1. Establish a Physical and Visual Link between Park – Site – Sea

2. Build a Covered Market based on a roof surface

3. Turn the building into a Power Plant using PV panels

What is the average speed a person achieves during that route, and how is it affected by obstacles or distractions such as traffic or beautiful visions…

Data was obtained from myTrack app for Android on a smartphone. The app registered via gps the position and speed of the subject during the route from his house to IaaC University in Barcelona.

From the vizualizing results some conclusions were drawn:

Vizualization Strategy and Tools:

1 – Get Ortophotomap from Google Earth with two referenced GPS points

2 – Import Map in Rhino and scale it to real size

3 – Draw points in Rhino on referenced points from map, and assign them in Grasshopper

4 – Assign referenced points in Grasshopper GPS coordinates and with Ghowl reference them to global GPS system

5 – Import in Grasshopper data file containing GPS tracked points and speed

6 – Arrange data file, sorting and listing position and speed items

7 – Assign circles and color meshes to each tracking point, the wider the circle and the redder the color,the bigger the speed

8 – Assign vertical line and 3dtext to indicate exact speed at each point

Suppose you want to buy a house in Spain.

First you would look at the prices per square meter of each major city and compare them. The objective of an analysis tool to make that process easier would be to establish a visual link between that cost per m2 and the geographic position of each major city.

0. BACKGROUND

Looking into Ben Fry´s Phd Thesys “Computacional Information Design”, MIT 2004,  one can realize the potential of communicating large ammounts of complex data in a visual way. To represent it one needs an adequate tool and to think of a proccess/strategy to handle that data, mainly consisting of two steps:

1 – obtaining and preparing/arranging Data

2 – representing that data

Ben Fry describes it in the following sequence:

acquire – parse – filter – mine – represent – refine – interact

It is important that the person that gets the data and prepares it is the same that the one who represents it. There´s an important connection between preparing data and linking it in a visual tool, in terms of translating the data, like in the case of Grasshopper for this exercise.

1. GETTING DATA

The first step was obtaining reliable data, to do so I accessed Ministerio de Fomento online and downloaded excel datasheets containing cities and houses price per m2 in Spain. The second step was deleting minor cities and irrelevant data. The third step was ordering cities alphabetically and saving excel files to import later in GH.

For the visualization strategy I followed this sequence: