 holds the record with 101 known vulnerabilities. The post also explores a notable drop in vulnerabilities around 2016 following a Cure53 security audit, though the exact cause remains unclear. The data is sourced from curl's vulnerability database and git history, with images assembled into a video using ffmpeg.

Data Analyst Roadmap 2026: What Actually Gets You Hired

A concise guide arguing that data analyst job seekers should focus on five key signals rather than exhaustive skill roadmaps: strong SQL proficiency, a portfolio that connects analysis to business decisions, deliberate fluency in one BI tool matched to the target employer's stack, the ability to communicate a clear 'so what' from data findings, and a clean resume and LinkedIn profile that survive ATS and recruiter screening. The post emphasizes depth over breadth and warns that most roadmap graphics optimize for course-selling rather than what recruiters actually check.

It’s Not the Cow, It’s the How: What 60 Years of Food Data Say About the Climate Cost of Dinner

Phân tích dữ liệu 60 năm về sản xuất thực phẩm cho thấy tiêu thụ thịt toàn cầu đã chững lại nhưng chuyển sang gia cầm, giảm nhẹ cường độ carbon trung bình. Vận chuyển chỉ chiếm ~4,7% khí thải thực phẩm, trong khi sản xuất chiếm ưu thế. Cường độ phát thải bò biến động gấp 70 lần giữa các quốc gia (4–270 kg CO₂e/kg) và giảm 32% kể từ năm 1961. Chỉ số carbon không tương quan tốt với sử dụng nước ngọt (~0,33), có thể gây chuyển dịch tác hại thay vì giảm thiểu.

Là lập trình viên muốn xây dựng các mô hình dự báo hoặc phân tích dữ liệu thực tế về môi trường, bài này giúp bạn hiểu cách xử lý sai lệch trong dữ liệu, đánh giá hiệu quả của các chỉ số đơn giản so với mô hình phức tạp, và ứng dụng kiến thức thống kê để tránh những nhầm lẫn trong việc đo lường tác động môi trường của ngành nông nghiệp.

Choosing the Right Telerik UI for Blazor Chart

A comprehensive guide to all chart types available in Telerik UI for Blazor, covering when and why to use each one. The post walks through 20+ chart types including column, bar, line, area, pie, donut, scatter, bubble, candlestick, OHLC, heatmap, radar, range area, range bar, waterfall, Sankey, stock chart, and trendline. Each chart type is explained with its visual structure and ideal use cases. A decision guide at the end helps developers quickly select the right chart based on their data scenario — comparisons, composition, relationships, ranges, or specialized financial data.

What Makes a Great Dive? The DiveMaxxing Winners

MotherDuck ran a three-week competition called DiveMaxxing where 48 participants built 60 interactive data apps (Dives) — React and SQL apps running live queries against real data, built with AI agents. The winners include 'Who Powers AI?' (Best Overall), a data journalism piece about AI infrastructure; 'Business Graph Explorer' (Most Creative), an entity-graph analytics tool; and 'Supply Chain Command Center' (Community Favorite), a polished operational dashboard with six accessibility-focused color modes. Standout entries also included a US county home-finder pulling 10 federal datasets, a logistics business simulation game, and a DOOM clone where the entire raycasting engine runs in SQL. The competition revealed that Dives go far beyond dashboards — they can be games, simulations, and interactive narratives built by describing an idea to an AI agent.

Flowcharts that belong in the analysis pipeline

The Gmisc R package's flowchart() function has been improved to support reproducible, code-generated research diagrams such as CONSORT charts, cohort derivation flows, data validation pipelines, and longitudinal follow-up diagrams. Unlike drawing tools, these flowcharts live inside the analysis pipeline — counts update automatically, exclusions stay in sync with the analysis script, and figures survive multiple reviewer rounds without manual editing. The post walks through several practical examples with full R code, covering grouped treatment arms, side exclusion branches, dotted return arrows for censored participants, and custom box shapes for data engineering workflows. The update targets Gmisc 3.4.0.

3 Questions: Beyond data-driven aesthetics

MIT Architecture alumnus Alexandros Haridis discusses his exhibition 'Beyond Data-Driven Aesthetics' at MIT's Keller Gallery, which traces the history of computational aesthetics from the 1930s through today. The exhibition translates dense algorithmic research — covering topics like George Birkhoff's mathematical aesthetic measure and the AICAN machine learning system — into physical installations and interactive visualizations. Haridis argues that many questions now framed as novel AI challenges around creativity and aesthetic judgment have deep roots in 20th-century computing research. The work is organized around five themes: Aesthetic Measure, Aesthetic Guidelines, Algorithmic Aesthetics, Aesthetic Appropriation, and Aesthetic Novelty, using design itself as an interpretive method to make opaque computational systems legible and experiential.