Sci² Tool

Interactive Dynamics for Visual Analysis Graphics Jeffrey Heer, Stanford University Ben Shneiderman, University of Maryland, College Park The increasing scale and availability of digital data provides an extraordinary resource for informing public policy, scientific discovery, business strategy, and even our personal lives. Visualization provides a powerful means of making sense of data. The goal of this article is to assist designers, researchers, professional analysts, procurement officers, educators, and students in evaluating and creating visual analysis tools. Our focus on interactive elements presumes a basic familiarity with visualization design. Within each branch of the taxonomy presented here, we describe example systems that exhibit useful interaction techniques. To enable analysts to explore large data sets involving varied data types (e.g., multivariate, geospatial, textual, temporal, networked), flexible visual analysis tools must provide appropriate controls for specifying the data and views of interest. 1. 2. 3.

Source Code & Tutorials Recently, I have released source code for a number of projects. In most cases these projects are released as they were published – while the code is reasonably well-commented, the projects weren’t build specifically to be released and thus may not be shining examples of standards and software architecture. That said, I hope that these releases will serve as inspiration for you to make some things of your own. If you do end up building something interesting, please let me know. Source Code Processing Kepler Visualization[post][GitHub]tree.gowth [post][project][download]GoodMorning! ActionScript 2 Variance [post][project][download]smart.rockets [post][project][download]Particle Swarm Optimization [download] Except where otherwise noted, all source releases are licensed under the CC-GNU GPL version 2.0 or later. Tutorials In addition to source releases, I have also written a number of tutorials designed to help people learn how to use code in a creative context.

Cytoscape: An Open Source Platform for Complex Network Analysis and Visualization SERP | Word Generation • Academic Language Development Note: Bronx schools in NYC are using a special combination of SciGen units to prepare students for a yearly science fair.Download Science Fair Packet 6.4 Is that really a fair test? This unit introduces students to what “fair” means in science and how to make a test fair. Students learn what variables are and how to control them, why multiple trials are used, and the importance of objective measurement. controlling ● fair ● objective ● process ● trial ● variable 6.5 How do we test that idea? In this unit, students learn how to develop a scientific hypothesis, design and perform an experiment to test their hypothesis, and write about the data gathered. affect ● develop ● hypothesis ● identify ● procedure ● reaction 6.6 Ready to conduct your own investigation? This unit investigates the necessary components of a scientific experiment. conduct ● determine ● device ● initial ● investigate ● testable

Transdisciplinarité Un article de Wikipédia, l'encyclopédie libre. La transdisciplinarité est une posture scientifique et intellectuelle. Elle a pour objectif la compréhension de la complexité du monde moderne et du présent. Le mot transdisciplinarité a été inventé par Jean Piaget, en 1970. Éclairage du concept[modifier | modifier le code] La transdisciplinarité est définie par Basarab Nicolescu par trois postulats méthodologiques : l'existence de niveaux de réalité et de perception, la logique du tiers inclus et la complexité. La transdisciplinarité se distingue ainsi de la pluridisciplinarité et l’interdisciplinarité en ce sens qu’elle déborde les disciplines d’une part, mais surtout d’autre part que sa finalité ne reste pas inscrite dans la recherche disciplinaire proprement dite. Ainsi, comme l’indique son préfixe « trans », la transdisciplinarité est la posture scientifique et intellectuelle qui se situe à la fois entre, à travers et au-delà de toute discipline. Annexes[modifier | modifier le code]

The Functional Art: An Introduction to Information Graphics and Visualization The Best Tools for Visualization Visualization is a technique to graphically represent sets of data. When data is large or abstract, visualization can help make the data easier to read or understand. There are visualization tools for search, music, networks, online communities, and almost anything else you can think of. Whether you want a desktop application or a web-based tool, there are many specific tools are available on the web that let you visualize all kinds of data. Here are some of the best: Visualize Social Networks Last.Forward: Thanks to Last.fm's new widget gallery, you can now explore a wide selection of extras to extend your Last.fm experience. Last Forward Friends Sociomap: Friends Sociomap is another Last.fm tools that generates a map of the music compatibility between you and your Last.fm friends. Fidg't:Fidg't is a desktop application that gives you a way to view your networks tagging habits. Fidg't The Digg Tools: One more: Digg Radar . YouTube: Visualize Music Musicovery Last.fm music visual tools: Amazon Data

Fast Thinking and Slow Thinking Visualisation Last week I attended the Association of American Geographers Annual Conference and heard a talk by Robert Groves, Director of the US Census Bureau. Aside the impressiveness of the bureau’s work I was struck by how Groves conceived of visualisations as requiring either fast thinking or slow thinking. Fast thinking data visualisations offer a clear message without the need for the viewer to spend more than a few seconds exploring them. These tend to be much simpler in appearance, such as my map of the distance that London Underground trains travel during rush hour. The explicit message of this map is that surprisingly large distances are covered across the network and that the Central Line rolling stock travels furthest. or the seemingly impenetrable (from a distance at least), but wonderfully intricate hand drawn work of Steven Walter (click image for interactive version). So do the renowned folks at the NY Times Graphics Dept. prefer fast or slow thinking visualisations?

Exploration Education Physical Science Advanced {Homeschool Review} Often when I write a product review, I base my opinion on using the product for six or eight weeks. This year we used nearly all of Exploration Education's Physical Science Advanced program before I finalized the review. I'm just as pleased with the program after more than thirty weeks of lessons as I was when Brennan first started using it last fall. I've had a hard time picking a science program for Brennan. He's not an avid reader so I don't want something that was very reading intensive. Exploration Education has proven to be the perfect balance of text-based materials, online videos, written assignments and hands-on projects. The material covered in the Physical Science Advanced Version progresses at a steady pace. The curriculum set comes neatly packaged in a small box which contains a Student Logbook, a Teacher's Manual, and the supplies required to complete the daily hands-on activities. After learning the new materials, several questions are asked of the student.

Glossaire de la systémique (gr. systÍma: ensemble) Dans le langage courant, mot pouvant signifier: a) un ensemble de composants matÈriels (ex: systËme solaire, systËme pileux, systËme nerveux), b) un ensemble de concepts ou d'idÈes (ex: systËme mÈtrique, systËme philosophique), c) un ensemble de mÈthodes ou de procÈdÈs (systËme d'Èducation, systËme D). Dans le contexte systÈmique, un systËme peut Ítre dÈfini de la faÁon la plus gÈnÈrale comme un tout organisÈ de composants en interaction. Cette dÈfinition gÈnÈrale fait ressortir les trois catÈgories primordiales nÈcessaires pour envisager un systËme gÈnÈrique: le monde des objets (composants), le monde des relations (interactions) et le monde de la totalitÈ (entitÈ existante). De tels systËmes sont caractÈrisÈs par un certain degrÈ de complexitÈ et un certain degrÈ d'autonomie.

A Case Study In How Infographics Can Bend The Truth We’ve made the point time and time again that charts and graphs, though they feel official and true, can lie. Rarely do you get to see that at work, but the good folks at Hyperakt have sent us a prime case study in infographic deception. The subject, of course, is politics--and in particular, the raging debate over whether the rich should be made to pay more taxes. "Using the same data, very different stories can be told depending on different agendas," says Deroy Peraza, one of the founders of Hyperakt. A story from the Wall Street Journal's far-right op-ed page gets us started, with a chart showing how much taxable income is made by Americans ranging from the rich to poor: Looking at that, the conclusion seems glaringly obvious: The rich don’t make so much money! The chart most certainly does not demonstrate the Journal’s point. And look closer: The left side of the chart deals with people who make between $0 and $50K. Whoa whoa whoa! Top image: S.