DAT 601 Real-Time
Luke Christison luke.christison@plymouth.ac.uk Immersive Vision Theatre Office hours available via email appointment
WHAT IS DATA?
Data visualisation not an abstract creative process, but rather is a linear process of decision making based on basic principles. 3 things should inform your design. 1: what you want to communicate. 2: the reader, they are not you they have their own context assumptions, and bias which needs to be accounted for. 3: The data itself, what that has to say, how it informs the truth. WHAT IS DATA?
Torsten Hägerstrand 1977
The Market
The Market
Networked Markets
Networked Markets
“ When everything is connected to everything else, for better or for worse everything is matters” Bruce Mau, Massive Change
Rhizome • Philosophical concept by Gillies Deleuze & Felix Guattari in Capitalism and Schizophrenia • The tree is dead, long live the network!
Rhizomatic structure Multiplicity Non Linearity Interconnectedness Interdependence Decentralization
BRAIN UNIVERSE Rat’s Neuronal Network Millennium Simulation Paul De Konick, Laval University Max Planck Society
Real-time? In every interactive system, there’s a feedback loop: you take action, the system responds, you see a response, or a notification of it, and you take another action. In some systems, the timing of that loop can be very loose. In other applications the timing must be tight.
Themes "Collecting the invisible” • Real-Time web • The Internet of Things • Virtual Worlds • Convergence • Data Visualization • Interactive technologies • Installation Art
Sources of data Softwar e Hardware Sensor device • Mobile phone • Unity • Raspberry Pi • Online / Network • Processing • Electric imp • Imaginary • Blender • Ardunio • Quantitative/ Qualitative • Max/Msp/Jitter • Gathering Mobile phones • VVVV / PD • Networked systems • Resolume • Analog devices • Eclipse • Outcomes Video cameras • Mqtt/ osc • Xbee • Touch Designer • Installations • Web technologies PHP, Node.Js, Python • • Dome show • Node-Red Projectors • • Learning Application • Processing • Kinect/ Myo/ Leap • Game/ simulation • OpenFrameworks • MindWave • Generative Art • Ableton • Oculus/ GearVR/ Vive Interactive visualisation • • Acoustic representation • Fulldome • Performance •
Invisible processes • Rhythmic • Biological • Emotional • Social / Behavioural • Energy • Electronic • Imaginary • Interplanetary / Interstellar • Micro / Macro • Material / immaterial
"Collecting the invisible" • Module will consist of short workshops, small group tutorials and self study sessions during which you will develop your final project for the final assessment. • This module offers students a range of experimental approaches to the production of the visual and sonic media.
Staff • Luke - Unity Data Visualisation Workshop • John – Sonifications • Simon – Networked Electronics • Lee – Wearable intelligence
TBC Guy Garrett of Achieve Intelligence Ltd. Methods of data Visualisation for Business Evening Lecture Absolute Data Science - A Datapreneurial view of BigData Solutions.
Schedule Luke Christison: 28th September. RLB208, 11:00 - 13:00, Intro, teams and research 29th September. RLB208, 13:00 -15:00, Unity3D Data Workshop Part1 5th October. RLB208, 11:00 - 13:00, Unity3D Data Workshop Part2 6th October. RLB208, 13:00 -15:00, Project Supervision Lee Nutbean 12th October. RLB208, 11:00 - 13:00, Conceptualization Workshop 13th October. RLB208, 13:00 -15:00, Project Supervision John Matthias: 19th October. RLB208, 10:00 - 12:00, Sonification Workshop Part1 20th October. RLB208, 13:00 -15:00, Project Supervision 26th October. RLB208, 11:00 - 13:00, Sonification Workshop Part2 27th October. RLB208, 13:00 -15:00, Project Supervision Simon Lock: 2nd November. RLB208, 11:00 -13:00, Networked Electronics Workshop Part1 3rd November. RLB208, 13:00 -15:00, Project Supervision 9th November. RLB208, 11:00 -13:00, Networked Electronics Workshop Part2 10th November. RLB208, 13:00 -15:00, Project Supervision Lee Nutbean: 16th November. RLB208, 11:00 -13:00, Wearable Intelligence Workshop Part1 17th November. RLB208, 13:00 -15:00, Project Supervision 23rd November. RLB208, 11:00 - 13:00, Wearable Intelligence Workshop Part2 24th November. RLB208, 13:00 -15:00, Project Supervision Luke: 30th November. RLB208, 11:00 - 13:00, Project Supervision 1st December. RLB208, 13:00 -15:00, Project Supervision Lee: 7th December. RLB208, 11:00 - 13:00, Project Supervision. 8th December. RLB208, 13:00 -15:00, Project Supervision. Luke & Lee: 14th December. RLB210, 10:00 - 13:00, Assessment. Gut Garrett?
Learning outcomes 1. Produce sophisticated visualisations, sonifications, animations and simulations within the context of a self initiated brief. 2. Demonstrate technical, practical and conceptual skills in the use of hardware, software and networked systems. 3. Demonstrate individual critical exploration of digital media.
Marking A group mark for the project as a whole assessed by 20 minute presentation. This should refer to both theoretical and practical aspects of your production and highlight the contributions of various group members. Assessment criteria used will be consistent with that used in the first term. This presentation is worth 50% of the module assessment - all group members share this mark. • A group mark for a short documentary video detailing the evolution of the project. This video is worth 20% of the module assessment - all group members share this mark. • An individual mark for your own reflective report and blog documentation on the group project. Detailed description of the content of the report will be provided in the tutorials. The report is worth 30% of the module assessment - each group member will have their own mark.
Marking • Project & Presentation 50% • Video 30% • Report & Blog 20% • Presentation Date: 14/12/16 • Marked by Luke, Lee
Methods of visualisation:
http://www.visualcomplexity.com/
http://www.visualcomplexity.com/
“The power of databases consists in their relational potential, the possibility of establishing multiple connections between different sets of data and constructing narratives about cultures” Christiane Paul, Digital Art, p178
Action-Centred Leadership • Group building • Think about your own skill sets • Balanced teams • Division of labor • Task Focus • Relationship Focus
Gapminder Trendalyzer is an information visualization software for • animation of statistics that was initially developed by Hans Rosling's Gapminder Foundation in Sweden. In March 2007 it was acquired by Google Inc..[1] The current[when?] beta version is a Flash application that is preloaded with statistical and historical data about the development of the countries of the world. The information visualization technique used by • Trendalyzer is an interactive bubble chart. By default it shows five variables: Two numeric variables on the X and Y axes, bubble size and colour, and a time variable that may be manipulated with a slider. The software uses brushing and linking techniques for displaying the numeric value of a highlighted country. Components of the Trendalyzer software, particularly the • Flash-based Motion Chart gadget, have become available for public use as part of the Google Visualizations API
Comparisons and proportions • Range and distribution: Discovering the range of values and the shape of their distribution within each variable and across combinations of variables • Ranking: Learning about the order of data in terms of general magnitude, identifying the big, medium, and small values. • Measurements: Looking beyond just the order of magnitude to learn about the significance of absolute values • Context: Judging values against the context of averages, standard deviations, targets, and forecasts.
Trends and patterns • Direction: Are values changing in an upward, downward, or flat motion? • Rate of change: How steep or flat do pattern changes occur? Do we see a consistent, linear pattern, or is it much more exponential in shape? • Fluctuation: Do we see evidence of consistent patterns or is there significant fluctuation? Maybe there is a certain rhythm, such as seasonality, or perhaps patterns are more random • Significance: Can we determine if the patterns we see are meaningful signals or simply represent the noise within the data? • Intersections: Do we observe any important intersections or overlaps between variables, crossover points that indicate a significant change in relationship?
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