PPT-1 Visualization Process and Collaboration

Author : ThePerfectFit | Published Date : 2022-08-02

Tamara Munzner Department of Computer Science University of British Columbia httpwwwcsubccatmmtalkshtmldagstuhl09 Dagstuhl Scientific Visualization Workshop June

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1 Visualization Process and Collaboration: Transcript


Tamara Munzner Department of Computer Science University of British Columbia httpwwwcsubccatmmtalkshtmldagstuhl09 Dagstuhl Scientific Visualization Workshop June 2009 Techniquedriven work. B.Tech Major Project. Project Guide. Dr. . Naresh. . Nagwani. Project Team Members. Pawan Singh. Sumit. . Guha. What is Data Visualisation ?. Data Visualisation . is the graphical representation. of information. Bar charts, scatter graphs, and. Nicholas Del . Rio. University of Texas at El Paso Computer Science. Workshop Objectives. U. nderstand . notion . and purpose of visualization . queries. Understand why writing queries may be easier that writing visualization programs. Sureyya Tarkan, Kostas . Pantazos. , Catherine . Plaisant. , Ben . Shneiderman. UMD Dept of Computer Science & HCIL. sureyya@cs.umd.edu. http://www.cs.umd.edu/hcil/sharp/. A Story. 1. Missed Lab Results. Yingcai Xiao. Computation with and without Visual Assistance. 67 x 89 = ? . Visualized Data Analysis. 67. x 89. ---------. 603. + 536. ---------. 5963. . Week . 9 . NJ Kang. What is creative visualization?. 5. Create new and fresh/. From language to visualization. http://pageturneradventures.com/2011/09/imagination-workout-visualization/. From word to image. Creates interactive visualization . and dashboards . Fast and easy to use. Connect to any . data regardless . of its size and . complexity. To present . data from multiple sources. It gives . you . the ability . IDOC Community Corrections Division. Collaboration at its finest? You be the judge!. Essential Elements of Effective Collaboration. Common Vision. Purpose. Clarity of Roles & Responsibilities. Healthy Communication Pathways. Starting up the Program. 2. Creating a Data Visualization . Using Tableau Public. Try 1. Creating a Data Visualization . Using Tableau Public. 3. Open Data. Creating a Data Visualization . Using Tableau Public. David Granholm. , Senior Director PM . Matt Milella, VP Engineering. Oracle Analytics. October 4, 2017. 2. 3. Oracle Analytic Apps Portfolio. OTBI. DV. Content. Packs. Oracle Analytic Cloud (OAC). Next-Gen. iPhone. Capstone Team#5. Fall 2009. Table of Contents. Topic. Slide Number. Team information. ………………………………………………3. Instructor/Mentors Information. ………………………………………………4. ParaViewWeb. Web3D – . Paris 2011. Julien. . Jomier. , . Kitware. . julien.jomier@kitware.com. Motivation. Acquiring Data (2). Tissue rotates. Knife advances. This tissue ribbon is collected by a submerged conveyor belt. Michael Johnson. 1. , Thomas Villani. 1, . Nick Crider. 1. ,Colleen Wojenski. 2 . 1. Visikol Inc., North Brunswick, NJ, 08902, 2. Product Safety Labs, Dayton, NJ, 08810. Abstract. Developmental and reproductive toxicology (DART) studies are required for new chemical entities going to market to ensure that there are not adverse developmental consequences associated with the chemical. These studies involve dosing a pregnant female animal (e.g. mouse, rat, rabbit) with the compound and evaluating the effect of the chemical on the offspring. This evaluation involves the parallel processes of histopathology and gross morphological evaluation wherein the most time-consuming component of DART studies is the performance of gross skeletal evaluation. Since the introduction of Thalidomide into the marketplace, close attention has been paid to the impact of chemicals on skeletal development and DART studies require the visualization of gross skeletal morphology for abnormalities. The current methodology for conducting skeletal evaluation involves digesting soft tissue using a strong base (potassium hydroxide) and staining the bone with alizarin and cartilage in some cases with . Chong Ho (Alex) Yu. Agenda. What is data visualization?. What isn’t data visualization?. What is the difference between dynamic, semi-dynamic, and non-dynamic (static) visualization systems?. Why do we need data visualization?. Cherdyntsev E.S.. We have now covered the start and the end of the visualization . pipeline, . namely getting data into the computer, and, on the . human side. , how perception and cognition help us interpret images. .

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