Real-Time Luke Christison luke.christison@plymouth.ac.uk Immersive - - PowerPoint PPT Presentation

DAT 601

Real-Time

Luke Christison luke.christison@plymouth.ac.uk Immersive Vision Theatre Office hours available via email appointment

WHAT IS DATA?

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.

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 Rat’s Neuronal Network Paul De Konick, Laval University UNIVERSE Millennium Simulation 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

• f 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

• Sensor device
• Mobile phone
• Online / Network
• Imaginary
• Quantitative/ Qualitative

Gathering Hardware

• Raspberry Pi
• Electric imp
• Ardunio
• Mobile phones
• Networked systems
• Analog devices
• Video cameras
• Xbee
• Web technologies
• Projectors
• Kinect/ Myo/ Leap
• MindWave
• Oculus/ GearVR/ Vive
• Fulldome

Software

• Unity
• Processing
• Blender
• Max/Msp/Jitter
• VVVV / PD
• Resolume
• Eclipse
• Mqtt/ osc
• Touch Designer
• PHP, Node.Js, Python
• Node-Red
• Processing
• OpenFrameworks
• Ableton

Outcomes

• Installations
• Dome show
• Learning Application
• Game/ simulation
• Generative Art
• Interactive visualisation
• Acoustic representation
• 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

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,

• r 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?

Relationships and connections

• Exceptions: Can we identify any significant values that sit outside of the

norm, such as outliers that change the dynamics of a given variable's range?

• Correlations: Is there evidence of strong or weak correlations between

variable combinations?

• Associations: Can we identify any important connections between different

combinations of variables or values?

• Clusters and gaps: Where is there evidence of data being "bunched"?

Where are there gaps in values and data points?

• Hierarchical relationships: Determining the composition, distribution,

and relevance of the data's categories and subcategories.

Data Activity 1: Remix

The goal of this activity is to practice the various techniques for presenting data. This gives participants a “toolbelt” of techniques they can use to tell a data story, helping them feel more confident that they can present data creatively. 10 minute brainstorm 5 minute sketch Share idea Gapminder.com

Data Activity 2: Word Web

Abstract ideas are hard to picture, and even harder to draw. A word web is a tool for exploring abstract ideas. This activity gives participants a way to turn abstract ideas into concrete images, allowing them to move from numbers to pictures to engage new audiences. 10 minutes silent brainstorming 5 minutes swap & discuss Share findings

Data Activity 3: Storybook

Storytelling is an art form, and we don’t get to practice it very

• much. This activity lets participants practice putting a data story

together into a narrative, like a storyteller would. It lets people sketch their story and play with different ways to tell it in a fun storybook form, creating a narrative that can tell their stories in a convincing way. 15 minutes to sketch narrative Share your story

Unity Workshop

Tomorrow

• Unity for Data Visualisation

Next week

• Unity for Immersive environments
• Project Guidance & Supervision

dward R. Tufte, (2001). The Visual Display of Quantitative Information 2nd ed., Cheshire, Conn: Graphics Press. Baudrillard, J. (1988) Simulacra and Simulation, Stanford: Stanford University Press. Paul, C. (2003) Digital Art, London: Thames & Hudson Ltd. Zics, B. (2008) Transparency, Cognition and Interactivity: Toward a New Aesthetic for Media Art. PhD Thesis. Newport, Wales: University of Wales. Wilson, S. (2002) Information Arts: Intersections of Art, Science and Technology, Cambridge, Mass; London: MIT Press. Drayson, H. (2009) 'Constructed Bodies; Can Biomedical Instruments Become Tools of Self-perception?' In New Realities, Being Syncretic, Ascott et al. (eds), Wein and New York: Springer. Krueger, M. (1977) 'Responsive Environments' in Packer, R. and Jordan, K. (eds.) (2001) Multimedia: From Wagner to Virtual Reality, New York: W.W. Norton & Company, Inc. Gibson, J. (1979). The Ecological Approach to Visual Perception, Boston: Houghton Mifflin. Kellmereir, D. Obodovski, D. (2013) The Silent Intelligence: The Internet of Things, New York: DND Ventures, LLC. Halperm, O. (2015) Beautiful Data: A History of Vision and Reason Since 1945 (Experimental Futures), England ,Durham: Duke University Press. Lima, M. (2011) Visual Complexity, Mapping Patterns of Information, New York City: Princeton Architectural Press. Mau, B. (2004) Massive Change, London : Phaidon Press. Khut, G. (2006) Development and Evaluation of Participant-Centred Biofeedback Artworks [online] Available: http://researchdirect.uws.edu.au/islandora/object/uws%3A2425/datastream/PDF/view Raja, D. et al. (2004) Exploring the Benefits of Immersion in Abstract Information Visualization [online] Available: http://people.cs.vt.edu/~bowman/papers/ipt_dheva.pdf Schroth, O. et al. (2010) From Information to Participation – Applying Interactive Features in Landscape Visualizations [online] Available: http://www.kolleg.loel.hs- anhalt.de/studiengaenge/mla/mla_fl/conf/pdf/conf2005/42schroth_c.pdf Sheppard, S.R.J. et al. (2008) Can Visualisation Save the World? - Lessons for Landscape Architects from Visualizing Local Climate Change[online] Available: http://www.kolleg.loel.hs-anhalt.de/landschaftsinformatik/fileadmin/user_upload/_temp_/2008/2008_Beitraege/001/Buh_2-21.pdf http://www.wired.com/2014/11/rise-of-data-artists/

Title image

• Title image
• From Invisible Journeys
• Oli Laurelle (2008)
• http://www.visualcomplexity.com/vc/project_details.cfm?id=5

57&index=557&domain=