ENV 20069.1 Envisioning Information Lecture 9 – Time: Taxonomy & Techniques Ken Brodlie

Slides:



Advertisements
Similar presentations
TWO STEP EQUATIONS 1. SOLVE FOR X 2. DO THE ADDITION STEP FIRST
Advertisements

You have been given a mission and a code. Use the code to complete the mission and you will save the world from obliteration…
Bellwork If you roll a die, what is the probability that you roll a 2 or an odd number? P(2 or odd) 2. Is this an example of mutually exclusive, overlapping,
Advanced Piloting Cruise Plot.
Kapitel 21 Astronomie Autor: Bennett et al. Galaxienentwicklung Kapitel 21 Galaxienentwicklung © Pearson Studium 2010 Folie: 1.
Chapter 1 The Study of Body Function Image PowerPoint
Copyright © 2011, Elsevier Inc. All rights reserved. Chapter 5 Author: Julia Richards and R. Scott Hawley.
1 Copyright © 2010, Elsevier Inc. All rights Reserved Fig 2.1 Chapter 2.
By D. Fisher Geometric Transformations. Reflection, Rotation, or Translation 1.
7.5 Glide Reflections and Compositions
Business Transaction Management Software for Application Coordination 1 Business Processes and Coordination.
Jeopardy Q 1 Q 6 Q 11 Q 16 Q 21 Q 2 Q 7 Q 12 Q 17 Q 22 Q 3 Q 8 Q 13
Jeopardy Q 1 Q 6 Q 11 Q 16 Q 21 Q 2 Q 7 Q 12 Q 17 Q 22 Q 3 Q 8 Q 13
Title Subtitle.
The Ellipse 10.3 Chapter 10 Analytic Geometry 3.4.1
My Alphabet Book abcdefghijklm nopqrstuvwxyz.
Coordinate Plane Practice The following presentation provides practice in two skillsThe following presentation provides practice in two skills –Graphing.
0 - 0.
DIVIDING INTEGERS 1. IF THE SIGNS ARE THE SAME THE ANSWER IS POSITIVE 2. IF THE SIGNS ARE DIFFERENT THE ANSWER IS NEGATIVE.
SUBTRACTING INTEGERS 1. CHANGE THE SUBTRACTION SIGN TO ADDITION
MULT. INTEGERS 1. IF THE SIGNS ARE THE SAME THE ANSWER IS POSITIVE 2. IF THE SIGNS ARE DIFFERENT THE ANSWER IS NEGATIVE.
Addition Facts
1 SDMIV Data Visualization - A Very Rough Guide Ken Brodlie University of Leeds.
ENV Envisioning Information Lecture 2 Simple Graphs and Charts Ken Brodlie School of Computing University of Leeds.
13.1 Vis_2003 Data Visualization Lecture 13 Visualization of Very Large Datasets.
ENV Envisioning Information Lecture 12 – Scientific Visualization Scalar 2D Data Ken Brodlie
13.1 Vis_04 Data Visualization Lecture 13 Information Visualization Part 1.
Data Visualization Lecture 4 Two Dimensional Scalar Visualization
GR2 Advanced Computer Graphics AGR
ENV Envisioning Information Lecture 3 – Multivariate Data Exploration Scatter plots and parallel coordinates Ken Brodlie.
ENV Envisioning Information Lecture 10 – Cartograms: A different way of drawing maps Ken Brodlie
1.1 Si23_03 SI23 Introduction to Computer Graphics School of Computing Ken Brodlie Semester Lecture 1 - Introduction.
SI23 Introduction to Computer Graphics
ENV Envisioning Information Lecture 4 – Multivariate Data Exploration Glyphs and other methods Hierarchical approaches Ken Brodlie.
ENV Envisioning Information Lecture 6 – Document Visualization Ken Brodlie
ENV Envisioning Information Lecture 5 – Connections Ken Brodlie
ENV Envisioning Information Lecture 7 – Interaction Ken Brodlie
7.1 si31_2001 SI31 Advanced Computer Graphics AGR Lecture 7 Polygon Shading Techniques.
ZMQS ZMQS
BT Wholesale October Creating your own telephone network WHOLESALE CALLS LINE ASSOCIATED.
10.2 Variables and Expressions
LOGO Regression Analysis Lecturer: Dr. Bo Yuan
Randomized Algorithms Randomized Algorithms CS648 1.
ABC Technology Project
Unit 8: Presenting Data in Charts, Graphs and Tables
Reconstruction from Voxels (GATE-540)
CHAPTER 6 Introduction to Graphing and Statistics Slide 2Copyright 2012, 2008, 2004, 2000 Pearson Education, Inc. 6.1Tables and Pictographs 6.2Bar Graphs.
© Charles van Marrewijk, An Introduction to Geographical Economics Brakman, Garretsen, and Van Marrewijk.
© Charles van Marrewijk, An Introduction to Geographical Economics Brakman, Garretsen, and Van Marrewijk.
“Start-to-End” Simulations Imaging of Single Molecules at the European XFEL Igor Zagorodnov S2E Meeting DESY 10. February 2014.
Squares and Square Root WALK. Solve each problem REVIEW:
We are learning how to read the 24 hour clock
© 2012 National Heart Foundation of Australia. Slide 2.
The x- and y-Intercepts
Lets play bingo!!. Calculate: MEAN Calculate: MEDIAN
Chapter 5 Test Review Sections 5-1 through 5-4.
GG Consulting, LLC I-SUITE. Source: TEA SHARS Frequently asked questions 2.
Addition 1’s to 20.
25 seconds left…...
Copyright © Cengage Learning. All rights reserved.
Week 1.
We will resume in: 25 Minutes.
1 Unit 1 Kinematics Chapter 1 Day
PSSA Preparation.
IP, IST, José Bioucas, Probability The mathematical language to quantify uncertainty  Observation mechanism:  Priors:  Parameters Role in inverse.
TASK: Skill Development A proportional relationship is a set of equivalent ratios. Equivalent ratios have equal values using different numbers. Creating.
How Cells Obtain Energy from Food
Copyright © Cengage Learning. All rights reserved.
1 18 April 2007 vizNET-LEEDS-PRES A Rough Guide to Data Visualization – Part 2 VizNET 2007 Annual Event Ken Brodlie School of Computing University.
Presentation transcript:

ENV Envisioning Information Lecture 9 – Time: Taxonomy & Techniques Ken Brodlie

ENV Time Many applications involve visualization of data over a period of time… … including the first visualization … and one of the most famous

ENV Time We are familiar with time series in many walks of life… Todays lecture looks at visualization and time Seismogram

ENV Taxonomy (Frank/Mueller/Schumann) Data: D = {(t 1,d 1 ), (t 2,d 2 ),.. (t n,d n )} where d i = f(t i ) d can be multivariate Representations can be: –Static –Dynamic Types of time… Discrete or interval time –Sequence of snapshots; or measured over interval such as days Linear or cyclic time –Start to end; or repeating like the seasons Ordered or branching time –Data values in strict time sequence; or branches with parallel time tracks Visualization Methods for Time-dependent Data – An Overview : Mueller and Schumann See also:

ENV Discrete vs Interval Time DiscreteInterval

ENV Linear vs Cyclic Linear –Previous examples were linear Cyclic –Circle graphs (discrete) –Sector graphs (interval) discrete interval

ENV Ordered vs Branching Time Rather than a simple ordered sequence…. Scientists often experiment with simulations of processes Here a simulation is started and results obtained at a sequence of time steps… … but to investigate some feature in more detail, the scientist rolls back the simulation and restarts with a different parameter setting

ENV Visual Metaphors Often we can use existing visualization techniques… and consider time as just any other variable.. New visual metaphors have also been suggested however…

ENV Parallel Coordinates for Time Series Data! Map different time steps to different axes Garnett, 1903 Statistical atlas, 12 th census of US Axes are years (right to left) Position on axis Is ranking

ENV Visual Metaphors : Long time periods Special techniques have been proposed for visualization over very long time periods Themeriver technique has been used to depict evolutionary behaviour…..Bit like an interval time version of parallel coordinates?? Evolution of baby names.... Try it at: Laura and Martin Wattenberg

ENV Themeriver Themeriver for climate change… …

ENV River Metaphor Taglines –Visualizing tags attached to Flickr online image sharing –Evolution over time –Show tags that are specific to a time period Definition of interesting is the following calculation: –u = tag –t = specified time period –N(u,t) = no of occurrences of tag in period –N(u) = total no of occurences of tag –C = constant I(u,t) = N(u,t) / (C + N(u))

ENV Cluster and Calendar based Visualization of Time Series Data Jarke van Wijk has shown how visualization can be used in analysis of time series data Opposite is power demand within ECN (Netherlands Energy Research Centre)… … hard to pick out patterns of usage

ENV Cluster Approach Each day taken as an observation and cluster analysis performed Take two closest days and merge into an average day… … and keep repeating dendogram Full cluster tree for energy data

ENV Visualizing the Main Clusters Then we are able to visualize the key patterns of use… … but better still, in next slide we link to a calendar

ENV Calendar View of Power Demand

ENV Calendar View of Number of Employees at Work What can you observe? (NB Dec 5 th )

ENV Timestore Timestore is a nice idea for organising mailboxes… Yiu, Baecker, Silver, Long U Toronto

ENV Spiral Graphs Spiral graphs are a space- efficient way of visualizing long time series… From Alexa et al

ENV Time Wheel The Time Wheel allows several time series to be viewed simultaneously… … how successful is this? … rotation can help, why? … again cf parallel coordinates? Tominski, Abello, Schumann - Rostock

ENV MultiComb Here is another idea from Rostock group – MultiComb Two variations: Time axes as spokesTime axes as perimeter

ENV TimeWheel in 3D The 3D TimeWheel has time in central axis, variable axes on opposite end of slices… …wheel can open out

ENV MultiComb in 3D MultiComb in 3D.... here there are 7 time series plots with a common time axis

ENV Kiviat Tubes Kiviat charts were used in parallel program performance visualization… … but are essentially star glyphs Here is a Kiviat Tube –Star glyphs laid out along time axis and surface created