Ash at CIID

Ashwin Rajan's blog while at the Copenhagen Institute of Interaction Design.

Posts Tagged ‘map

Designing from the frontlines

leave a comment »

We are currently exploring wearable computing solutions for firefighters in the line of duty. Navigation and orientation in extremely difficult environments (often on fire) with very low visibility is a huge challenge faced by firefighters everyday, and a key design challenge. Lots of interesting work happening in this area.
Still at the desktop and field research stage, here’s a great story I found today while browsing the net – the story of a firefighter who turned designer after being trapped himself in what turned out to be the perfect research situation. The page also has a good example of a very simple but effective video prototype (they could have shown more of the details of the actual device to make it even better IMO).


Written by Ashwin Rajan

January 14, 2009 at 9:48 pm

History of Religion Visualization

with one comment

Check out this compelling information visualization on the history of religion in movie format. The movie approach to presenting visualizations is very effective for communicating encapsulated information about limited and specific parameters – in this case WHEN, WHICH and HOW MUCH five dominant religions flourished.

A visulization of the history of religion in movie format

A visulization of the history of religion in movie format

This mode is the opposite approach to an interactive timeline/map approach, where all of the information would be available upfront, and the user learns primarily by exploring the interface. In which case, the customization made available to users is gained by trading off the goal to communicate something very specific as is achieved by this visualization.

Come to think of it, it is surprisingly difficult to go beyond the handful of infoviz presentation formats in currency today.  Maps, charts, graphs, clouds, trees and network diagrams seem to dominate in different forms and variations. And this is true for two reasons – its incredibly hard to find new metaphors that do a great job of representing qualitative information, and secondly, I suspect it has a lot to do with our own preferred ways of ‘seeing meaning’ – the information scanning, browsing and seeking behaviors we are most attuned to.

For instance, this is a list of Visualization Types provided by IBM’s ‘Many Eyes’. While the formats are decidely limited, the possibilities of exploiting these formats to present various types and degrees of qualitative information (as suggested by the titles they are grouped under) catch my eye.

1. See the world:
-World maps
-Country maps

2.Track rises and falls over time:
-Line graph
-Stack graph
-Stack graph for categories

3.Compare a set of values:
-Bar chart
-Block histogram
-Bubble chart
-Matrix chart

4.See relationships among data points
-Network diagram

5.See parts of a whole
-Pie chart
-Tree map
-Change tree map

6.Look for common words in a text
-Tag cloud
-Word tree

Written by Ashwin Rajan

January 2, 2009 at 4:38 am

Visualizing Wind

leave a comment »

This mini-project was executed as part of the Computational Design course at CIID some weeks back. My objective was to use the Nintendo Wii to record simple wind data by suspending the Wii in an open location, and using the recorded data to create visualizations drawn by programming in Processing. More details follow.

The Concept:
This intent is to show  a concept for visualization of simulated wind data as would be available from a sensor located on a windmill.
A real stakeholder – wind data analyst – from a leading Danish consultancy was interviewed to understand key challenges in wind turbine design.
It is common in the Danish wind industry (and elsewhere) to record wind data for very small intervals of time. By understanding wind patterns in terms of its properties such as acceleration and constancy, engineers are able to go beyond physical limitations of turbine design to evolve increasingly efficient and productive systems.
With over 20 sensors recording different parameters on a single windmill, analysts often face a veritable mountain of data (down to individual seconds). In this context, visualization of such data in a manner that facilitates comparison, causality and multivariant evidence becomes key. The poster describes briefly how some of these goals were met.

The delightful ‘Wiimote’ was used in this experiment to mimic the sensor.

Design Context: A real world scenario 
Location: a wind farm out in the North Sea
o   72 turbines
o   20 sensors on each turbine
o   Each sec of wind data recorded
o   Data from 8 years archived for analysis

·      The peak production of windmills of all capacities is 60% of full capacity due to physical limitations
·      Measuring constancy of wind is of most interest to wind analysts and windmills designers
·      Acceleration of wind is most deterrent to wind production as it wears out the material most, and least load on the material comes from constancy of wind
·      The main difficulty in real-world wind turbine design isn’t generating the most electricity at a given speed – it is making blades which will work across a range of wind speeds
·      The design challenge is to be able to measure and visualize wind data in a way that can help engineers interpret the ‘acceleration’, ‘lift’ and ‘orientation’ of wind.

Using the Wii Remote as principle sensor
Wii remote sensors simulate the acceleration of wind by it’s x, y, z acceleration coordinates
·      In order to holistically render the acceleration of wind in a visual manner, we have focused on gathering data in coordinate directions x and y, and rendered the z axis insignificant – by suspending the sensor (in this case, the Wiimote) with a cord of fixed length.
·      Due to the position of the Wii remote when recording the raw wind data, the x and y coordinates are principle axis in this experiment. This has two benefits
o   The z sensor is rendered insignificant in terms of contributing to measuring acceleration, thus rendering it simpler by reducing the number of variables required in its calculating
o   The z axis becomes dedicated to measuring ‘lift’ and denoted here by the small series of arcs at the bottom.

Anatomy of a second - Composite View
Anatomy of a second – Composite View


And another mode of visualizing the same data set …




Written by Ashwin Rajan

November 30, 2008 at 9:00 pm