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Data Visualization Workshop @ CADA, Lisboa

Data visualization has been a longterm interest of mine and I'm extremely pleased about the opportunity to run a workshop about the topic at CADA in Lisbon (super thanks to Tom Carden for making contact! ;). From April 20-22, we will have three intense days of experimentation and team work exploring the field in a hands-on manner using Processing as well as other open source tools. If you want to take part, head over to the CADA website and sign up. A brief abstract & outline of what we've planned is below:

Data visualization workshop poster

About

Data is everywhere around us. Through the ongoing technological developments and digitalization, ever more aspects of our lives become subject to scrutinizing and so become measurable. The rapidly increasing amount of data being published online constitutes great political, cultural, artistic and design challenges to society and individuals alike. This trend is accelerated by the increased introduction of ubiquitous computing systems into various aspects of our everyday. Persuasive and locative technologies in particular have an yet to be fully understood effect (as well as side effects) on our behaviours & the way we live our lives, now supplemented with these new means. Tracking technologies like GPS are integrated into existing products like mobile phones, cameras, cars. In a similar vain, but on a more local scale, RFID is increasingly being used to enable reliable, passive long range identification of objects and persons. However, each of these technologies creates an opportunity for monitoring and so ever more data trails, which are being silently aggregated by corporations & governments worldwide. In addition social media is on a constant rise in popularity. Here too, the technology and algorithms behind the various social networks are entirely based on our willingness to share more and more previously private data with 3rd parties.In that light, data almost could be considered a meta-medium too, since it creates spaces around any other medium. Furthermore these different data spaces can be combined and by doing this we can extract and transform data into new information and gain an exponentially larger amount of insights. So when we talk about data visualization, we are actually referring not just to the presentation of the available data, but even more so to the guided act of visualizing the various relationships between those data.

It should be in our personal interests to obtain a greater literacy of the nature of data and data processing technologies. Much of the available data would not only enable new insights for ourselves, but too actually allow wider parts of the population to play a more active part in the discourse around related topics, incl. privacy & data protection.

Data visualization of large datasets still is a relative young field of design, but it also is a very necessary one. In this world of absolute data abundance we need new means to manage, combine, analyse & view these. We need to explore new visual languages and other forms of expression to help us cope, find patterns and gain new insights or even just retain an overview of various topics.

Scope

Over the three days of this workshop we will explore the nature of data as much as various techniques to visualize it. We will focus on working with Processing, but also make use of other opensource tools & languages, better suited for other parts of the visualization creation process. Since the workshop only lasts for 3 days, you're expected to have a good understanding of basic Processing concepts & programming constructs. That way we can focus better on the actual topic at hand.In order to give you a thorough understanding of the whole field, we will also cover a large amount of related theory, both technical & design. All topics will be supported by examples and exercises, building on each other iteratively.

The last day of the workshop will be largely reserved for 1:1 teaching & the creation of a small project utilizing your skills just learned. You can either work as team or individually.

Topics covered

(not exhaustive & in no particular order)

  • Discussion of various examples & popular methods, techniques, practitioners
  • Linked data, graph theory, data relationships, database basics
  • Creating & transforming structured data to allow different points of view
  • Overview of popular data formats and how to choose
  • Metaphor and conceptual representation & framing, qualitative vs. quantitative
  • Data space vs. presentation space
  • Multi-dimensionality & mapping inputs to outputs: from 1D, 2D, 3D, 4D… nD
  • Many-to-many mappings: Coordinate systems, space, topology, time, colour, size, shapes
  • Dynamic layout algorithms
  • Information theory: Inputs, Process, Output
  • System architecture: Model-View-Controller
  • Signal-to-noise ratio, filtering, pre-analysis
  • Aggregating data from multiple sources
  • Set theory operations, Venn diagrams, working with collections
  • Gestalt theory & Synaesthesia basics
  • Transposing data into other domains (e.g. sonification)
  • Managing level of detail
  • Literal presentation vs. artistic approach, using data as input for artworks
  • Re-coup of Processing basics & introduction to various libraries
  • Popular toolkits
  • Working with RSS/XML/JSON
  • Transforming data with XSLT
  • Regular Expressions
  • Working with webservices/APIs
  • Mapping geo data
  • Fluidity of data: streams vs. crystals (Realtime data vs. recorded data)
  • Data filtering (normalizing, scaling, projection, grouping, averaging etc.)
  • Recording data in a local database
  • Using Python/PHP/JavaScript as proxy to request & store data
  • Working with colour
  • Adding interactive controls
  • Exporting the visualization (PDF, 3D mesh, API, e.g Google charts)

For more information & registration please visit the CADA website.

Last modified: 2009/04/03 09:44