Category: Data Visualisation

My Year in Maps

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Lots happened in 2016 to keep cartographers busy…here are some of my highlights (in no particular order).   Maps and the 20th Century: Drawing the Line at the British Library is an absolutely extraordinary exhibition at the British Library. The breadth and quality of maps on display is amazing. (Inspired by the exhibition, I am giving a […]

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2016 in maps, Data Visualisation, Maps, Slideshow, visualisation

7 Deadly Sins of (Academic) Data Visualisation

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I was recently asked to deliver a days training on scientific data visualisation. I spent a while scanning through papers to pull out what I see as the “7 deadly sins” of academic data visualisation (there are probably many more) . These sins are rooted in a lack of time and training, an underestimation of the importance […]

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best practice, Data Visualisation, mapping, Resources, sins, visualisation

Mapping London’s Twitter Activity in 3d

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Image 1. The tweet density from 8am to 4pm on 20th June 2015, Central London




Twitter Mapping is increasingly useful method to link virtual activities and geographical space. Geo-tagged data attached to tweets containing the users’ location where they tweeted and it can visualise the locations of users on the map. Although the number of the geo-taggedtweets is a relatively small portion of all tweets, we can figure out the density, spatial patterns and other invisible relationships between online and offline.


Recently, studies with geo-tagged tweets have been developed to analyse the public response tospecific urban events, natural disasters and regional characteristics (Li et al., 2013) [1].  Furthermore, it is extending to traditional urban research topics, for example, revealing spatial segregation and inequality in cities (Shelton et al., 2015) [2].

 

Twitter mapping in 3D can augment 2d visualisation by providing built environment contexts and improved information. There are many examples of Twitter mapping in 3d such as A) #interactive/Andes [3] , B) London’s Twitter Island [4], C) Mapping London in real time, using Tweets [5]. A) and B) build up 3d mountains of the geo-tagged tweet on the map.  In the case of C), when the geo-tagged tweets are sent in the city, the heights of nearest buildings increase in the 3d model. These examples are creative and show different ways to view the integrated environments.

From a Networking City’s view, if we make a Twitter visualisation more tangible in a 3d urban model, it would help us to have a better understanding how urban environments are interconnected with the invisible media flow.

 

To make the visualisation, the Twitter data has been collected by using Big Data Toolkit developed by Steven Gray at CASA, UCL. All 53,750 geo-tagged tweets are collected on 20thJune, 2015 across the UK. As we can see from Table 1, the number of tweets was at the lowest point at 5am and reached to the highest point at 10pm with 3495 tweets. Moreover, Video 1 shows the location of the data in the UK and London on that day in real time.

 


Table 1. The Number of Geo-Coded Tweets in the UK on 20th June, 2015

 

https://www.youtube.com/watch?v=dg-2VlVfFaM



Video 1. The location of Geo-Coded Tweets in the UK on 20th June, 2015



When we calculate the density of the data, London, particularly Central London, contains the largest number of the tweets. (Image 2)

 

 

 

Image 2. The density of Geo-Coded Tweets in the UK on 20th June, 2015

In order to focus on the high density data, 6 km x 3.5 km area of Central London is chosen for the 3d model. Buildings, bridges, roads and other natural environments of the part of London have been set in the model based on OS Building Heights data[6]. Some Google 3d warehouse buildings are added to represent important landmark buildings like St.Pauls, London Eye and Tower Bridge as you can see from Image 3, Image 4 and Image 5.

 

 

Image 3. The plan view of Central London model

Image 4. The perspective view of Central London model

Image 5. The perspective view of Central London model (view from BT Tower)

The geo-tagged data set is divided into one hour periodsand distributed on the map to identify the tweet density in the area. Through this process, we can see how the density is changing depending on the time period. For example, the tweets are mainly concentrated around Piccadilly Circus and Trafalgar Square between 10am and 11am, but  there are two high-density areas between 12pm and 1pm (See Image 6, Image 7, Image 8 and Image 9)

Image 6. The tweet density between 10am and 11am on 20th June 2015

Image 7. The tweet density between 12pm and 1pm on 20th June 2015

Image 8. The tweet density from 12am to 12pm

Image 9. The tweet density from 12pm to Midnight

 


 

As we’ve seen above, the 2d mapping is useful to understand the relative density in one period such as which area is high and which area is low between 12pm and 1pm. However, we cannot understand the degree of intensity in the highest peak areas. It is believed that 3d mapping is needed at this stage. We can clearly see the density of the tweet data in each periodand the intensity of the tweet density across the time periods from Image 10 to Image 14.

West End area shows high density throughout the whole day but City area shows the peak only during lunch time. This pattern likely relates to the activities of office workers in City and leisure/tourist in West End.

Image 10. The tweet density in 3d between 10am and 11am on 20th June 2015

Image 11. The tweet density in 3d between 12pm and 1pm on 20th June 2015
 

Image 12. The tweet density in 3d from 12am to 8pm

Image 13. The tweet density in 3d from 8am to 4pm

Image 14. The tweet density from 4pm to Midnight

 

 

 ________________________________________

[1] Linna Li , Michael F. Goodchild & Bo Xu (2013) Spatial, temporal, and socioeconomic patterns in the use of Twitter and Flickr, Cartography and Geographic Information Science, 40:2, 61-77

 

[2] Taylor Shelton, Ate Poorthuis & Matthew Zook (2015) Social Media and the City: Rethinking Urban Socio-Spatial Inequality Using User-Generated Geographic Information, Landscape and Urban Planning (Forthcoming), http://papers.ssrn.com/abstract=2571757

 

[3] Nicolas Belmonte, #interactive/Andes,   http://twitter.github.io/interactive/andes/  (Strived on 15th August 2015)

 

[4] Andy Hudson-Smith, London’s Twitter Island – From ArcGIS to Max to Lumion, http://www.digitalurban.org/2012/01/londons-twitter-island-from-arcgis-to.html#comment-7314


(Strived on 15thAugust 2015)

 
[5] Stephan Hugel and Flora Roumpani, Mapping London in real time, using Tweets, https://www.youtube.com/watch?feature=player_embedded&v=3fk_qxGZWFQ (Strived on 15th August 2015)

[6] OS Building Heights-Digimap Home Page  http://digimap.edina.ac.uk/webhelp/os/data_information/os_products/os_building_heights.htm  (Strived on 15th August 2015)

 

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3d mode, 3dMapping, Big Data, CASA, Data Visualisation, geo-coded, GIS, london, mapping, SNS, twitter, Urban Data, visualisation

Mapping London’s Twitter Activity in 3d

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Image 1. The tweet density from 8am to 4pm on 20th June 2015, Central London




Twitter Mapping is increasingly useful method to link virtual activities and geographical space. Geo-tagged data attached to tweets containing the users’ location where they tweeted and it can visualise the locations of users on the map. Although the number of the geo-taggedtweets is a relatively small portion of all tweets, we can figure out the density, spatial patterns and other invisible relationships between online and offline.


Recently, studies with geo-tagged tweets have been developed to analyse the public response tospecific urban events, natural disasters and regional characteristics (Li et al., 2013) [1].  Furthermore, it is extending to traditional urban research topics, for example, revealing spatial segregation and inequality in cities (Shelton et al., 2015) [2].

 

Twitter mapping in 3D can augment 2d visualisation by providing built environment contexts and improved information. There are many examples of Twitter mapping in 3d such as A) #interactive/Andes [3] , B) London’s Twitter Island [4], C) Mapping London in real time, using Tweets [5]. A) and B) build up 3d mountains of the geo-tagged tweet on the map.  In the case of C), when the geo-tagged tweets are sent in the city, the heights of nearest buildings increase in the 3d model. These examples are creative and show different ways to view the integrated environments.

From a Networking City’s view, if we make a Twitter visualisation more tangible in a 3d urban model, it would help us to have a better understanding how urban environments are interconnected with the invisible media flow.

 

To make the visualisation, the Twitter data has been collected by using Big Data Toolkit developed by Steven Gray at CASA, UCL. All 53,750 geo-tagged tweets are collected on 20thJune, 2015 across the UK. As we can see from Table 1, the number of tweets was at the lowest point at 5am and reached to the highest point at 10pm with 3495 tweets. Moreover, Video 1 shows the location of the data in the UK and London on that day in real time.

 


Table 1. The Number of Geo-Coded Tweets in the UK on 20th June, 2015

 

https://www.youtube.com/watch?v=dg-2VlVfFaM



Video 1. The location of Geo-Coded Tweets in the UK on 20th June, 2015



When we calculate the density of the data, London, particularly Central London, contains the largest number of the tweets. (Image 2)

 

 

 

Image 2. The density of Geo-Coded Tweets in the UK on 20th June, 2015

In order to focus on the high density data, 6 km x 3.5 km area of Central London is chosen for the 3d model. Buildings, bridges, roads and other natural environments of the part of London have been set in the model based on OS Building Heights data[6]. Some Google 3d warehouse buildings are added to represent important landmark buildings like St.Pauls, London Eye and Tower Bridge as you can see from Image 3, Image 4 and Image 5.

 

 

Image 3. The plan view of Central London model

Image 4. The perspective view of Central London model

Image 5. The perspective view of Central London model (view from BT Tower)

The geo-tagged data set is divided into one hour periodsand distributed on the map to identify the tweet density in the area. Through this process, we can see how the density is changing depending on the time period. For example, the tweets are mainly concentrated around Piccadilly Circus and Trafalgar Square between 10am and 11am, but  there are two high-density areas between 12pm and 1pm (See Image 6, Image 7, Image 8 and Image 9)

Image 6. The tweet density between 10am and 11am on 20th June 2015

Image 7. The tweet density between 12pm and 1pm on 20th June 2015

Image 8. The tweet density from 12am to 12pm

Image 9. The tweet density from 12pm to Midnight

 


 

As we’ve seen above, the 2d mapping is useful to understand the relative density in one period such as which area is high and which area is low between 12pm and 1pm. However, we cannot understand the degree of intensity in the highest peak areas. It is believed that 3d mapping is needed at this stage. We can clearly see the density of the tweet data in each periodand the intensity of the tweet density across the time periods from Image 10 to Image 14.

West End area shows high density throughout the whole day but City area shows the peak only during lunch time. This pattern likely relates to the activities of office workers in City and leisure/tourist in West End.

Image 10. The tweet density in 3d between 10am and 11am on 20th June 2015

Image 11. The tweet density in 3d between 12pm and 1pm on 20th June 2015
 

Image 12. The tweet density in 3d from 12am to 8pm

Image 13. The tweet density in 3d from 8am to 4pm

Image 14. The tweet density from 4pm to Midnight

 

 

 ________________________________________

[1] Linna Li , Michael F. Goodchild & Bo Xu (2013) Spatial, temporal, and socioeconomic patterns in the use of Twitter and Flickr, Cartography and Geographic Information Science, 40:2, 61-77

 

[2] Taylor Shelton, Ate Poorthuis & Matthew Zook (2015) Social Media and the City: Rethinking Urban Socio-Spatial Inequality Using User-Generated Geographic Information, Landscape and Urban Planning (Forthcoming), http://papers.ssrn.com/abstract=2571757

 

[3] Nicolas Belmonte, #interactive/Andes,   http://twitter.github.io/interactive/andes/  (Strived on 15th August 2015)

 

[4] Andy Hudson-Smith, London’s Twitter Island – From ArcGIS to Max to Lumion, http://www.digitalurban.org/2012/01/londons-twitter-island-from-arcgis-to.html#comment-7314


(Strived on 15thAugust 2015)

 
[5] Stephan Hugel and Flora Roumpani, Mapping London in real time, using Tweets, https://www.youtube.com/watch?feature=player_embedded&v=3fk_qxGZWFQ (Strived on 15th August 2015)

[6] OS Building Heights-Digimap Home Page  http://digimap.edina.ac.uk/webhelp/os/data_information/os_products/os_building_heights.htm  (Strived on 15th August 2015)

 

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3d mode, 3dMapping, Big Data, CASA, Data Visualisation, geo-coded, GIS, london, mapping, SNS, twitter, Urban Data, visualisation

Mapping London’s Twitter Activity in 3d

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Image 1. The tweet density from 8am to 4pm on 20th June 2015, Central London Twitter Mapping is increasingly useful method to link virtual activities and geographical space. Geo-tagged data attached to tweets containing the users’ location where the…

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3d mode, 3dMapping, Big Data, CASA, Data Visualisation, geo-coded, GIS, london, mapping, SNS, twitter, Urban Data, visualisation

GIS Course Note 02: Research Application, Software and Data Sources

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The second lecture of GIS comprised mainly three parts, the examples of practical research by using GIS, GIS software and the way to gain relevant data for the research.  
In the beginning, Dr. Adam Dennett, the lecturer of CASA, informed the aim of the lecture to understand the basic elements of social science research using GIS and the diverse analytical approaches with it. He showed several example maps, which are related to population, crime, deprivation, health care, flooding, and education, and the way how to read economic, social and physical characteristics from the maps and its meaning in the projects. (Image 1)



Image 1



And then, he moved to GIS software industry which has been significantly growing. As interest and the utilisation of GIS are increasing, GIS software market is expanding almost 10% every year and now it is used in all industries and public sectors such as business, public safety, military and education. The popular GIS tools: Arc GIS, MAP Info, Quantum GIS, Pythonand R, and specific points of each tool were introduced. Also, small description of GIS cloud and online GIS tools was following. (Image 2)

Image 2

In the last part, he said of various kinds of the data and the way of gathering the data which is the key element to proceed the research. Easily, we can classify the data according to the way of gathering. On the one hand, we can use the open data, which are provided by public sectors and other organisations. On the other hand, we need to collect the data through participation and measuring by ourselves. Some websites of the UK, which contain the open data or shapefiles, and the characteristics of each website were mentioned. As we can see Image 3, some other methods like WebScarping and Volunteered Geographic Information were shown as alternative ways to collect the data by ourselves, when the given data are unclear, and the goal of the research needs the specific data.

Image 3

 

The lecture was finished with the emphasis on caution when using the open data and the mapping with it. Much of the data are made with inadequate formats like pdf, or do not include any spatial reference, so we need to be careful to collect and use the data. When it came to the mapping with the data, he insisted that it is necessary to make analytical and meaningful maps rather than something fancy or colourful. In addition, it is essential to acknowledge that some errors could be made by way of ‘generalisation’ in the process of research, therefore, setting up the range and the level of the research will enrich the quality of it.
 
After one hour lecture, students had a training session that mapping population data on the map of London Borough with R. (Image 4)
Image 4

 

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Adam, CASA, Data Visualisation, GIS, mapping, Note, Open Data, public data, software

GIS Course Note 02: Research Application, Software and Data Sources

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The second lecture of GIS comprised mainly three parts, the examples of practical research by using GIS, GIS software and the way to gain relevant data for the research.  
In the beginning, Dr. Adam Dennett, the lecturer of CASA, informed the aim of the lecture to understand the basic elements of social science research using GIS and the diverse analytical approaches with it. He showed several example maps, which are related to population, crime, deprivation, health care, flooding, and education, and the way how to read economic, social and physical characteristics from the maps and its meaning in the projects. (Image 1)



Image 1



And then, he moved to GIS software industry which has been significantly growing. As interest and the utilisation of GIS are increasing, GIS software market is expanding almost 10% every year and now it is used in all industries and public sectors such as business, public safety, military and education. The popular GIS tools: Arc GIS, MAP Info, Quantum GIS, Pythonand R, and specific points of each tool were introduced. Also, small description of GIS cloud and online GIS tools was following. (Image 2)

Image 2

In the last part, he said of various kinds of the data and the way of gathering the data which is the key element to proceed the research. Easily, we can classify the data according to the way of gathering. On the one hand, we can use the open data, which are provided by public sectors and other organisations. On the other hand, we need to collect the data through participation and measuring by ourselves. Some websites of the UK, which contain the open data or shapefiles, and the characteristics of each website were mentioned. As we can see Image 3, some other methods like WebScarping and Volunteered Geographic Information were shown as alternative ways to collect the data by ourselves, when the given data are unclear, and the goal of the research needs the specific data.

Image 3

 

The lecture was finished with the emphasis on caution when using the open data and the mapping with it. Much of the data are made with inadequate formats like pdf, or do not include any spatial reference, so we need to be careful to collect and use the data. When it came to the mapping with the data, he insisted that it is necessary to make analytical and meaningful maps rather than something fancy or colourful. In addition, it is essential to acknowledge that some errors could be made by way of ‘generalisation’ in the process of research, therefore, setting up the range and the level of the research will enrich the quality of it.
 
After one hour lecture, students had a training session that mapping population data on the map of London Borough with R. (Image 4)
Image 4

 

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Adam, CASA, Data Visualisation, GIS, mapping, Note, Open Data, public data, software

A hive plot of hospitality received by Coalition Special Advisers

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With political transparency an increasingly topical subject in the wake of press scandals and allegations of official coverup, it is a useful exercise to examine any data reflecting the interaction between our leaders and our purveyors of news. Since taking power the UK coalition government has published records of hospitality received by Special Advisers – […]

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Data Visualisation, meda, politics, R statistical programming

A hive plot of hospitality received by Coalition Special Advisers

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With political transparency an increasingly topical subject in the wake of press scandals and allegations of official coverup, it is a useful exercise to examine any data reflecting the interaction between our leaders and our purveyors of news. Since taking power the UK coalition government has published records of hospitality received by Special Advisers – […]

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Data Visualisation, meda, politics, R statistical programming

Review: Designing for the situated and public visualisation of urban data

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Journal of Urban Technology, Volume 19, Issue 2, 2012
Designing for the situated and public visualisation of urban data
by Andrew Vande Moere & Dan Hill

THE authors point out recent urban data visualisation still remains on the stage of simply providing statistical data, and it is ineffective to make better understanding about the interaction of the massive and complex urban data. They argue public policy should be changed to open more public data, which are including local characteristics, to raise public awareness and encourage actionable public participation.

Through five main parts; theoretical part (data and public visualisation) – Recent projects – Student projects – characteristics of urban visualisation – conclusion, this article draws the question and tries to answer against how we can visualise the complex and continuously changing condition of cities, where have different problems by particular factors in different parts within a city, and how we can expect the unpredictable condition in the information age.

The authors premise that the character of place has been formulated by economic and cultural patterns based on the rock of physical and geographical aspects, and these patterns adversely facilitate the physical change.  In the past, the production of the place represented the specific character of the place, and it had coupled with the regional change. However, since cities have transformed their industry from material based to knowledge based, they have been showing the movement of hominization. This paper argues that the character of the city in this era can be revealed by the data, which are endlessly producing in the city, and we can find the difference between cities by the analysis of the data.  Therefore, the urban data is not an indicator of urban activities but also the driving force leading qualitative changing of the urban environment.

Particularly, previous data unilaterally delivered statistical data of urban areas, but recent the urban data stimulate active participation of citizen by well-developed mobile devices and illustrate what feedbacks are creating by the citizen. And the authors emphasize the following elements are essential to visualise the urban data.  
1) Situated : contextual, local, social
2) Informative: feedback, insightful, consistent
3) Functional: medium, participate, opportunistic, aesthetic, trustworthy, persuasive

Despite a lot of attractive contents, the most impressive point in the article is the well-organised logical flow of what they use; Neo-industrial city (production of data) – open data (role of public data) – social visualisation (impact of data) – urban computing (technological integration) – urban scene (combination of data & urban environment), to explain the meaning of data in this period, its social role and the combination with the physical environment. When we consider the vague use and weak logical connection of the concepts surrounding the data and urban areas, it is a profound approach. This article reminds us to make a coherent structure and clear correlation is an critical issue to set up the base of opinion and to insist it by writing.

To cite this article: Andrew Vande Moere & Dan Hill (2012) Designing for the Situated and Public Visualization of Urban Data, Journal of Urban Technology, 19:2, 25-46
 
 
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Andrew Vande Moere, Dan Hill, Data Visualisation, journal, public data, review, Smart city, Urban Data

Review: Designing for the situated and public visualisation of urban data

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Journal of Urban Technology, Volume 19, Issue 2, 2012
Designing for the situated and public visualisation of urban data
by Andrew Vande Moere & Dan Hill

THE authors point out recent urban data visualisation still remains on the stage of simply providing statistical data, and it is ineffective to make better understanding about the interaction of the massive and complex urban data. They argue public policy should be changed to open more public data, which are including local characteristics, to raise public awareness and encourage actionable public participation.

Through five main parts; theoretical part (data and public visualisation) – Recent projects – Student projects – characteristics of urban visualisation – conclusion, this article draws the question and tries to answer against how we can visualise the complex and continuously changing condition of cities, where have different problems by particular factors in different parts within a city, and how we can expect the unpredictable condition in the information age.

The authors premise that the character of place has been formulated by economic and cultural patterns based on the rock of physical and geographical aspects, and these patterns adversely facilitate the physical change.  In the past, the production of the place represented the specific character of the place, and it had coupled with the regional change. However, since cities have transformed their industry from material based to knowledge based, they have been showing the movement of hominization. This paper argues that the character of the city in this era can be revealed by the data, which are endlessly producing in the city, and we can find the difference between cities by the analysis of the data.  Therefore, the urban data is not an indicator of urban activities but also the driving force leading qualitative changing of the urban environment.

Particularly, previous data unilaterally delivered statistical data of urban areas, but recent the urban data stimulate active participation of citizen by well-developed mobile devices and illustrate what feedbacks are creating by the citizen. And the authors emphasize the following elements are essential to visualise the urban data.  
1) Situated : contextual, local, social
2) Informative: feedback, insightful, consistent
3) Functional: medium, participate, opportunistic, aesthetic, trustworthy, persuasive

Despite a lot of attractive contents, the most impressive point in the article is the well-organised logical flow of what they use; Neo-industrial city (production of data) – open data (role of public data) – social visualisation (impact of data) – urban computing (technological integration) – urban scene (combination of data & urban environment), to explain the meaning of data in this period, its social role and the combination with the physical environment. When we consider the vague use and weak logical connection of the concepts surrounding the data and urban areas, it is a profound approach. This article reminds us to make a coherent structure and clear correlation is an critical issue to set up the base of opinion and to insist it by writing.

To cite this article: Andrew Vande Moere & Dan Hill (2012) Designing for the Situated and Public Visualization of Urban Data, Journal of Urban Technology, 19:2, 25-46
 
 
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Andrew Vande Moere, Dan Hill, Data Visualisation, journal, public data, review, Smart city, Urban Data

Review: Designing for the situated and public visualisation of urban data

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Journal of Urban Technology, Volume 19, Issue 2, 2012Designing for the situated and public visualisation of urban databy Andrew Vande Moere & Dan Hill THE authors point out recent urban data visualisation still remains on the stage of simply provi…

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Andrew Vande Moere, Dan Hill, Data Visualisation, journal, public data, review, Smart city, Urban Data

The World Protests by GDELT

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Image 1. All GDELT protest data for 2013. The image was captured from GDELT’s work. (See below)

Global Database of Events, Language, and Tone (GDELT) is a remarkable organisation to provide, freely, the data of all human behaviours, particularly protest, over the world since 1979. They are trying to make “real-time social sciences earth observatory” by updating the data every day. It is running by three researchers, Kalev Leetaru, Philip Schrodt and Patrick Brandt. 
 
If you visit their website and their blog, you would be surprised by their enormous data set as well as effective and nice visualisation. For example, recent GDELT’s work is showing protest movement in 2013. (Image 1) This interactive map illustrates how many protests have been raising in the world a year including Egypt, Brazil and Turkey, and we can recognise that the flame of protests are covering the world even though the data would not report all hidden protests.
 
Image 2. Syria’s civil war. The image was captured from GDELT’s work. (See below) 
 
Another map describes the terrific condition of Syria’s civil war in detail. (Image 2) Visualising the location, the number of violence per day and the period of the civil war together warns us how the situation is significant much more than just some sentences and images of broadcasting news. It was issued on The Guardian.  
 
However, the most important thing is their continuous effort to collect the data, sort it out and provide the valuable data for further research. Opening the data might not be an easy decision and it would be a extremely time-consuming work.
 
After visiting the website of GDELT, Networking City understood the importance of open data, its impacts and the power of visualisation, and promised to work hard and being more opened.
 
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Big Data, Data Visualisation, GDELT, Open Data, protest, Syria, urban planning

The World Protests by GDELT

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Image 1. All GDELT protest data for 2013. The image was captured from GDELT’s work. (See below)

Global Database of Events, Language, and Tone (GDELT) is a remarkable organisation to provide, freely, the data of all human behaviours, particularly protest, over the world since 1979. They are trying to make “real-time social sciences earth observatory” by updating the data every day. It is running by three researchers, Kalev Leetaru, Philip Schrodt and Patrick Brandt. 
 
If you visit their website and their blog, you would be surprised by their enormous data set as well as effective and nice visualisation. For example, recent GDELT’s work is showing protest movement in 2013. (Image 1) This interactive map illustrates how many protests have been raising in the world a year including Egypt, Brazil and Turkey, and we can recognise that the flame of protests are covering the world even though the data would not report all hidden protests.
 
Image 2. Syria’s civil war. The image was captured from GDELT’s work. (See below) 
 
Another map describes the terrific condition of Syria’s civil war in detail. (Image 2) Visualising the location, the number of violence per day and the period of the civil war together warns us how the situation is significant much more than just some sentences and images of broadcasting news. It was issued on The Guardian.  
 
However, the most important thing is their continuous effort to collect the data, sort it out and provide the valuable data for further research. Opening the data might not be an easy decision and it would be a extremely time-consuming work.
 
After visiting the website of GDELT, Networking City understood the importance of open data, its impacts and the power of visualisation, and promised to work hard and being more opened.
 
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Big Data, Data Visualisation, GDELT, Open Data, protest, Syria, urban planning

Review: City Sense – Shaping our environment with real-time data

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Image1. The cover image of ‘City Sense – Shaping our environment with real-time data’

Since 2005, the Institute for Advanced Architecture of Catalonia in Barcelona, which is a provocative architectural school and research institution, has opened architectural competition once in every two years. This competition seeks new types of architectural experiments in the fast changing urban environment and is gaining an international reputation over the world. The most recent competition was held in 2011, and 275 groups participated in from 98 countries. The themes of the competition have expected ideal projections in the future rather than current urban situations; therefore, it is a bit harder to articulate architectural ideas of the themes than other competitions.
 
The book “City Sense – Shaping our environment with real-time data”, which was published by ACTAR, is the outcome of the competition in 2011 and the title of the book is the same as it of the competition. 
 
High speed information and communication technologies have created more possibilities of diversity, mobility and change in the city that comparatively the speed of change is lower than the speed of the technologies by its physical nature. Therefore, urban design and urban planning in the future would claim not traditional approaches for physical urban structure but more and more concerns of immaterial and invisible urban factors based on the development of the technology. In the preface of City Sense, Manuel Gausa, Dean of IAAC, argues that new urban dynamics will emerge from interactive, synchronous and integrated information in multi-level of urban areas, not physical characteristics any more. He explains the purpose of this competition was to find innovative ways of urban design for increasing civic participation, interactive response with the urban environment and real-time information. 
 

Image 2. page 76-77. Honourable Mention- THE DATA-CITIZEN DRIVEN CITY

Image 3. Second prize winner- THE CYBORG LANDSCAPE
 

Image 4. Third prize winner- RCNHA 2030+
 


Image 5. Honourable Mention- 0kWhcity

 The publisher divided competition entry works into six categories: Sensors & Data, Adaptive & Reactive, Behavioural systems, Parametric technology, Social & Collaborative and Theories & Strategies. There are many fresh and fascinating ideas to show various approaches to architectural and urban design. For example, enhancing digital networks in urban areas by social media and applying to urban management, reducing the rate of risky incidences of Chicago through making 1/25 scale testing model of Chicago, creating on-offline network for exchanging second-hand goods and suggestion for architectural system to checking environmental pollution in the site of landfill.

Among lots of entertaining works, Francisco’s work, which is the first prize winner, is outstanding. Francisco Castillo Navarro is an architect and interactive designer. After he graduated from ETSAS and UPF, he set up his own research group: Responsive Environments and has been doing several research projects focus on the urban environment changes.
 



Image 6. pp.82-83. First prize winner– CITY DATA SENSING
 

Image 7. Panel image of CITY DATA SENSING
 
His idea is to collect invisible but influential data for urban life such as the flows of energy, transportation and economic, and to provide these data with citizen based on real-time. It leads the change of citizen activities and then new information are generated by these changes, as the result, the citizen and the information in urban endlessly foster the interaction between them.
The most participants are bound in physical architectural suggestions as the outcome of the competition; however, Francisco illustrates that integrated system for real-time information, which would stimulate sustainable interactive actions of citizen, could become an aggressive outcome of urban design in the digital era. Unlike other entry works which started from architectural ideas, his approach began from the other fields such as collecting real-time data, visualisation of big data and urban modelling. His final images for the competition could be understood as pretending to describe multiple urban data; however, his actual final work is a movie file to display collecting urban information on tidal system and visualising it.  As the result, other participants demonstrate images and systems at the moment; however, Francisco’s work suggests that the tidal changes of urban information and the visualising structure of real operating situation. Please check his movie image here.  On his blog pages, there are nice information of 3d printing and robotic fabrication as well as his works. Blog1 and Blog2. 
 
The new book of ACTAR is too full of suggestions to regard just the outcome of idea competition. Above all, this book clearly points out that new urban environment based on the rapid developing technologies pushes architects need to collaborate with other fields more than before. It reminds us to consider how the urban environment will be changed by integrated set of information from individuals and institutions, and how new technologies impact on architecture.
Secondly, all winning projects of the competition propose specific own urban system connecting with all urban area not separate buildings. Traditional design approach, which means the sequence of analysing site, finding similar cases, making concept idea, developing mass and building up 3d model, cannot be available anymore for new urban design that needs to understand and develop urban networks and its system.
 
Of course, there are some disappointing parts.
All participants submitted three panel images through the internet, but it is doubtful whether traditional panel images would be applicable to explain invisible flow of data in urban areas or not. As we regard that the real outcome of the first prize winner is a movie image, IAAC needs to revise the format of the submission. On the one hand, there are many fresh ideas and well finished projects. On the other hand, I think the most projects are not far away from pre-existing design methods and are rooted in technical optimism that the city could be effectively controlled by one system. Also, the size of the book is relatively small. It is convenient to carry, but uncomfortable to look at images.
 
But it is obvious to allow this book as a good reference to designate the influence of the technologies on the city and alternative ways of urban design in digital era.
 
The detailed contents and the entry works of last competitions are well arranged on the homepage of IAAC. Please visit there.  
1st competition- Self-Sufficient Housing, 2005http://bit.ly/YMF79q
2nd competition- Self-Sufficient Housing, THE SELF-FAB HOUSE, 2007http://bit.ly/WphN53
3rd competition- THE SELF-SUFFICIENT CITY: Envisioning the habitat of the future, 2009http://bit.ly/13zxrgk
4th competition- THE SELF-SUFFICIENT CITY: Envisioning the habitat of the future, 2011http://bit.ly/Crab7

 

Basic outcome is below.

Paperback: 368 pages
Publisher: ACTAR / Institut d’Arquitectura Avançada de Catalunya (IAAC)
                 (2 Jan 2013)
Language: English
ISBN-10: 8415391293
ISBN-13: 978-8415391296
Product Dimensions: 16 x 12.2 x 2.3

Continue reading »
2013, Actar, Book, city sense, Data Visualisation, review, Social Networks, urban design

Review: City Sense – Shaping our environment with real-time data

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Image1. The cover image of ‘City Sense – Shaping our environment with real-time data’

Since 2005, the Institute for Advanced Architecture of Catalonia in Barcelona, which is a provocative architectural school and research institution, has opened architectural competition once in every two years. This competition seeks new types of architectural experiments in the fast changing urban environment and is gaining an international reputation over the world. The most recent competition was held in 2011, and 275 groups participated in from 98 countries. The themes of the competition have expected ideal projections in the future rather than current urban situations; therefore, it is a bit harder to articulate architectural ideas of the themes than other competitions.
 
The book “City Sense – Shaping our environment with real-time data”, which was published by ACTAR, is the outcome of the competition in 2011 and the title of the book is the same as it of the competition. 
 
High speed information and communication technologies have created more possibilities of diversity, mobility and change in the city that comparatively the speed of change is lower than the speed of the technologies by its physical nature. Therefore, urban design and urban planning in the future would claim not traditional approaches for physical urban structure but more and more concerns of immaterial and invisible urban factors based on the development of the technology. In the preface of City Sense, Manuel Gausa, Dean of IAAC, argues that new urban dynamics will emerge from interactive, synchronous and integrated information in multi-level of urban areas, not physical characteristics any more. He explains the purpose of this competition was to find innovative ways of urban design for increasing civic participation, interactive response with the urban environment and real-time information. 
 

Image 2. page 76-77. Honourable Mention- THE DATA-CITIZEN DRIVEN CITY

Image 3. Second prize winner- THE CYBORG LANDSCAPE
 

Image 4. Third prize winner- RCNHA 2030+
 


Image 5. Honourable Mention- 0kWhcity

 The publisher divided competition entry works into six categories: Sensors & Data, Adaptive & Reactive, Behavioural systems, Parametric technology, Social & Collaborative and Theories & Strategies. There are many fresh and fascinating ideas to show various approaches to architectural and urban design. For example, enhancing digital networks in urban areas by social media and applying to urban management, reducing the rate of risky incidences of Chicago through making 1/25 scale testing model of Chicago, creating on-offline network for exchanging second-hand goods and suggestion for architectural system to checking environmental pollution in the site of landfill.

Among lots of entertaining works, Francisco’s work, which is the first prize winner, is outstanding. Francisco Castillo Navarro is an architect and interactive designer. After he graduated from ETSAS and UPF, he set up his own research group: Responsive Environments and has been doing several research projects focus on the urban environment changes.
 



Image 6. pp.82-83. First prize winner– CITY DATA SENSING
 

Image 7. Panel image of CITY DATA SENSING
 
His idea is to collect invisible but influential data for urban life such as the flows of energy, transportation and economic, and to provide these data with citizen based on real-time. It leads the change of citizen activities and then new information are generated by these changes, as the result, the citizen and the information in urban endlessly foster the interaction between them.
The most participants are bound in physical architectural suggestions as the outcome of the competition; however, Francisco illustrates that integrated system for real-time information, which would stimulate sustainable interactive actions of citizen, could become an aggressive outcome of urban design in the digital era. Unlike other entry works which started from architectural ideas, his approach began from the other fields such as collecting real-time data, visualisation of big data and urban modelling. His final images for the competition could be understood as pretending to describe multiple urban data; however, his actual final work is a movie file to display collecting urban information on tidal system and visualising it.  As the result, other participants demonstrate images and systems at the moment; however, Francisco’s work suggests that the tidal changes of urban information and the visualising structure of real operating situation. Please check his movie image here.  On his blog pages, there are nice information of 3d printing and robotic fabrication as well as his works. Blog1 and Blog2. 
 
The new book of ACTAR is too full of suggestions to regard just the outcome of idea competition. Above all, this book clearly points out that new urban environment based on the rapid developing technologies pushes architects need to collaborate with other fields more than before. It reminds us to consider how the urban environment will be changed by integrated set of information from individuals and institutions, and how new technologies impact on architecture.
Secondly, all winning projects of the competition propose specific own urban system connecting with all urban area not separate buildings. Traditional design approach, which means the sequence of analysing site, finding similar cases, making concept idea, developing mass and building up 3d model, cannot be available anymore for new urban design that needs to understand and develop urban networks and its system.
 
Of course, there are some disappointing parts.
All participants submitted three panel images through the internet, but it is doubtful whether traditional panel images would be applicable to explain invisible flow of data in urban areas or not. As we regard that the real outcome of the first prize winner is a movie image, IAAC needs to revise the format of the submission. On the one hand, there are many fresh ideas and well finished projects. On the other hand, I think the most projects are not far away from pre-existing design methods and are rooted in technical optimism that the city could be effectively controlled by one system. Also, the size of the book is relatively small. It is convenient to carry, but uncomfortable to look at images.
 
But it is obvious to allow this book as a good reference to designate the influence of the technologies on the city and alternative ways of urban design in digital era.
 
The detailed contents and the entry works of last competitions are well arranged on the homepage of IAAC. Please visit there.  
1st competition- Self-Sufficient Housing, 2005http://bit.ly/YMF79q
2nd competition- Self-Sufficient Housing, THE SELF-FAB HOUSE, 2007http://bit.ly/WphN53
3rd competition- THE SELF-SUFFICIENT CITY: Envisioning the habitat of the future, 2009http://bit.ly/13zxrgk
4th competition- THE SELF-SUFFICIENT CITY: Envisioning the habitat of the future, 2011http://bit.ly/Crab7

 

Basic outcome is below.

Paperback: 368 pages
Publisher: ACTAR / Institut d’Arquitectura Avançada de Catalunya (IAAC)
                 (2 Jan 2013)
Language: English
ISBN-10: 8415391293
ISBN-13: 978-8415391296
Product Dimensions: 16 x 12.2 x 2.3

Continue reading »
2013, Actar, Book, city sense, Data Visualisation, review, Social Networks, urban design

Datascape – New 3D Dataviz tool from Daden

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This is intriguing, a new 3D package to map and explore data – Datascape, by Daden Ltd, known perviously for their work in Second Life, provides an immersive environment in which users can explore and interact with data from almost any source. David Burden, Daden’s Managing Director said “Datascape is ground-breaking and we’re…

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Data Visualisation, data viz, datascape, Featured, Front Page

3D Visualisation of World Flight Paths

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Robin Edwards, a student on our MRes in Advanced Spatial Analysis and Visualisation here at the Centre for Advanced Spatial Analysis, University College London, has used Processing to create a visualisation using data from OpenFlights.org. The clip below visualises approx 50,000 active flight-paths,interpolating motion along great circle paths for dynamic effect: Robin notes that it […]

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CASA MRes, Data Visualisation, flight path data, MRes in Advanced Spatial Analysis and Visualisation, openflights

6 Fellowships £10,000 Each at The Centre for Spatial Analysis and Policy (CSAP) in Leeds or the Centre for Advanced Spatial Analysis (CASA) in London

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We are pleased to announce the availability of six fellowships are available to support individuals in non-academic institutions to undertake defined research projects at the Centre for Spatial Analysis and Policy (CSAP) in Leeds or the Centr…

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Agent Based Modelling, CASA, Data Visualisation, fellowships, Geospatial, Leeds, Microsimulation, NCRM, TALISMAN

Visualising City Wide Data: London Retail and Office Space

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The movie below is a visualisation of office and retail space in London. Using data kindly supplied by the Economics Unit at the Greater London Authority, Duncan Smith a PhD student here at CASA has calculated the amount of retail and office in London per 500 metre grid square: Duncan…

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3D Max, ArcScene, Data Visualisation, data visualization, London Office, London Retail