{"id":301,"date":"2021-01-25T20:00:24","date_gmt":"2021-01-25T20:00:24","guid":{"rendered":"https:\/\/groups.cs.umass.edu\/asarv\/?page_id=301"},"modified":"2021-04-26T21:36:21","modified_gmt":"2021-04-26T21:36:21","slug":"data-visualization-and-exploration-spring-2021","status":"publish","type":"page","link":"https:\/\/groups.cs.umass.edu\/asarv\/data-visualization-and-exploration-spring-2021\/","title":{"rendered":"Data Visualization and Exploration &#8211; Spring 2021"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"301\" class=\"elementor elementor-301\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-c6da18d elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"c6da18d\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-911d7d3\" data-id=\"911d7d3\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-a59e83e elementor-tabs-view-horizontal elementor-widget elementor-widget-tabs\" data-id=\"a59e83e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"tabs.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-tabs\">\n\t\t\t<div class=\"elementor-tabs-wrapper\" role=\"tablist\" >\n\t\t\t\t\t\t\t\t\t<div id=\"elementor-tab-title-1731\" class=\"elementor-tab-title elementor-tab-desktop-title\" aria-selected=\"true\" data-tab=\"1\" role=\"tab\" tabindex=\"0\" aria-controls=\"elementor-tab-content-1731\" aria-expanded=\"false\">Overview<\/div>\n\t\t\t\t\t\t\t\t\t<div id=\"elementor-tab-title-1732\" class=\"elementor-tab-title elementor-tab-desktop-title\" aria-selected=\"false\" data-tab=\"2\" role=\"tab\" tabindex=\"-1\" aria-controls=\"elementor-tab-content-1732\" aria-expanded=\"false\">Class Schedule<\/div>\n\t\t\t\t\t\t\t\t\t<div id=\"elementor-tab-title-1733\" class=\"elementor-tab-title elementor-tab-desktop-title\" aria-selected=\"false\" data-tab=\"3\" role=\"tab\" tabindex=\"-1\" aria-controls=\"elementor-tab-content-1733\" aria-expanded=\"false\">Project<\/div>\n\t\t\t\t\t\t\t\t\t<div id=\"elementor-tab-title-1734\" class=\"elementor-tab-title elementor-tab-desktop-title\" aria-selected=\"false\" data-tab=\"4\" role=\"tab\" tabindex=\"-1\" aria-controls=\"elementor-tab-content-1734\" aria-expanded=\"false\">Readings &amp; Discussions<\/div>\n\t\t\t\t\t\t\t\t\t<div id=\"elementor-tab-title-1735\" class=\"elementor-tab-title elementor-tab-desktop-title\" aria-selected=\"false\" data-tab=\"5\" role=\"tab\" tabindex=\"-1\" aria-controls=\"elementor-tab-content-1735\" aria-expanded=\"false\">Homework <\/div>\n\t\t\t\t\t\t\t\t\t<div id=\"elementor-tab-title-1736\" class=\"elementor-tab-title elementor-tab-desktop-title\" aria-selected=\"false\" data-tab=\"6\" role=\"tab\" tabindex=\"-1\" aria-controls=\"elementor-tab-content-1736\" aria-expanded=\"false\">Midterm Exam<\/div>\n\t\t\t\t\t\t\t\t\t<div id=\"elementor-tab-title-1737\" class=\"elementor-tab-title elementor-tab-desktop-title\" aria-selected=\"false\" data-tab=\"7\" role=\"tab\" tabindex=\"-1\" aria-controls=\"elementor-tab-content-1737\" aria-expanded=\"false\">Resources<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t\t<div class=\"elementor-tabs-content-wrapper\" role=\"tablist\" aria-orientation=\"vertical\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-tab-title elementor-tab-mobile-title\" aria-selected=\"true\" data-tab=\"1\" role=\"tab\" tabindex=\"0\" aria-controls=\"elementor-tab-content-1731\" aria-expanded=\"false\">Overview<\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-1731\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"1\" role=\"tabpanel\" aria-labelledby=\"elementor-tab-title-1731\" tabindex=\"0\" hidden=\"false\"><p style=\"text-align: center\"><span style=\"font-family: arial, helvetica, sans-serif;font-size: 12pt;color: #333399\"><strong>Data Visualization and Analysis<\/strong><\/span><\/p><p style=\"text-align: center\"><span style=\"font-family: arial, helvetica, sans-serif\"><span style=\"font-size: 12pt\">Spring 2021 Tuesday, Thursday, 8:30-9:45 AM<\/span><\/span><\/p><p style=\"text-align: center\"><span style=\"font-family: arial, helvetica, sans-serif;font-size: 12pt;color: #333399\"><strong>Instructor:<\/strong> <\/span><span style=\"font-family: arial, helvetica, sans-serif;font-size: 12pt;text-decoration: underline\">Dr. Ali Sarvghad<\/span><\/p><p style=\"text-align: center\"><span style=\"font-family: arial, helvetica, sans-serif\"><span style=\"font-size: 12pt\">asarv@cs.umass.edu,\u00a0<\/span><\/span><span style=\"font-family: arial, helvetica, sans-serif\"><span style=\"font-size: 12pt\"> CICS 344 <\/span><\/span><\/p><p style=\"text-align: center\"><span style=\"font-family: arial, helvetica, sans-serif\"><span style=\"font-size: 12pt\">Virtual office hours: Monday 2:30 &#8211; 3:30 pm. <\/span><\/span><span style=\"color: #00ccff;font-size: 12pt;font-family: arial, helvetica, sans-serif\"><a href=\"https:\/\/umass-amherst.zoom.us\/j\/93320170894\"><span style=\"color: #0000ff\">Zoom link<\/span><\/a><\/span><\/p><p style=\"text-align: center\"><span style=\"font-family: arial, helvetica, sans-serif;font-size: 12pt;color: #333399\"><strong>Teaching Assistant:<\/strong>\u00a0<\/span><span style=\"text-align: left;font-size: 16px;color: #808080\"><span style=\"font-family: arial, helvetica, sans-serif\"><u>Joshua Levine<\/u><\/span><\/span><\/p><p style=\"text-align: center\"><span style=\"font-family: arial, helvetica, sans-serif\"><span style=\"font-size: 16px\">joshualevine@umass.edu<\/span><\/span><\/p><p style=\"text-align: center\"><span style=\"font-family: arial, helvetica, sans-serif\"><span style=\"font-size: 12pt\">Virtual office hours: Friday 1:30-3 pm. <span style=\"color: #0000ff\"><a style=\"color: #0000ff\" href=\"https:\/\/umass-amherst.zoom.us\/j\/99039642559\">Zoom link<\/a><\/span><br \/><\/span><\/span><\/p><hr \/><h3>Course delivery policy for Spring 2021<\/h3><p><span style=\"color: #000000\">Welcome to Data Visualization and Exploration course (590V). Due to the COVID-19 pandemic, the course will be offered remotely. Lectures will be pre-recorded and provided asynchronously, and discussion sessions will be synchronous. We will record and publish discussions for those of you who can not attend the live sessions due to a major time difference. Please see the class schedule for more details about the lectures and discussion topics.<\/span><\/p><hr \/><h3><strong>Course overview<\/strong><\/h3><p><span style=\"color: #000000\">Information visualization is an area of research that helps people analyze and understand data using visualization techniques. The multi-disciplinary area draws from other areas of science, including human-computer interaction, data science, psychology, and art, to develop new visualization methods and understand how (and why) they are effective.<\/span><\/p><p><span style=\"color: #000000\">Information visualization methods are applied to data from many different application domains, including:<\/span><\/p><ul><li><span style=\"color: #000000\">Political reporting and forecasting \u2013 as seen on TV and in the papers in the election season.<\/span><\/li><li><span style=\"color: #000000\">News reporting \u2013 look at the interactive visualizations used by the New York Times, Wall Street Journal, Slate, etc.<\/span><\/li><li><span style=\"color: #000000\">Social science and economic data, such as census and other surveys, and micro and macroeconomic trends.<\/span><\/li><li><span style=\"color: #000000\">Social networking and web traffic to understand patterns of communication<\/span><\/li><li><span style=\"color: #000000\">Business intelligence and business dashboards \u2013 to forecast sales trends, understand competitive marketplace positions, allocate resources, manage production, and logistics.<\/span><\/li><li><span style=\"color: #000000\">Text analysis \u2013 to determine trends and relationships for literary analysis and information retrieval.<\/span><\/li><li><span style=\"color: #000000\">Criminal investigations \u2013 to portray the relationships between events, people, places, and things.<\/span><\/li><li><span style=\"color: #000000\">Performance analysis of computer networks and systems.<\/span><\/li><li><span style=\"color: #000000\">Software engineering \u2013 developing, debugging, and maintaining software.<\/span><\/li><li><span style=\"color: #000000\">Bioinformatics, to understand DNA, gene expressions, systems biology.<\/span><\/li><\/ul><hr \/><h4><span style=\"color: #000000\"><strong>Course objectives<\/strong><\/span><\/h4><ul><li><span style=\"color: #000000\">Learn the principles involved in information visualization<\/span><\/li><li><span style=\"color: #000000\">Understand the wide variety of information visualizations and know what visualizations are appropriate for various types of data and for different goals<\/span><\/li><li><span style=\"color: #000000\">Develop skills in critiquing different visualization techniques in the context of user goals and objectives<\/span><\/li><li><span style=\"color: #000000\">Learn how to implement compelling information visualizations<\/span><\/li><\/ul><hr \/><h4><span style=\"color: #000000\"><strong>Recommended text<\/strong><\/span><\/h4><p><span style=\"color: #000000\">The following textbooks are strongly recommended for this course. Particularly, we will closely follow Tamara Munzner&#8217;s book:<\/span><\/p><ul><li><span style=\"color: #000000\"><span style=\"text-decoration: underline\"><em>Visualization\u00a0Analysis and Design<\/em><\/span>, Tamara Munzner, CRC Press, ISBN 9781466508910. Principles and paradigms of visualization design<\/span><span style=\"color: #000000\">.\u00a0<\/span><\/li><li><span style=\"color: #000000\"><span style=\"text-decoration: underline\"><em>Interactive Data Visualization for the Web<\/em><\/span>, Scott Murray, O\u2019Reilly Media, ISBN 9781449339739. All about D3, the programming tool we will be using for <\/span>homework<span style=\"color: #000000\"> and projects.\u00a0<\/span><\/li><\/ul><hr \/><h4><span style=\"color: #000000\"><strong>Evaluation<\/strong><\/span><\/h4><p>Grading will be based on the project deliverables, midterm exam, class participation, and final project demo. \u00a0Final course grades may be curved (but not always). Grading weights are:<\/p><table style=\"height: 100%;width: 100.178%;border-collapse: collapse\" border=\"0\"><tbody><tr style=\"height: 17px\"><td style=\"width: 420.4px;height: 17px\">Midterm exam<\/td><td style=\"width: 135.6px;height: 17px\">25%<\/td><\/tr><tr style=\"height: 17px\"><td style=\"width: 420.4px;height: 19px\">Homework &amp; Discussion<\/td><td style=\"width: 135.6px;height: 19px\">20%<\/td><\/tr><tr style=\"height: 10px\"><td style=\"width: 420.4px;height: 10px\">Readings<\/td><td style=\"width: 135.6px;height: 10px\">10%<\/td><\/tr><tr style=\"height: 17px\"><td style=\"width: 420.4px;height: 17px\">Course project &amp; deliverables<\/td><td style=\"width: 135.6px;height: 17px\">45%<\/td><\/tr><\/tbody><\/table><p><em><img decoding=\"async\" src=\"https:\/\/i.ya-webdesign.com\/images\/finger-pointing-right-png-11.png\" alt=\"Image result for pointing hand icon\" width=\"45\" height=\"45\" \/>\u00a0 \u00a0 Project details can be found under the Project tab.\u00a0<\/em><\/p><\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-tab-title elementor-tab-mobile-title\" aria-selected=\"false\" data-tab=\"2\" role=\"tab\" tabindex=\"-1\" aria-controls=\"elementor-tab-content-1732\" aria-expanded=\"false\">Class Schedule<\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-1732\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"2\" role=\"tabpanel\" aria-labelledby=\"elementor-tab-title-1732\" tabindex=\"0\" hidden=\"hidden\"><p><span style=\"font-size: 10pt\"><strong>Course Schedule (Lectures, midterm, due dates)<\/strong><\/span><\/p><p><span style=\"color: #0000ff\"><a style=\"color: #0000ff\" href=\"https:\/\/umass-amherst.zoom.us\/j\/98685758459\"><span style=\"font-size: 10pt\">Discussion Zoom Link<\/span><\/a><\/span><\/p><table style=\"border-collapse: collapse;width: 94.891%;height: 424px\" border=\"1\"><tbody><tr style=\"height: 17px\"><td style=\"width: 1.80832%;height: 17px\"><span style=\"font-size: 10pt\"><strong>Week<\/strong><\/span><\/td><td style=\"width: 1.80832%;height: 17px\"><span style=\"font-size: 10pt\"><strong>Date<\/strong><\/span><\/td><td style=\"width: 3.16115%;height: 17px\"><span style=\"font-size: 10pt\"><strong>Activity<br \/><\/strong><\/span><\/td><td style=\"width: 11.2546%;height: 17px\"><span style=\"font-size: 10pt\"><strong>Topic<\/strong><\/span><\/td><td style=\"width: 13.7433%;height: 17px\"><span style=\"font-size: 10pt\"><strong>Homework<br \/><\/strong><\/span><\/td><td style=\"width: 7.59494%;height: 17px\"><span style=\"font-size: 10pt\"><strong>Reading<\/strong><\/span><\/td><td style=\"width: 3.61664%;height: 17px\"><span style=\"font-size: 10pt;color: #ff6600\"><strong>Project Due dates<\/strong><\/span><\/td><\/tr><tr style=\"background-color: #ffffff\"><td style=\"width: 1.80832%;height: 34px\" rowspan=\"2\"><span style=\"font-size: 10pt\"><strong>1<\/strong><\/span><br \/><span style=\"font-size: 10pt\"><strong><br \/><\/strong><\/span><\/td><td style=\"width: 1.80832%;height: 17px\"><span style=\"font-size: 10pt\">2\/2<\/span><\/td><td style=\"width: 3.16115%;height: 17px\"><span style=\"font-size: 10pt\">Lecture<br \/><\/span><\/td><td style=\"width: 11.2546%;height: 17px\"><span style=\"font-size: 10pt\">Course introduction<\/span><\/td><td style=\"width: 13.7433%;height: 17px\">\u00a0<\/td><td style=\"width: 7.59494%;height: 17px\">\u00a0<\/td><td style=\"width: 3.61664%;height: 17px\">\u00a0<\/td><\/tr><tr style=\"background-color: #ffffff\"><td style=\"width: 1.80832%;height: 17px\"><span style=\"font-size: 10pt\">2\/4<\/span><\/td><td style=\"width: 3.16115%;height: 17px\"><span style=\"font-size: 10pt\">Lecture<br \/><\/span><\/td><td style=\"width: 11.2546%;height: 17px\"><span style=\"font-size: 10pt\">Data and task abstraction<\/span><\/td><td style=\"width: 13.7433%;height: 17px\">HW-1: data and task abstraction<\/td><td style=\"width: 7.59494%;height: 17px\">P1: <span style=\"color: #3366ff\"><a style=\"color: #3366ff\" href=\"https:\/\/drive.google.com\/file\/d\/1I6sZ7UvcGJnTKs9YAUNzvxLZOrMbXUfk\/view?usp=sharing\"><span style=\"color: #3366ff\">Bridging From Goals to Tasks with Design Study Analysis Reports<\/span><\/a><\/span><\/td><td style=\"width: 3.61664%;height: 17px\">\u00a0<\/td><\/tr><tr style=\"background-color: #ffffff;height: 17px\"><td style=\"width: 1.80832%;height: 36px\" rowspan=\"2\"><span style=\"font-size: 10pt\"><strong>2<\/strong><\/span><br \/><span style=\"font-size: 10pt\"><strong><br \/><\/strong><\/span><\/td><td style=\"width: 1.80832%;height: 18px\"><span style=\"font-size: 10pt\">2\/9<\/span><\/td><td style=\"width: 3.16115%;height: 18px\"><span style=\"font-size: 10pt\">Discussion<br \/><\/span><\/td><td style=\"width: 11.2546%;height: 18px\">HW-1 <span style=\"color: #ff6600\">(due 8th)<\/span><\/td><td style=\"width: 13.7433%;height: 18px\">\u00a0<\/td><td style=\"width: 7.59494%;height: 18px\">\u00a0<\/td><td style=\"width: 3.61664%;height: 18px\">\u00a0<\/td><\/tr><tr style=\"height: 18px\"><td style=\"width: 1.80832%;height: 18px\"><span style=\"font-size: 10pt\">2\/11<\/span><\/td><td style=\"width: 3.16115%;height: 18px\"><span style=\"font-size: 10pt\">Lecture<br \/><\/span><\/td><td style=\"width: 11.2546%;height: 18px\"><span style=\"font-size: 10pt\">D3: set up, drawing with SVG<br \/><\/span><\/td><td style=\"width: 13.7433%;height: 18px\">HW-2: driving with SVG<\/td><td style=\"width: 7.59494%;height: 18px\">\u00a0<\/td><td style=\"width: 3.61664%;height: 18px\"><p><span style=\"font-weight: 400;color: #ff6600\"><strong>Project:<\/strong> groups (12th),<\/span><\/p><p><span style=\"font-weight: 400;color: #ff6600\"> HW-2 (15th)<\/span><\/p><\/td><\/tr><tr style=\"background-color: #ffffff\"><td style=\"width: 1.80832%;height: 27px\" rowspan=\"2\"><span style=\"font-size: 10pt\"><strong>3<\/strong><\/span><br \/><span style=\"font-size: 10pt\"><strong><br \/><\/strong><\/span><\/td><td style=\"width: 1.80832%;height: 10px\"><span style=\"font-size: 10pt\">2\/16<\/span><\/td><td style=\"width: 3.16115%;height: 10px\"><span style=\"font-size: 10pt\">Discussion<\/span><\/td><td style=\"height: 10px;width: 11.2546%\">HW-2 <span style=\"color: #ff6600\">(due 15th)<\/span><\/td><td style=\"width: 13.7433%;height: 10px\">\u00a0<\/td><td style=\"width: 7.59494%;height: 10px\">\u00a0<\/td><td style=\"width: 3.61664%;height: 10px\">\u00a0<\/td><\/tr><tr style=\"background-color: #ffffff\"><td style=\"width: 1.80832%;height: 17px\"><span style=\"font-size: 10pt\">2\/18<\/span><\/td><td style=\"width: 3.16115%;height: 17px\"><span style=\"font-size: 10pt\">Lecture<br \/><\/span><\/td><td style=\"width: 11.2546%;height: 17px\"><span style=\"font-size: 10pt\">Marks &amp; Channels<\/span><\/td><td style=\"width: 13.7433%;height: 17px\">HW-3: Marks &amp; channels\u00a0<\/td><td style=\"width: 7.59494%;height: 17px\">P2: <a href=\"https:\/\/drive.google.com\/file\/d\/1RQOhTQOwiMMzLjJsbF5jBBVM8bW0HoV7\/view?usp=sharing\"><span style=\"color: #3366ff\">Crowdsourcing graphical perception<\/span><\/a><\/td><td style=\"width: 3.61664%;height: 17px\"><span style=\"font-weight: 400;color: #ff6600\"><strong>Project:<\/strong> dataset<\/span><\/td><\/tr><tr style=\"background-color: #ffffff\"><td style=\"width: 1.80832%;height: 33px\" rowspan=\"2\"><span style=\"font-size: 10pt\"><strong>4<\/strong><\/span><br \/><span style=\"font-size: 10pt\"><strong><br \/><\/strong><\/span><\/td><td style=\"width: 1.80832%;height: 16px\"><span style=\"font-size: 10pt\">2\/23<\/span><\/td><td style=\"width: 3.16115%;height: 16px\"><span style=\"font-size: 10pt\">Discussion<\/span><\/td><td style=\"height: 16px;width: 11.2546%\">HW-3 <span style=\"color: #ff6600\">(due 22nd)<\/span><\/td><td style=\"width: 13.7433%;height: 16px\">\u00a0<\/td><td style=\"width: 7.59494%;height: 16px\">\u00a0<\/td><td style=\"width: 3.61664%;height: 16px\">\u00a0<\/td><\/tr><tr style=\"background-color: #ffffff\"><td style=\"width: 1.80832%;height: 17px\"><span style=\"font-size: 10pt\">2\/25<\/span><\/td><td style=\"width: 3.16115%;height: 17px\"><span style=\"font-size: 10pt\">Lecture<br \/><\/span><\/td><td style=\"width: 11.2546%;height: 17px\"><span style=\"font-size: 10pt\">Color Maps &#8211; Visualizing tabular data<br \/><\/span><\/td><td style=\"width: 13.7433%;height: 17px\">HW-4: colormaps &amp; tabular data<\/td><td style=\"width: 7.59494%;height: 17px\">P3: <a href=\"https:\/\/drive.google.com\/file\/d\/1VFntQVdHCe77VDaKYO2Xbo1GXZEk_7yO\/view?usp=sharing\"><span style=\"color: #3366ff\">Task-Based Effectiveness of Basic Visualizations<\/span><\/a><\/td><td style=\"width: 3.61664%;height: 17px\"><span style=\"font-weight: 400;color: #ff6600\"><strong>Project:<\/strong> user and tasks<\/span><\/td><\/tr><tr style=\"background-color: #ffffff\"><td style=\"width: 1.80832%;height: 34px\" rowspan=\"2\"><span style=\"font-size: 10pt\"><strong>5<\/strong><\/span><br \/><span style=\"font-size: 10pt\"><strong><br \/><\/strong><\/span><\/td><td style=\"width: 1.80832%;height: 17px\"><span style=\"font-size: 10pt\">3\/2<\/span><\/td><td style=\"width: 3.16115%;height: 17px\"><span style=\"font-size: 10pt\">Discussion<\/span><\/td><td style=\"width: 11.2546%;height: 17px\">HW-4 <span style=\"color: #ff6600\">(due 1st)<\/span><\/td><td style=\"width: 13.7433%;height: 17px\">\u00a0<\/td><td style=\"width: 7.59494%;height: 17px\">\u00a0<\/td><td style=\"width: 3.61664%;height: 17px\">\u00a0<\/td><\/tr><tr style=\"height: 17px\"><td style=\"width: 1.80832%;height: 17px\"><span style=\"font-size: 10pt\">3\/4<\/span><\/td><td style=\"width: 3.16115%;height: 17px\"><span style=\"font-size: 10pt\">Lecture<br \/><\/span><\/td><td style=\"height: 17px;width: 11.2546%\"><span style=\"font-size: 10pt\">D3: making basic charts, scales, axes<br \/><\/span><\/td><td style=\"width: 13.7433%;height: 17px\">HW-5: practice building charts with D3<\/td><td style=\"width: 7.59494%;height: 17px\">\u00a0<\/td><td style=\"width: 3.61664%;height: 17px\">\u00a0<\/td><\/tr><tr style=\"background-color: #ffffff\"><td style=\"width: 1.80832%;height: 34px\" rowspan=\"2\"><span style=\"font-size: 10pt\"><strong>6<\/strong><\/span><br \/><span style=\"font-size: 10pt\"><strong><br \/><\/strong><\/span><\/td><td style=\"width: 1.80832%;height: 17px\"><span style=\"font-size: 10pt\">3\/9<\/span><\/td><td style=\"width: 3.16115%;height: 17px\"><span style=\"font-size: 10pt\">Discussion<\/span><\/td><td style=\"width: 11.2546%;height: 17px\"><span style=\"font-size: 10pt\">\u00a0HW-5 <span style=\"color: #ff6600\">(due 8th)<\/span><\/span><\/td><td style=\"width: 13.7433%;height: 17px\">\u00a0<\/td><td style=\"width: 7.59494%;height: 17px\">\u00a0<\/td><td style=\"width: 3.61664%;height: 17px\"><span style=\"font-weight: 400;color: #ff6600\"><strong>Project:<\/strong> data &amp; task abstraction<\/span><\/td><\/tr><tr style=\"height: 17px\"><td style=\"width: 1.80832%;height: 17px\"><span style=\"font-size: 10pt\">3\/11<\/span><\/td><td style=\"width: 3.16115%;height: 17px\"><span style=\"font-size: 10pt\">Lecture<br \/><\/span><\/td><td style=\"width: 11.2546%;height: 17px\"><span style=\"font-size: 10pt\">Visualizing networks and Trees<\/span><\/td><td style=\"width: 13.7433%;height: 17px\">\u00a0<\/td><td style=\"width: 7.59494%;height: 17px\">P4:\u00a0<span style=\"color: #3366ff\"><a style=\"color: #3366ff\" href=\"https:\/\/drive.google.com\/file\/d\/1NkiaLNhBdegGbZGoaR1qmzzOKb5PnK7-\/view?usp=sharing\">NodeTrix: A Hybrid Visualization of Social Networks<\/a><\/span><\/td><td style=\"width: 3.61664%;height: 17px\">\u00a0<\/td><\/tr><tr style=\"background-color: #ffffff\"><td style=\"width: 1.80832%;height: 34px\" rowspan=\"2\"><span style=\"font-size: 10pt\"><strong>7<\/strong><\/span><br \/><span style=\"font-size: 10pt\"><strong><br \/><\/strong><\/span><\/td><td style=\"width: 1.80832%;height: 17px\"><span style=\"font-size: 10pt\">3\/16<\/span><\/td><td style=\"width: 3.16115%;height: 17px\"><strong><span style=\"font-size: 10pt;color: #ff6600\">MIDTERM<\/span><\/strong><\/td><td style=\"height: 17px;width: 11.2546%\">\u00a0<\/td><td style=\"height: 17px;width: 13.7433%\">\u00a0<\/td><td style=\"height: 17px;width: 7.59494%\">\u00a0<\/td><td style=\"width: 3.61664%;height: 17px\">\u00a0<\/td><\/tr><tr style=\"background-color: #ffffff\"><td style=\"width: 1.80832%;height: 17px\"><span style=\"font-size: 10pt\">3\/18<\/span><\/td><td style=\"width: 3.16115%;height: 17px\"><span style=\"font-size: 10pt\">No Class<br \/><\/span><\/td><td style=\"width: 11.2546%;height: 17px\"><span style=\"font-size: 10pt\">No Class<br \/><\/span><\/td><td style=\"width: 13.7433%;height: 17px\">\u00a0<\/td><td style=\"width: 7.59494%;height: 17px\">\u00a0<\/td><td style=\"width: 3.61664%;height: 17px\">\u00a0<\/td><\/tr><tr style=\"background-color: #ffffff\"><td style=\"width: 1.80832%;height: 20px\" rowspan=\"2\"><span style=\"font-size: 10pt\"><strong>8<\/strong><\/span><br \/><span style=\"font-size: 10pt\"><strong><br \/><\/strong><\/span><\/td><td style=\"width: 1.80832%;height: 10px\"><span style=\"font-size: 10pt\">3\/23<\/span><\/td><td style=\"width: 3.16115%;height: 10px\"><span style=\"font-size: 10pt\">Lecture<\/span><\/td><td style=\"height: 10px;width: 11.2546%\">Handle data complexity<\/td><td style=\"width: 13.7433%;height: 10px\">\u00a0<\/td><td style=\"width: 7.59494%;height: 10px\">P5: <span style=\"color: #3366ff\"><a style=\"color: #3366ff\" href=\"https:\/\/drive.google.com\/file\/d\/1F6bjFYhD3syRIGIvNYQ0XaYhj5DOkxu-\/view?usp=sharing\">Graph-Theoretic Scagnostics<\/a><\/span><\/td><td style=\"width: 3.61664%;height: 10px\">\u00a0<\/td><\/tr><tr style=\"height: 18px\"><td style=\"width: 1.80832%;height: 10px\"><span style=\"font-size: 10pt\">3\/25<\/span><\/td><td style=\"width: 3.16115%;height: 10px\"><span style=\"font-size: 10pt\">Discussion<\/span><\/td><td style=\"height: 10px;width: 11.2546%\"><span style=\"font-size: 10pt\">\u00a0<\/span><\/td><td style=\"width: 13.7433%;height: 10px\">\u00a0<\/td><td style=\"width: 7.59494%;height: 10px\">\u00a0<\/td><td style=\"width: 3.61664%;height: 10px\"><span style=\"font-weight: 400;color: #ff6600\"><strong>Project:<\/strong> design<\/span><\/td><\/tr><tr style=\"background-color: #ffffff\"><td style=\"width: 1.80832%;height: 20px\" rowspan=\"2\"><span style=\"font-size: 10pt\"><strong>9<\/strong><\/span><br \/><span style=\"font-size: 10pt\"><strong><br \/><\/strong><\/span><\/td><td style=\"width: 1.80832%;height: 10px\"><span style=\"font-size: 10pt\">3\/30<\/span><\/td><td style=\"width: 3.16115%;height: 10px\"><span style=\"font-size: 10pt\">Lecture<\/span><\/td><td style=\"height: 10px;width: 11.2546%\">D3: interactivity, layouts<\/td><td style=\"width: 13.7433%;height: 10px\"><span style=\"font-size: 10px\">\u00a0<\/span><\/td><td style=\"width: 7.59494%;height: 10px\">\u00a0<\/td><td style=\"width: 3.61664%;height: 10px\">\u00a0<\/td><\/tr><tr style=\"background-color: #ffffff\"><td style=\"width: 1.80832%;height: 10px\"><span style=\"font-size: 10pt\">4\/1<\/span><\/td><td style=\"width: 3.16115%;height: 10px\"><span style=\"font-size: 10pt\">Discussion<\/span><\/td><td style=\"width: 11.2546%;height: 10px\"><span style=\"font-size: 10pt\">HW-6 <span style=\"color: #ff6600\">(due before discussion)<\/span><\/span><\/td><td style=\"width: 13.7433%;height: 10px\"><span style=\"font-size: 10px\">\u00a0<\/span><\/td><td style=\"width: 7.59494%;height: 10px\">\u00a0<\/td><td style=\"width: 3.61664%;height: 10px\">\u00a0<\/td><\/tr><tr style=\"background-color: #ffffff\"><td style=\"width: 1.80832%;height: 27px\" rowspan=\"2\"><span style=\"font-size: 10pt\"><strong>10<\/strong><\/span><br \/><span style=\"font-size: 10pt\"><strong><br \/><\/strong><\/span><\/td><td style=\"width: 1.80832%;height: 17px\"><span style=\"font-size: 10pt\">4\/6<\/span><\/td><td style=\"width: 3.16115%;height: 17px\"><span style=\"font-size: 10pt\">Lecture<\/span><\/td><td style=\"width: 11.2546%;height: 17px\"><span style=\"font-size: 10pt\">Uncertainty visualization<\/span><\/td><td style=\"width: 13.7433%;height: 17px\">\u00a0<\/td><td style=\"width: 7.59494%;height: 17px\">P6: <span style=\"color: #3366ff\"><a style=\"color: #3366ff\" href=\"https:\/\/drive.google.com\/file\/d\/1lLy73NVYwOcst8MBUtmT5mrqz_nreOyK\/view?usp=sharing\">Hypothetical Outcome Plots Help Untrained Observers Judge Trends in Ambiguous Data<\/a><\/span><\/td><td style=\"width: 3.61664%;height: 17px\">\u00a0<\/td><\/tr><tr style=\"background-color: #ffffff\"><td style=\"width: 1.80832%;height: 10px\"><span style=\"font-size: 10pt\">4\/8<\/span><\/td><td style=\"width: 3.16115%;height: 10px\"><span style=\"font-size: 10pt\">Lecture<\/span><\/td><td style=\"width: 11.2546%;height: 10px\"><span style=\"font-size: 10pt\">Evaluation techniques in Visualization<\/span><\/td><td style=\"width: 13.7433%;height: 10px\">\u00a0<\/td><td style=\"width: 7.59494%;height: 10px\">P7: <span style=\"color: #3366ff\"><a style=\"color: #3366ff\" href=\"https:\/\/drive.google.com\/file\/d\/1pfKkalmVAPIcQ1KUqoh7Qsu6G3jmj4GK\/view?usp=sharing\">A Systematic Review on the Practice of Evaluating Visualization<\/a><\/span><\/td><td style=\"width: 3.61664%;height: 10px\">\u00a0<\/td><\/tr><tr style=\"background-color: #ffffff\"><td style=\"width: 1.80832%;height: 34px\" rowspan=\"2\"><span style=\"font-size: 10pt\"><strong>11<\/strong><\/span><br \/><span style=\"font-size: 10pt\"><strong><br \/><\/strong><\/span><\/td><td style=\"width: 1.80832%;height: 17px\"><span style=\"font-size: 13.3333px\">4\/13<\/span><\/td><td style=\"width: 3.16115%;height: 17px\"><span style=\"font-size: 10pt\">Lecture<\/span><\/td><td style=\"width: 11.2546%;height: 17px\"><span style=\"font-size: 10pt\">Storytelling with data<\/span><\/td><td style=\"width: 13.7433%;height: 17px\">\u00a0<\/td><td style=\"width: 7.59494%;height: 17px\">\u00a0<\/td><td style=\"width: 3.61664%;height: 17px\">\u00a0<\/td><\/tr><tr style=\"background-color: #ffffff\"><td style=\"width: 1.80832%;height: 17px\"><span style=\"font-size: 10pt\">4\/15<\/span><\/td><td style=\"width: 3.16115%;height: 17px\"><span style=\"font-size: 10pt\">Cancelled<\/span><\/td><td style=\"width: 11.2546%;height: 17px\"><span style=\"font-size: 10pt\">Cancelled<\/span><\/td><td style=\"width: 13.7433%;height: 17px\">\u00a0<\/td><td style=\"width: 7.59494%;height: 17px\">\u00a0<\/td><td style=\"width: 3.61664%;height: 17px\">\u00a0<\/td><\/tr><tr style=\"background-color: #ffffff\"><td style=\"width: 1.80832%;height: 34px\" rowspan=\"2\"><span style=\"font-size: 10pt\"><strong>12<\/strong><\/span><br \/><span style=\"font-size: 10pt\"><strong><br \/><\/strong><\/span><\/td><td style=\"width: 1.80832%;height: 17px\"><span style=\"font-size: 10pt\">4\/20<\/span><\/td><td style=\"width: 3.16115%;height: 17px\"><span style=\"font-size: 10pt\">No class<\/span><\/td><td style=\"width: 11.2546%;height: 17px\"><span style=\"font-size: 10pt\">No class<br \/><\/span><\/td><td style=\"width: 13.7433%;height: 17px\">\u00a0<\/td><td style=\"width: 7.59494%;height: 17px\">\u00a0<\/td><td style=\"width: 3.61664%;height: 17px\">\u00a0<\/td><\/tr><tr style=\"background-color: #ffffff\"><td style=\"width: 1.80832%;height: 17px\"><span style=\"font-size: 10pt\">4\/22<\/span><\/td><td style=\"width: 3.16115%;height: 17px\"><span style=\"font-size: 10pt\">Guest lecture: Cindy Xiao<br \/><\/span><\/td><td style=\"width: 11.2546%;height: 17px\"><span style=\"font-size: 10pt\">Cognitive biases and visual data analysis<br \/><\/span><\/td><td style=\"width: 13.7433%;height: 17px\">\u00a0<\/td><td style=\"width: 7.59494%;height: 17px\">\u00a0<\/td><td style=\"width: 3.61664%;height: 17px\">\u00a0<\/td><\/tr><tr style=\"background-color: #ffffff\"><td style=\"width: 1.80832%;height: 20px\" rowspan=\"2\"><span style=\"font-size: 10pt\"><strong>13<\/strong><\/span><br \/><span style=\"font-size: 10pt\"><strong><br \/><\/strong><\/span><span style=\"font-size: 10pt\"><strong><br \/><\/strong><\/span><\/td><td style=\"width: 1.80832%;height: 10px\"><span style=\"font-size: 10pt\">4\/27<\/span><\/td><td style=\"width: 3.16115%;height: 10px\"><span style=\"font-size: 10pt\">Guest lecture: Narges Mahyar<br \/><\/span><\/td><td style=\"width: 11.2546%;height: 10px\">Application example: Digital civics<\/td><td style=\"width: 13.7433%;height: 10px\">\u00a0<\/td><td style=\"width: 7.59494%;height: 10px\">\u00a0<\/td><td style=\"width: 3.61664%;height: 10px\">\u00a0<\/td><\/tr><tr style=\"height: 33px\"><td style=\"width: 1.80832%;height: 10px\"><span style=\"font-size: 10pt\">4\/29<\/span><\/td><td style=\"width: 3.16115%;height: 10px\"><span style=\"font-size: 10pt;color: #ff6600\">Final Project Demo<br \/><\/span><\/td><td style=\"width: 11.2546%;height: 10px\">\u00a0<\/td><td style=\"width: 13.7433%;height: 10px\"><span style=\"font-size: 10pt\">\u00a0<\/span><\/td><td style=\"width: 7.59494%;height: 10px\"><span style=\"font-size: 10pt\">\u00a0<\/span><\/td><td style=\"width: 3.61664%;height: 10px\"><span style=\"font-size: 10pt\">\u00a0<\/span><\/td><\/tr><tr style=\"background-color: #ffffff\"><td style=\"width: 1.80832%;height: 20px\"><span style=\"font-size: 10pt\"><strong>14<\/strong><\/span><span style=\"font-size: 10pt\"><strong><br \/><\/strong><\/span><\/td><td style=\"width: 1.80832%;height: 20px\"><span style=\"font-size: 10pt\">5\/4<\/span><\/td><td style=\"width: 3.16115%;height: 20px\"><span style=\"font-size: 10pt;color: #ff6600\">Final Project Demo<br \/><\/span><\/td><td style=\"width: 11.2546%;height: 20px\">\u00a0<\/td><td style=\"width: 13.7433%;height: 20px\">\u00a0<\/td><td style=\"width: 7.59494%;height: 20px\">\u00a0<\/td><td style=\"width: 3.61664%;height: 20px\">\u00a0<\/td><\/tr><\/tbody><\/table><\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-tab-title elementor-tab-mobile-title\" aria-selected=\"false\" data-tab=\"3\" role=\"tab\" tabindex=\"-1\" aria-controls=\"elementor-tab-content-1733\" aria-expanded=\"false\">Project<\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-1733\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"3\" role=\"tabpanel\" aria-labelledby=\"elementor-tab-title-1733\" tabindex=\"0\" hidden=\"hidden\"><h2>Project overview<\/h2><p>The course project carries <strong>45%<\/strong> of the overall course grade. This is a group project (unless the course instructor approves an individual work). Expectations will <span style=\"text-decoration: underline\">NOT<\/span> be adjusted according to group size.<\/p><ul><li><h4>Groups<\/h4><ul><li><p>Each group <span style=\"text-decoration: underline\">MUST<\/span> be comprised of both grad and undergrad students. The preferred size of a group is 3. Groups smaller than 2 and bigger than 4 will not be allowed (unless under special circumstances and with the instructor&#8217;s approval).\u00a0<\/p><\/li><li>You can start looking for teammates as early as the first day of classes. T<span style=\"text-decoration: underline\">he deadline for having a team is <\/span><strong><span style=\"text-decoration: underline;color: #ff6600\">Feb 12<\/span>,\u00a0<\/strong> the last day of add\/drop. <span style=\"text-decoration: underline\">Reach out to us before the deadline if you have difficulty finding a team.<\/span><\/li><\/ul><\/li><\/ul><ul><li><h4>Project proposal (45%) \u00a0<\/h4><ul><li>Data selection (10%)<\/li><li>Users and tasks identification (10%)<\/li><li>Data and task abstraction (10%)<\/li><li>Design (15%)<\/li><li><img decoding=\"async\" class=\"\" src=\"https:\/\/i.ya-webdesign.com\/images\/finger-pointing-right-png-11.png\" alt=\"Image result for pointing hand icon\" width=\"36\" height=\"36\" \/> <em>Scroll down to see details.<\/em><\/li><\/ul><\/li><li><h4>User evaluation (Optional- Bonus 5%)\u00a0\u00a0<\/h4><ul><li>Report of methodology, data analysis, and findings<\/li><li><img decoding=\"async\" class=\"\" src=\"https:\/\/i.ya-webdesign.com\/images\/finger-pointing-right-png-11.png\" alt=\"Image result for pointing hand icon\" width=\"36\" height=\"36\" \/> <em>Scroll down to see details.<\/em><\/li><\/ul><\/li><li><h4>Final demo (50%)<\/h4><ul><li>Live demo of the implemented data visualization tool<\/li><li><img decoding=\"async\" class=\"\" src=\"https:\/\/i.ya-webdesign.com\/images\/finger-pointing-right-png-11.png\" alt=\"Image result for pointing hand icon\" width=\"36\" height=\"36\" \/> <em>Scroll down to see details.<\/em><\/li><\/ul><\/li><li><h4>Final report (5%)<\/h4><ul><li>Implementation details\u00a0<\/li><li>Evaluation results (if any)<\/li><li><img decoding=\"async\" class=\"\" src=\"https:\/\/i.ya-webdesign.com\/images\/finger-pointing-right-png-11.png\" alt=\"Image result for pointing hand icon\" width=\"36\" height=\"36\" \/> <em>Scroll down to see details.<\/em><\/li><\/ul><\/li><li><h4>Late and missing submission policy<\/h4><ul><li>Late submission = 50% loss of project deliverable&#8217;s mark<\/li><li>No submission = 0\u00a0<\/li><li><img decoding=\"async\" class=\"\" src=\"https:\/\/i.ya-webdesign.com\/images\/finger-pointing-right-png-11.png\" alt=\"Image result for pointing hand icon\" width=\"36\" height=\"36\" \/> <em>Scroll down to see details.<\/em><\/li><\/ul><\/li><\/ul><p>This project accounts for 45% of your grade in this course and will require a significant amount of time and effort. <span style=\"text-decoration: underline\">In particular, I&#8217;m seeking creative projects showcasing interesting ideas related to current challenges and issues we face today such as the impact of the pandemic on different aspects of our lives,\u00a0 minorities and underrepresented communities and groups, and social equity and justice.<\/span> No matter what topic you choose, I am expecting a high-quality project. A good project should consist of visualization designs and a software artifact that implements the designs. Interaction and data manipulation are keys in information visualization, and it is difficult to understand the interaction issues in your project without a running system.\u00a0 Ideally, I would like your efforts to be innovative and to result in some form of potential publication to similar venues and styles as the papers that we will read throughout the semester.<\/p><p>You should develop a web-deployable\u00a0system so that your system can be shown to everyone in the world, and use D3 for visualizing data! Arguments will be entertained for using different visualization toolkits, but in general, D3 is preferred. Using a different toolkit should be approved by the professor prior to starting any code<\/p><p><strong>Two examples of previous projects can be found <span style=\"color: #00ccff\"><a style=\"color: #00ccff\" href=\"https:\/\/shezanmirzan.github.io\/DataVis-Mental-Health\/\">here<\/a><\/span> and <span style=\"color: #00ccff\"><a style=\"color: #00ccff\" href=\"http:\/\/xiaoliu1990.gitee.io\/videogamesales\/\">here<\/a>.<\/span><\/strong><\/p><hr \/><h2>Project details<\/h2><p>The idea of the project is to take the knowledge and background that you are learning this semester about Information Visualization and put it to good use in a new, creative effort. A real key to the project, however, is to select a data set that people will find interesting and intriguing. Even better would be to select a data set with a clearly identified set of &#8220;users&#8221; or &#8220;analysts&#8221; who care deeply about that data. Select a topic that people want to know more about! I cannot emphasize strongly enough the importance of your topic and data set.<\/p><h4>Project proposal<\/h4><p>The project proposal is a document that you will gradually complete. The proposal has four major components, listed below:<\/p><p><strong>1- Data selection (10%). <span style=\"color: #ff6600\">Due on: 2\/18<\/span><\/strong><\/p><p>You start your project by selecting a dataset, and a problem. You can use your own data (from a school project, self-quantified, etc) or find and select publicly available data online:<\/p><ul><li>BYOD (Bring Your Own Data)<ul><li>you (or your teammates) have your own data to analyze such as:<ul><li>thesis\/research topic<\/li><li>personal interest<\/li><li>dovetail with another course (sometimes works, but timing may be tricky)<\/li><\/ul><\/li><\/ul><\/li><li>FDOI (Find Data of Interest)<ul><li>many existing datasets on the internet <strong>(e.g., <span style=\"color: #00ccff\"><a style=\"color: #00ccff\" href=\"https:\/\/www.kaggle.com\/\">Kaggle<\/a>, <a style=\"color: #00ccff\" href=\"http:\/\/data.un.org\/\">UN Data<\/a><\/span><\/strong>)<\/li><li>Can be tricky to determine reasonable analysis tasks that users may want to do<\/li><\/ul><\/li><\/ul><p>If you select a tabular dataset online, there should contain a minimum of 10 variables and 500 records. We will consider smaller datasets upon the approval by the instructor.\u00a0<\/p><p><em>The deliverable in this part is a document with information about the data set, such as personal or public, the name of the dataset, and a one-paragraph description of data origin and high-level semantics. <\/em><\/p><p><em><span style=\"text-decoration: underline\">All the submitted documents for this course should be single-spaced with a 12 font size.<\/span>\u00a0\u00a0<\/em><\/p><p><strong>2-Users and tasks identification (10%). <span style=\"color: #ff6600\">Due on: 2\/25<\/span><\/strong><\/p><p>In this part, you identify describe the intended user(s) who need to explore, analyze, and make sense of data. These descriptions can be based on real users or personas (<span style=\"color: #00ccff\"><a style=\"color: #00ccff\" href=\"https:\/\/www.interaction-design.org\/literature\/article\/personas-why-and-how-you-should-use-them\">what is a persona?<\/a><\/span>). We encourage you to consider 3-4 different users, with varying interest in the data to enrich the space of exploration (and tool design). Each of these users needs to understand and analyze data from\u00a0 (slightly to very) different perspectives. Remember the tool you design will need to accommodate these users and their analytical needs. You will create a user scenario for each identified user (<span style=\"color: #00ccff\"><a style=\"color: #00ccff\" href=\"https:\/\/www.interaction-design.org\/literature\/topics\/user-scenarios#:~:text=User%20scenarios%20are%20stories%20which,and%20usability%2Dtest%20optimal%20solutions.\">what is a user scenario?<\/a><\/span>). Each scenario includes the following:<\/p><ul><li>Background\u00a0\u2013\u00a0who\u00a0are your users (including their knowledge base and skillset\/s)?<\/li><li>Motivations\u00a0\u2013\u00a0what\u00a0goals do they want to achieve?<\/li><li>Tasks\u00a0\u2013\u00a0what\u00a0must they do to reach those goals?<\/li><li>Context of use\u00a0\u2013\u00a0how\u00a0will they encounter your design?<ul><li>Challenges\u00a0\u2013\u00a0when\u00a0they try to use it,\u00a0what\u00a0can get in their way (e.g., signal loss)?<\/li><\/ul><\/li><\/ul><p><em>The deliverable in this part is user scenarios. For each identified user, you will write a one-paragraph user scenario.<\/em><\/p><p><strong>3 &#8211; Data and task abstraction (10%). <span style=\"color: #ff6600\">Due on: 3\/9<\/span><\/strong><\/p><p>In this part of the proposal, you will apply data and task abstraction techniques that will be covered in lectures to describe and transform the data and user tasks from user space to visualization design space.<\/p><p><em>The deliverables of this part are data and task abstractions\u00a0 (1-3 pages each)<\/em><\/p><p><strong>4- Design (15%). <span style=\"color: #ff6600\">Due on: 3\/25<\/span><\/strong><\/p><p>In this part, you will propose the design of the visualization tool.\u00a0<\/p><p><em>The deliverable is a 3-5 pages document, explaining why and how your proposed design will help the (previously identified) users to achieve their data analysis goals. This document should include medium or high fidelity prototypes of your solution (<span style=\"color: #00ccff\"><a style=\"color: #00ccff\" href=\"https:\/\/www.interaction-design.org\/literature\/topics\/prototyping#:~:text=Prototyping%20is%20an%20experimental%20process,can%20release%20the%20right%20products.\">what is prototyping?<\/a><\/span>).<\/em><\/p><hr \/><h4>User Evaluation<\/h4><p>Due to the current pandemic and difficulty of performing user studies, user evaluation is optional. Performing a user evaluation, however, carries a 5% bonus mark towards the overall project assessment. We will cover common methods of visualization evaluation in lectures. The evaluation must be completed before the final project demo and reported in the final report.<\/p><hr \/><h4>Final Demo. <span style=\"color: #ff6600\"><strong>Due on: 4\/29<\/strong><\/span><\/h4><p>Final project demos will be held online during the last two or three classes (depending on the number of teams). Each group will be given 12 minutes to present their work. The 12 minutes should be roughly broken down as follows:<\/p><ul><li>a short slideshow, presenting data, user, and tasks (~5 mins)<\/li><li>live demo of the tool (~5 mins)<\/li><li>question and answer (~2 mins)<\/li><\/ul><p>The presentation date and order will be assigned randomly. Therefore, you need to make sure that your tool is ready before the first date when presentations start.<\/p><p>Demos will be evaluated according to these high-level criteria:<\/p><ol><li>The match between the defined user tasks and the tool&#8217;s functionalities<\/li><li>Design of effective and efficient visualizations that match data type and support user tasks<\/li><li>Supporting interactivity<\/li><li>Supporting data manipulation and transformation<\/li><li>Supporting exploration<\/li><\/ol><hr \/><h4>Final Report. <span style=\"color: #ff6600\">Due date: 5\/14<\/span><\/h4><p>The final report will provide implementation details of the tool such as architecture and technologies used. This will be a 1-2 page document. In the case of any user evaluations, you should add 1-2 pages to the final report and describe the methodology used, participants, description of collected data, and your high-level findings.<\/p><hr \/><h4>Late and missing submission policy<\/h4><p>Late submissions are allowed for the project deliverables, however, you will lose 50% of the mark allocated to the specific deliverable. Missing submission results in the total loss of the deliverable&#8217;s mark.<\/p><p>If your late or missing submission is due to a legitimate reason such as illness or an emergency, contact the TA or the course instructor as soon as possible to consider and assess your case.\u00a0<\/p><hr \/><h2><strong>Tips for a Successful Project<\/strong><\/h2><p>It is extremely important to select an interesting problem with data that some group of people will care deeply about. I cannot stress enough how vital it is to start with interesting data. Find some topic that almost everyone cares about or that some subset of people really cares about. <span style=\"text-decoration: underline\">Consider combining different data sets to produce a new composite data set of special interest.<\/span> Such a fusion of data often creates a dataset that people want to learn about. Remember that this often takes time and effort to \u201cfuse\u201d multiple data types, so you want to make sure you pick them wisely (i.e., they should be in support of the questions that you want people to be able to answer using your tool).<\/p><p>Two possible styles of successful visualization projects (definitely space is not limited to these two):<\/p><p>In the first style, the group created a visualization system that has only one view\/representation but this representation is new and creative. Here, you should focus on designing an innovative new visual representation. The actual user interface may have different components or pieces, but it should be tightly integrated. The real focus here is on creativity and innovation, and the novel representation of the information. These projects emphasize the mappings between the data (and characteristics\/variables of the data) to visual encodings, glyphs, and metaphors.<\/p><p>The second type of successful project employs multiple coordinated views where each view may use some well-known visualization techniques, perhaps customized a little for this problem. The emphasis in this type of project is to create a sound, functional system implementation that clearly can be of help for data analysis and understanding. It is important in this type of project to have coordinated views that work well together and provide different perspectives on the data. This type of project does not have the same level of visualization innovation as the first, but it comes together in strong system implementation, including well-designed user interactions that allow users to explore the data and progress through their task to answer the questions they may have of the data.<\/p><hr \/><h2><strong>Example projects<\/strong><\/h2><p><a href=\"https:\/\/joshualevine.github.io\/COMPSCI-590V-Final-Project\/\">Project on the Food Environment Atlas<\/a><\/p><p><a href=\"https:\/\/shezanmirzan.github.io\/DataVis-Mental-Health\/\">Project on the OSMI Mental Health Data<\/a><\/p><\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-tab-title elementor-tab-mobile-title\" aria-selected=\"false\" data-tab=\"4\" role=\"tab\" tabindex=\"-1\" aria-controls=\"elementor-tab-content-1734\" aria-expanded=\"false\">Readings &amp; Discussions<\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-1734\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"4\" role=\"tabpanel\" aria-labelledby=\"elementor-tab-title-1734\" tabindex=\"0\" hidden=\"hidden\"><h3>Required Reading (10%)<\/h3><p>Regularly during the term, you will be assigned research papers related to the topics that have been covered in the class to read. The papers will be posted on Moodle.\u00a0 All the students <span style=\"text-decoration: underline\">MUST<\/span> read the paper(s) and provide a summary(s) of the research on the associated Moodle forum. In addition to the summary, graduate students <span style=\"text-decoration: underline\">MUST<\/span> post at least one question\/critique about the paper and answer others&#8217; questions\/critiques. This is optional for undergrads though we encourage them to participate in discussions around the papers. Summary(s) are due one week after the date on which the paper is posted.<\/p><h4>Your summary <span style=\"text-decoration: underline\">MUS<\/span>T include the following:<\/h4><ul><li>Explain the problem that the paper investigates. Why is it important? Whom does it affect?<\/li><li>How the authors propose to investigate\/solve this problem?<\/li><li>Why &amp; how the proposed solution can address the problem?<\/li><li>How do they evaluate their solution? What methodology do they use in their evaluation?<\/li><li>What are the most important findings of their evaluation?<\/li><\/ul><p>We will read all of your summaries and questions\/critiques. However, we will <span style=\"text-decoration: underline\">NOT<\/span> provide you with feedback unless your work is below the bar or is missing.<\/p><p>You can find many guidelines online that describe how to read and summarize a research paper. <span style=\"color: #00ccff\"><a style=\"color: #00ccff\" href=\"https:\/\/www.eecs.harvard.edu\/~michaelm\/postscripts\/ReadPaper.pdf\">Here<\/a><\/span> is an example from Harvard. You can also talk to me or the TA if you have any questions about reading and summarizing research papers.<\/p><h4>Late and missing submission policy<\/h4><p>Late submission is allowed for reading, however, you will lose 50% of the mark allocated to the reading. Missing submission results in the total loss of the reading&#8217;s mark.<\/p><p>If your late or missing submission is due to a legitimate reason such as illness or an emergency, contact the TA or the course instructor as soon as possible to consider and assess your case.\u00a0<\/p><h4>Reading links<\/h4><p>Reading 1: <a href=\"https:\/\/drive.google.com\/file\/d\/1I6sZ7UvcGJnTKs9YAUNzvxLZOrMbXUfk\/view?usp=sharing\">Bridging From Goals to Tasks with Design Study Analysis Reports<\/a><\/p><p>Reading 2: <a href=\"https:\/\/drive.google.com\/file\/d\/1RQOhTQOwiMMzLjJsbF5jBBVM8bW0HoV7\/view?usp=sharing\">Crowdsourcing graphical perception<\/a><\/p><p>Reading 3: <a href=\"https:\/\/drive.google.com\/file\/d\/1VFntQVdHCe77VDaKYO2Xbo1GXZEk_7yO\/view?usp=sharing\">Task-Based Effectiveness of Basic Visualizations<\/a><\/p><p>Reading 4: <a href=\"https:\/\/drive.google.com\/file\/d\/1NkiaLNhBdegGbZGoaR1qmzzOKb5PnK7-\/view?usp=sharing\">NodeTrix: A Hybrid Visualization of Social Networks<\/a><\/p><p>Reading 5: <a href=\"https:\/\/drive.google.com\/file\/d\/1F6bjFYhD3syRIGIvNYQ0XaYhj5DOkxu-\/view?usp=sharing\">Graph-Theoretic Scagnostics<\/a><\/p><p>Reading 6: <a href=\"https:\/\/drive.google.com\/file\/d\/1lLy73NVYwOcst8MBUtmT5mrqz_nreOyK\/view?usp=sharing\">Hypothetical Outcome Plots Help Untrained Observers Judge Trends in Ambiguous Data<\/a><\/p><p>Reading 7: <a href=\"https:\/\/drive.google.com\/file\/d\/1pfKkalmVAPIcQ1KUqoh7Qsu6G3jmj4GK\/view?usp=sharing\">A Systematic Review on the Practice of Evaluating Visualization<\/a><\/p><\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-tab-title elementor-tab-mobile-title\" aria-selected=\"false\" data-tab=\"5\" role=\"tab\" tabindex=\"-1\" aria-controls=\"elementor-tab-content-1735\" aria-expanded=\"false\">Homework <\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-1735\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"5\" role=\"tabpanel\" aria-labelledby=\"elementor-tab-title-1735\" tabindex=\"0\" hidden=\"hidden\"><h4>Homework<\/h4><p>Throughout the course, you will be given 6 homework that you will work on individually and submit your work on Moodle. Homeworks cover topics covered in visualization and D3 lectures. We will discuss answers to the homework in the discussion sessions.<span style=\"text-decoration: underline\"> Each homework is due before its discussion session.<\/span> See class schedule for details. We will mark and return your homework to you after the discussion session.<\/p><h4>Late and missing submission policy<\/h4><p>Late submission is allowed for homework, however, you will lose 50% of the mark allocated to the homework. Missing submission results in the total loss of the homework&#8217;s mark.<\/p><p>If your late or missing submission is due to a legitimate reason such as illness or an emergency, contact the TA or the course instructor as soon as possible to consider and assess your case.\u00a0<\/p><\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-tab-title elementor-tab-mobile-title\" aria-selected=\"false\" data-tab=\"6\" role=\"tab\" tabindex=\"-1\" aria-controls=\"elementor-tab-content-1736\" aria-expanded=\"false\">Midterm Exam<\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-1736\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"6\" role=\"tabpanel\" aria-labelledby=\"elementor-tab-title-1736\" tabindex=\"0\" hidden=\"hidden\"><h4>Midterm<\/h4><p>The midterm will be on March 16th. It will be a take-home exam with a 24 hour return time. Questions will be open-ended, requiring you to draw on the knowledge you have gained so far in the course to answer.<\/p><p>\u00a0<\/p><h4>Late and missing submission policy<\/h4><p>Late submission is <span style=\"text-decoration: underline\">NOT<\/span> allowed for the midterm exam.\u00a0<\/p><p>If you miss the midterm due to a legitimate reason such as illness or an emergency, contact the TA or the course instructor as soon as possible to consider and assess your case.\u00a0<\/p><\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-tab-title elementor-tab-mobile-title\" aria-selected=\"false\" data-tab=\"7\" role=\"tab\" tabindex=\"-1\" aria-controls=\"elementor-tab-content-1737\" aria-expanded=\"false\">Resources<\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-1737\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"7\" role=\"tabpanel\" aria-labelledby=\"elementor-tab-title-1737\" tabindex=\"0\" hidden=\"hidden\"><p><strong>D3 Resources<\/strong><\/p><p><a href=\"http:\/\/www.youtube.com\/watch?v=8jvoTV54nXw\"><span style=\"color: #3366ff\">http:\/\/www.youtube.com\/watch?v=8jvoTV54nXw<\/span><\/a>\u00a0\u2013 nice overview and run-through video\/talk<br \/><span style=\"color: #3366ff\"><a style=\"color: #3366ff\" href=\"http:\/\/alignedleft.com\/tutorials\/d3\/\">http:\/\/alignedleft.com\/tutorials\/d3\/<\/a><\/span>\u00a0\u2013 thorough d3 tutorials from an academic instructor and the author of the open OReilly book, \u201cInteractive Data Visualization for the Web\u201d (look for free preview link for the actual book draft<br \/><span style=\"color: #3366ff\"><a style=\"color: #3366ff\" href=\"https:\/\/www.youtube.com\/user\/d3Vienno\/videos?view=0&amp;flow=grid\">https:\/\/www.youtube.com\/user\/d3Vienno\/videos?view=0&amp;flow=grid<\/a>\u00a0<\/span>\u2013 many tutorial videos by d3Vienno<br \/><span style=\"color: #3366ff\"><a style=\"color: #3366ff\" href=\"http:\/\/www.cs171.org\/2015\/resources\/\">http:\/\/www.cs171.org\/2015\/resources\/<\/a>\u00a0<\/span>\u2013 list of d3 resources from Harvard CS 171 class<br \/><span style=\"color: #3366ff\"><a style=\"color: #3366ff\" href=\"https:\/\/github.com\/mbostock\/d3\/wiki\/Tutorials\">https:\/\/github.com\/mbostock\/d3\/wiki\/Tutorials<\/a>\u00a0<\/span>\u2013 big list of resources from the author of D3<br \/><span style=\"color: #3366ff\"><a style=\"color: #3366ff\" href=\"https:\/\/github.com\/mbostock\/d3\/wiki\/API-Reference\">https:\/\/github.com\/mbostock\/d3\/wiki\/API-Reference<\/a>\u00a0<\/span>\u2013 well-done D3 documentation<br \/><span style=\"color: #3366ff\"><a style=\"color: #3366ff\" href=\"http:\/\/www.d3noob.org\/\">http:\/\/www.d3noob.org<\/a><\/span>\u00a0\u2013 free ebook with lots of tips and tricks, actively updated<br \/><span style=\"color: #3366ff\"><a style=\"color: #3366ff\" href=\"https:\/\/groups.google.com\/forum\/?fromgroups=#!forum\/d3-js\">https:\/\/groups.google.com\/forum\/?fromgroups=#!forum\/d3-js<\/a>\u00a0<\/span>\u2013 D3 Google group<br \/><span style=\"color: #3366ff\"><a style=\"color: #3366ff\" href=\"http:\/\/bost.ocks.org\/mike\/selection\/\">http:\/\/bost.ocks.org\/mike\/selection\/<\/a>\u00a0<\/span>\u2013 Guide to understanding selections, key part of D3.<br \/><a href=\"http:\/\/bcc-talks.surge.sh\/2012\/NCDevCon\/#\/\"><span style=\"color: #3366ff\">http:\/\/bcc-talks.surge.sh\/2012\/NCDevCon\/#\/<\/span><\/a> \u2013 A talk, with interactive examples and code snippets, explaining d3<br \/><span style=\"color: #3366ff\"><a style=\"color: #3366ff\" href=\"http:\/\/www.udacity.com\/course\/data-visualization-and-d3js--ud507\">http:\/\/www.udacity.com\/course\/data-visualization-and-d3js\u2013ud507<\/a>\u00a0<\/span>\u2013 d3.js Udacity Course<br \/><a href=\"http:\/\/bl.ocks.org\/curran\/3a68b0c81991e2e94b19\"><span style=\"color: #3366ff\">http:\/\/bl.ocks.org\/curran\/3a68b0c81991e2e94b19<\/span><\/a>\u00a0\u2013 Responsive Visualizations (Resizing)<br \/><span style=\"color: #3366ff\"><a style=\"color: #3366ff\" href=\"http:\/\/bl.ocks.org\/hubgit\/raw\/9133448\/\">http:\/\/bl.ocks.org\/hubgit\/raw\/9133448\/<\/a>\u00a0<\/span>\u2013 Nesting CSV Data<br \/><span style=\"color: #3366ff\"><a style=\"color: #3366ff\" href=\"https:\/\/bost.ocks.org\/mike\/nest\/\">http:\/\/bost.ocks.org\/mike\/nest\/<\/a>\u00a0<\/span>\u2013 Nesting Visualization Elements<br \/><span style=\"color: #3366ff\"><a style=\"color: #3366ff\" href=\"http:\/\/www.visualcinnamon.com\/blog\">http:\/\/www.visualcinnamon.com\/blog<\/a>\u00a0<\/span>\u2013 Creative Tutorials from Nadieh Bremer<\/p><\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Overview Class Schedule Project Readings &amp; Discussions Homework Midterm Exam Resources Overview Data Visualization and Analysis Spring 2021 Tuesday, Thursday, 8:30-9:45 AM Instructor: Dr. Ali Sarvghad asarv@cs.umass.edu,\u00a0 CICS 344 Virtual office hours: Monday 2:30 &#8211; 3:30 pm. Zoom link Teaching Assistant:\u00a0Joshua Levine joshualevine@umass.edu Virtual office hours: Friday 1:30-3 pm. Zoom link Course delivery policy for &hellip; <a href=\"https:\/\/groups.cs.umass.edu\/asarv\/data-visualization-and-exploration-spring-2021\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Data Visualization and Exploration &#8211; Spring 2021&#8221;<\/span><\/a><\/p>\n","protected":false},"author":10,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":""},"class_list":["post-301","page","type-page","status-publish","hentry","group-blog","hfeed"],"_links":{"self":[{"href":"https:\/\/groups.cs.umass.edu\/asarv\/wp-json\/wp\/v2\/pages\/301","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/groups.cs.umass.edu\/asarv\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/groups.cs.umass.edu\/asarv\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/groups.cs.umass.edu\/asarv\/wp-json\/wp\/v2\/users\/10"}],"replies":[{"embeddable":true,"href":"https:\/\/groups.cs.umass.edu\/asarv\/wp-json\/wp\/v2\/comments?post=301"}],"version-history":[{"count":130,"href":"https:\/\/groups.cs.umass.edu\/asarv\/wp-json\/wp\/v2\/pages\/301\/revisions"}],"predecessor-version":[{"id":462,"href":"https:\/\/groups.cs.umass.edu\/asarv\/wp-json\/wp\/v2\/pages\/301\/revisions\/462"}],"wp:attachment":[{"href":"https:\/\/groups.cs.umass.edu\/asarv\/wp-json\/wp\/v2\/media?parent=301"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}