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作品タイトル（日本語）
Tokyo
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作品タイトル（英語）
Tokyo
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制作物のコンセプトを記載してください。
The purpose of this artwork was to visualize data related to natural phenomena via a generative algorithm. I was especially interested in the ways data visualization could express abstract patterns. Data related to natural phenomena are often complicated, but through the use of mining data, it is often possible to bring out their beautiful and straightforward characteristics. I decided to create “Tokyo” to show the city’s temperature changes from 1990 to 2017, and thus artistically display the effects of climate change via data visualization. I have lived in Tokyo for many years and have experienced the four seasons here over the entire time. However, I have sometimes noticed differences between the current seasons and those I remember when growing up. The past winters were colder compared with those more recently, and current summer days are hotter than those of previous summers. Therefore, I collected Tokyo temperature data and created a program that allowed me to map the data in my artwork using colored dots. In the completed work, warm days were expressed in orange, while cold days were shown in blue. It quickly became clear that the more recent lengths of orange-colored dot patterns expressing warm weather were longer than those showing past days, most likely because of global warming. Although I found this scientific proof of global warming by chance, I could feel the data visualization more empathetically when expressed in the form of an abstract painting.
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制作物のコンセプトを記載してください。（英語）
The purpose of this artwork was to visualize data related to natural phenomena via a generative algorithm. I was especially interested in the ways data visualization could express abstract patterns. Data related to natural phenomena are often complicated, but through the use of mining data, it is often possible to bring out their beautiful and straightforward characteristics. I decided to create “Tokyo” to show the city’s temperature changes from 1990 to 2017, and thus artistically display the effects of climate change via data visualization. I have lived in Tokyo for many years and have experienced the four seasons here over the entire time. However, I have sometimes noticed differences between the current seasons and those I remember when growing up. The past winters were colder compared with those more recently, and current summer days are hotter than those of previous summers. Therefore, I collected Tokyo temperature data and created a program that allowed me to map the data in my artwork using colored dots. In the completed work, warm days were expressed in orange, while cold days were shown in blue. It quickly became clear that the more recent lengths of orange-colored dot patterns expressing warm weather were longer than those showing past days, most likely because of global warming. Although I found this scientific proof of global warming by chance, I could feel the data visualization more empathetically when expressed in the form of an abstract painting.
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作品の素材・仕様
A4 size, processing
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作品の素材・仕様（英語）
A4 size, processing
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作品のリファレンスURL
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作品の映像URL
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公式サイト、もしくはSNSのURL
http://yinteraction-design.com/datavisualization3/
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プロフィール情報
Takuya Yamauchi (Software Developer, Media Artist, Interaction Designer and UX Designer) Ph.D, Graduate School of Media and Governance, Keio University (2009)
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参加メンバー
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居住国
日本
- 23
Tokyo
その他
(Exhibition) The artwork was accepted for SIGGRAPH ASIA2020 Art Gallery
“Tokyo” is a generative artwork created by visualizing continuous recorded Tokyo temperature data obtained from the Japan Meteorological Agency from 1990 to 2017, and then printing out the result in a creative manner. The colored dots in the artwork reflect the temperature of each day. Cold days were colored in blue while warm days were displayed in orange. There are two primary reasons for using natural phenomena, such as temperature data in generative art creation. First, the data allows us to embrace and comprehend the unpredictability of natural phenomena. Second, when used with a generative algorithm, it makes possible data visualization in ways that allow us to create abstract art. Since there are massive amounts of historical temperature data, such artwork would be impossible to create without computers. Simple patterns like noise are not always random and often contain repeating patterns that can be expressed harmoniously. The seeming randomness of dots showing temperature distributions of hot summer days can be painted as patterns that result in abstract artwork. When applied to Tokyo temperature data, the stain-like patterns that resulted are among the most attractive characteristics of generative art painting and would be difficult to express without the generative algorithm.
“Tokyo” is a generative artwork created by visualizing continuous recorded Tokyo temperature data obtained from the Japan Meteorological Agency from 1990 to 2017, and then printing out the result in a creative manner. The colored dots in the artwork reflect the temperature of each day. Cold days were colored in blue while warm days were displayed in orange. There are two primary reasons for using natural phenomena, such as temperature data in generative art creation. First, the data allows us to embrace and comprehend the unpredictability of natural phenomena. Second, when used with a generative algorithm, it makes possible data visualization in ways that allow us to create abstract art. Since there are massive amounts of historical temperature data, such artwork would be impossible to create without computers. Simple patterns like noise are not always random and often contain repeating patterns that can be expressed harmoniously. The seeming randomness of dots showing temperature distributions of hot summer days can be painted as patterns that result in abstract artwork. When applied to Tokyo temperature data, the stain-like patterns that resulted are among the most attractive characteristics of generative art painting and would be difficult to express without the generative algorithm.
