Source of Sustainable Architecture in Europe Group members: Antigoni Anna Anastasopoulou, Duygu Kirisoglu, Andreana Papantoniou
The visualization: https://visit.impure.com/space/#/antigonianna/SourceOfSustainableArchitectureInEurope_ Visualiza The workspace: https://visit.impure.com/space/#/antigonianna/SourceOfSustainableArchitectureInEurope_fi nal
Our objective is to create a “source� of Sustainable Architecture for Europe where someone can see information for the systems and techniques applied on the most well-known contemporary examples of sustainable buildings and in the same time the monthly weather conditions for the city where they are located. The main goal of this data-set is to understand in which way and level weather conditions affect the design of buildings in terms of lighting, ventilation, cooling, heating, shading etc. At the visualization every point on the map represents one building. So, when one of them is selected, the systems applied to it can be seen as well as the photos of it in flickr. The weather conditions of the specific city can be also seen.
We started our project doing a research on Sustainable Architecture and we created a list of the most important self-sufficient buildings in different cities of Europe. Then, we had to identify the energy systems and design strategies that have been applied to each building. We also had to confirm that the examples of the buildings we chose could be found in flickr and we should find the exact key words to limit the photos unrelated with it. We found the exact location of each building and we took its coordinates from Google Earth. Finally, we took the monthly values of the average temperature and wind for each city for one year from the following site: http://www.wunderground.com/.
Therefore, we organized our data by creating one csv file. This file contains the Selected Buildings, the Country, the City, the Architect, the Flickr Tags, the Coordinates of each location on Google map and the Systems of Sustainability and the weather data; twelve measurements of temperature and wind for every month for each city.
This file was brought into our workspace with a “FileLoader” control. Then, we used a “Polygon2dSimpleVisualizator2” in order to locate the points-buildings that should appear on the map, getting the coordinates from the appropriate columns. This was done by using the “getSublist” with defined intervals 5 and 6, the “pairsNumberTableToPolygon” and the “universalProjectionOnTransformationGeo” operators.Then, we used a “GoogleMapsVisor” visualizator which has been connected to the “GeocoderGooglemaps” defining at the string the world “Europe”. The two vizualizators have been finally connected using the “CreatesTransformationGeo” and the “universalProjectionOnTransformationGeo” operators.
Our next step was to connect the “Polygon2dSimpleVisualizator2” with the “ImageTransition” visualizator in order to see images of the selected building. For this, we used “FlickrImageMultiSearch” api and the “MultiImageLoader” control to search and load images on Flickr. By using the “getElementFromList” and defined the number equal to 4 the list of „Flickr Tags‟ is given to “FlickrImageMultiSearch” which allows the search to be started. By using a second “getElementFromList” for connecting the “Polygon2dSimpleVisualizator2” with the “MultiImageLoader”, the image loading can be achieved by selecting the building from the map. Next, we had to connect the “Polygon2dSimpleVisualizator2” to the “HTMLVisualizator” in order to show the different systems of sustainability in a text. This was done by using two “getElementFromList” to take both the list 7 from the central csv file which corresponds to the systems and from that list the element from the selected building. Therefore, by selecting the building you can see at the same time images from Flickr and the systems that have been used.
The last part of our project was to visualize the weather data; average temperature and wind of the city where the selected building is located and at the same time to visualize the average of the weather conditions in all the European cities of our project in order to make the comparison between them easier. To manage that, we used two “curvesGraph2” visualizators which we combined with the “getRow”, the “getSubList” and the “listAssembler5” operators and two more “curvesGraph2” visualizators which we combined with the “getSubListFromPosition”, the “averages” and the “listAssembler5” operators. Finally, we overlapped all these visualizators so that they can be seen together.