Our interactive narrative guides viewers through an analysis of San Francisco Bike Sharing data in 2014. instructor Jeffrey Heer. Links to the Canvas discussion for weeks 0-7 are included in the schedule above. Dominikus Baur. Jeffrey Heer, Michael Bostock, and Vadim Ogievetsky. Repositories for UW's Data Visualization Course. Catalog Description: Techniques for creating effective visualizations of data based on principles from graphic design, perceptual psychology, and statistics. A Python data visualization helps a user understand data in a variety of ways: Distribution, mean, median, outlier, skewness, correlation, and spread measurements. Visualization provides one means of combating information overload, as a well-designed visual encoding can supplant cognitive calculations with simpler perceptual inferences and improve comprehension, memory, and decision making. Martin Wattenberg and Fernanda Viégas. InfoVis 2009. Hierarchical Edge Bundles: Visualization of Adjacency Relations in Hierarchical Data. Chapter 10: Information Visualization for Search Interfaces, in, Chapter 11: Information Visualization for Text Analysis, in. Up through week 7, all enrolled students are required to submit at least 1 substantive discussion post per week related to the course readings. D3: Data-Driven Documents. Voyager: Exploratory Analysis via Faceted Browsing of Visualization Recommendations. Students will learn how to design and build interactive visualizations for the web, using the D3.js (Data-Driven Documents) framework. Design and implement visualizations from the idea to the final product according to human perception and cognition; Know the common data-viz techniques for each data domain (multivariate data, networks, texts, cartography, etc) with their technical limitations This visualization is a case study to inform those political and corporate stakeholders interested in creating or expanding bike sharing programs in their communities. IEEE InfoVis 2007. Critiques of arguments made in the papers, Analysis of implications or future directions for work discussed in lecture or readings, Clarification of some point or detail presented in the class, Insightful questions about the readings or answers to other people's questions, Links to web resources or examples that pertain to a lecture or reading. View CSE442-Tools.pdf from CIS 442 at Pierce College. An evolving book. The Death of Interactive Infographics? InfoVis 2006. Students will share the results of their final project as both an interactive website and a short presentation. View CSE442-Narrative.pdf from CIS 442 at Pierce College. Reinventing Explanation. Judge visualization in a critical manner and suggest improvements. CSE 442 - Data Visualization Data and Image Models Jeffrey Heer, Jane Hoffswell Univ. Good comments typically exhibit one or more of the following: See the resources page for visualization tools, data sets, and related web sites. Am. Building off of others' work—including 3rd party libraries, public source code examples, and design ideas—is acceptable and in most cases encouraged. Connor Gramazio, David Laidlaw & Karen Schloss. K. Wongsuphasawat, D. Moritz, A. Satyanarayan & J. Heer. Practical experience building and evaluating visualization systems. Gregor Aisch. Tentative Schedule The schedule is subject to change throughout the semester. Ben Shneiderman. Chris Stolte, Diane Tang, and Pat Hanrahan. In addition to class discussions, students will complete visualization design and data analysis assignments, as well as a final project. This book is not intended to be static. Data visualization helps you make sense of it all. Mark Bruls, Kees Huizing & Jarke van Wijk. 2010. InfoVis 2009. J. Final Projects - Spring 2017. Christopher Healey. Mapping Text with Phrase Nets. of Washington How much data OpenVis Conf 2016. Drive better business decisions by analyzing your enterprise data for insights. CSE 442 - Data Visualization Visualization Tools Jeffrey Heer, Jane Hoffswell Univ. Data Visualization Project CSE 442. Learning Goals & Objectives This course is designed to provide students with the foundations necessary for understanding and extending the current state of the art in data visualization. Polaris: A System for Query, Analysis and Visualization of Multi-dimensional Relational Databases. Design Study Methodology: Reflections from the Trenches and the Stacks. Michael Bostock. An understanding of key visualization techniques and theory, including data models, graphical perception and methods for visual encoding and interaction. Effectiveness of Animation in Trend Visualization. Tim Dwyer. Are you an entrepreneur looking to share data with your investors, stakeholders, or consumers - but you don't know where to start? Introducing d3-scale. Squarified Treemaps. 55-60, 1999. Chapter 11: The Cartogram: Value-by-Area Mapping, in. View CSE442_ Data Visualization31.pdf from CIS 442 at Pierce College. Scott Murray, O'Reilly Press. Topics include visual encoding models, exploratory data analysis, visualization software, interaction techniques, graphical perception, color, animation, high-dimensional data, cartography, network visualization, and text visualization. In Defense of Interactive Graphics. Tamara Munzner. What is Data Visualization?Data is an increasingly potent tool at the negotiating table. To satisfy our curiosity, and also practice our skill in data visualization, we made the following two interactive charts to explore. 2015. Jim Vallandingham. Interactive Dynamics for Visual Analysis. IEEE Transactions on Visualization and Computer Graphics, 2002. 12/2/2020 CSE442: Data Visualization CSE442 Data Visualization (Fall 2020) < Back to home Assignment 3: Interactive How Mariano Rivera Dominates Hitters. A Tour through the Visualization Zoo. InfoVis 2010. Visualization provides one means of combating information overload, as a well-designed visual encoding can supplant cognitive calculations with simpler perceptual inferences and improve comprehension, memory, and decision making. InfoVis 2008. IEEE InfoVis 2014. Michael Correll, Michael Gleicher. (Read Online!) University of Washington - Paul G. Allen School of Computer Science & Engineering, Box 352350 Seattle, WA 98195-2350 (206) 543-1695 voice, (206) 543-2969 FAX, UW Privacy Policy and UW Site Use Agreement. Scott Murray, O'Reilly Press. Plagiarism Policy: Assignments should consist primarily of original work. Programs > Data Visualization: Communicating Data and Complex Ideas Visually (Online) Data Visualization: Communicating Data and Complex Ideas Visually (Online) Whether you are pitching a new idea, persuading others to take action, building a strategy, or making a decision, data is key. Alan MacEachren, Robert Roth, James O'Brien, Bonan Li, Derek Swingley, Mark Gahegan. Exploratory Data Analysis, NIST Engineering Statistics Handbook. Code examples available on GitHub. Scalable, Versatile and Simple Constrained Graph Layout. D3 - A JavaScript library for data-driven DOM manipulation, interaction and animation. UW CSE 442 project to create data visualizations that show trends among SAT scores in NYC. Kennedy Elliott. A Nested Model for Visualization Design and Validation. Cynthia Brewer. Proc. InfoVis 2012. 39 Studies About Human Perception in 30 Minutes. Follow their code on GitHub. There are a wide array of libraries you can use to create Python data visualizations, including Matplotlib, seaborn, Plotly, and others. View CSE442-Animation.pdf from CIS 442 at Pierce College. William S. Cleveland, Robert McGill. However, failure to cite such sources will result in score deductions proportional to the severity of the oversight. Exectution. CSE 442 - Data Visualization Animation Jane Hoffswell University of Washington Why Use Motion? Data Visualization in Python. - UW-CSE442-WI20/FP-wifi-crime-and-sat-scores-of-nyc IEEE Transactions on Visualization and Computer Graphics, 22(1), 649-658, 2016. Each lecture will assume that you have read and are ready to discuss the day's readings. Questions should be posted on Canvas. Perception in Visualization. Visualizing Algorithms. Edward Segel & Jeffrey Heer. Class participation includes both in-class participation as well as participation in the discussion on Canvas. CSE442-17F has one repository available. CSE442: Data Visualization. Build narratives around your data so that its relevance is clearly communicated and easy to understand. assistants Jane Hoffswell Kanit "Ham" Wongsuphasawat. 2012. CSE 442 - Data Visualization The Value of Visualization Jeffrey Heer, Jane Hoffswell Univ. Michael Bostock, Vadim Ogievetsky & Jeffrey Heer. Visual variable to encode data Direct If you have a private question, email the instructors at cse442@cs or come to office hours. Interactive Data Visualization for the Web, 2nd Edition. Chapter 3: The Power of Representation, in. Interactive Data Visualization for the Web, 2nd Edition. 2015. Date: Topic: Reading : Notes: Week 1: August 31: Course and Project Introduction ()September 2 Eurographics Data Visualization 2000. 2017. EuroVis 2009. Late Policy: We will deduct 10% for each day an assignment is late. Design and Redesign in Data Visualization. OpenVis Conf 2017. Each student has 1 pass for skipping comments. Chart IEEE InfoVis 2012. Animated Transitions in Statistical Data Graphics. Proc. InfoVis 2011. View CSE442-ValueOfVisualization.pdf from CIS 442 at Pierce College. Contribute to leem42/cse442-17s.github.io development by creating an account on GitHub. The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations. Exposure to a number of common data domains and corresponding analysis tasks, including multivariate data, networks, text and cartography. CSE442 Data Visualization (Fall 2020) << Back to home. Vega Lite: A Grammar of Interactive Graphics. Michael Nielsen, 2014. Visualization provides one means of combating information overload, as a well-designed visual encoding can supplant cognitive calculations with simpler perceptual inferences and improve comprehension, memory, and decision making. It enables you to look at data differently to discover new answers and insights by: Tell a Visual Data Story Go beyond simply presenting numbers and facts. Jeffrey Heer & George Robertson. Visual Semiotics & Uncertainty Visualization: An Empirical Study. IEEE Conference on Visual Languages, 1996. Capture insights as visual stories. The world is awash with increasing amounts of data, and we must keep afloat with our relatively constant perceptual and cognitive abilities. It is important to attend the lectures and read the readings. The Visual Uncertainty Experience. ACM Queue, 8(5). IEEE Transactions on Visualization and Computer Graphics. Furthermore, visual representations may help engage more diverse audiences in the process of analytic thinking. Interactive Data Visualization for the Web, 2nd Edition. Learn JS Data: Data Cleaning, Manipulation, and Wrangling in JavaScript. Jessica Hullman. Contribute to leem42/cse442-17s.github.io development by creating an account on GitHub. Jeffrey Heer & Ben Shneiderman. of Washington How do people create visualizations? Assignment 1: Visualization Design. Starting in January 2019, we use this book to teach data visualization in the Stanford Data Challenge Lab (DCL) course. Our dataset contains variables including global game sales, publisher names, year-of-release, critic scores, and user scores. The CSE442 Web: © 1993-2021, Department of Computer Science and Engineering, Univerity of Washington. NY Times, February 2010. NY Times, June 2010. The world is awash with increasing amounts of data, and we must keep afloat with our relatively constant perceptual and cognitive abilities. (Read Online!) 2017. of Washington The Big Picture task questions, View CSE442_ Data Visualization4.pdf from CIS 442 at Pierce College. Der CAS Data Visualization ist interdisziplinär und medienübergreifend: Wir vermitteln Ihnen Theorie, Methoden und praktische Fertigkeiten für die Entwicklung und Gestaltung von Informationsgrafiken und Datenvisualisierungen. George Robertson, Roland Fernandez, Danyel Fisher, Bongshin Lee, & John Stasko. Vega - A declarative language for representing visualizations. CSE 442 - Data Visualization Narrative Visualization Matthew Conlen (with material from Jeff Heer, Edward Segel, and Jessica Hullman) About View CSE442_ Data Visualization3.pdf from CIS 442 at Pierce College. GitHub is where UW CSE 442 Data Visualization builds software. So You Think You Can Scroll. Assoc. View CSE442-DataAndImageModels.pdf from CIS 442 at Pierce College.
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