Data Art & Science Project 2023

Datasets:

Health Care System (all available OECD data from all available countries)

Chapter 1:

• Waiting times for operations (https://stats.oecd.org/ Health > Healthcare Utilisation > Waiting Times)

Chapter 2:

• Perceived status by socio-economic status – Good/very good health, income quintile 1 (lowest) compared to income quintile 5 (highest) (https://stats.oecd.org/ Health > Health Status > Perceived health status by socio-economic status)
• Health expenditure and financing – all providers – per capita, current prices, current PPPs (Purchasing Power Parity) (https://stats.oecd.org/ Health > Health expenditure and financing)

Chapter 3:

• Pharmaceutical consumption – defined daily dosage per 1000 inhabitants per day (https://stats.oecd.org/ Health > Pharmaceutical consumption)
• Pharmaceutical sales – Million US at exchange rate 8 (https://stats.oecd.org/ Health > Pharmaceutical sales)

Legend:

1. Chapter: Health Care Utilisation

Waiting times of patients for operations in mean days, sorted by year by country Visual: waiting time / year / country as loading bar, all countries per year at once Sound: duration of waiting time

2. Chapter: Health Status & expenditure

A) Perceived health status by socio-economic status, sorted by year by country Variable: Good/very good health, total aged 15+, Income quintile 1 (lowest) AND

Variable: Good/very good health, total aged 15+, Income quintile 5 (highest) Measure: % of population

Visual:

• Quintile 1 compared to Quintile 5 as white bars on pill
• ratio between Quintile 1 and Quintile 5 defines tilt of pills

Sound:

• white noise filtered depending on perceived health (Quintile 5 high value > high sound, Quintile 1 perceives very good health > low sounds)
• sine wave repeating same pattern

B) Health expenditure and financing, sorted by year by country:

Financing scheme: All financing schemes Function: Current expenditure on health (all functions) Health Care Provider: All providers Measure: Per capita, current prices, current PPPs Visual: amount of expenditure defines amount of pills Sound: expenditure defines gain (volume)

3. Chapter: Pharmaceutical Market A) Pharmaceutical consumption, all available drugs, per year per country Measure – Defined daily dosage per 1000 inhabitants per day

Visual:

• type of drug defines colour of pill
• all consumed pills (defined daily dosage) stay visible – ending with all consumed pills of all available drugs in all available countries over the years Auditive representation: one defined tone per country

B) Total Pharmaceutical sales, per year per country Measure: Million US at exchange rate Visual: number of sales defines rhythm/visibility Sound: expenditure defines gain (volume) and reverb

Dataset:

Our World in Data: Optimism & Pessimism, https://ourworldindata.org/optimism-and-pessimism

Artist Statement: “First, I visited the “Our World in Data” website and realized that there was a difference between my personal experience and the world represented by the data. We are optimistic or pessimistic about the future, depending on how far the topic is from a personal area. And those biases change behaviour and change the future.

Before diving into the data and painting, I started moving my body, creating physical phenomena as a painter, and then aiming to discover some properties/characteristics. The bubbles in the painting will always break. However, bubbles also appear in our daily life as circles.

While observing elements from the chaos, If I find something in my work that “is an irreplaceable individual, yet also has universality in the multitude.” I think it can, regardless of the specific topic, become “My personal story and the story of all of us,” living beside optimistic/pessimistic perspectives together.”

Legend:

“I didn’t directly connect data with visuals, so extracting the elements from reality was crucial. One day, my friend made jelly and sent me a photo of how lovely it was. The shapes of the bubbles that emerged in the thickening were stable and suitable to observe. I was convinced that it would be fit for this project.

The collaboration with Mika. She usually has a more powerful touch while playing piano, but the song was so gentle, and she told me a beautiful secret: She played the piano in the morning, and her husband was still asleep then, so the melody was subconsciously gentle. The tone contains information about the relationship between her and her love.

When I started working with data, I noticed that I was somewhere in the graph and trying to separate myself into pieces #tags of information. But, in this work, we mixed several aspects of ourselves, such as ” Akiko the painter / Akiko talking about jelly with a friend” and “Mika the pianist / Mika in her life with her partner.”. In the artwork, some figures are created by interacting with several things, such as the borderline created by the contrasting spread of two different types of paint and the relationship of gravity. In this way, I thought it was important for the visuals to express information that the natures are related to each other.”

Credits:

Piano: Mika Kawada

Dataset:

TU Graz, Institute of Electronica Sensor Systems: Project CARES (City Air Remote Emission Sensing)

Part 1: stations: Emission data from measuring stations in Prague, Brno, Krakow, Milano gathered over several days in 2021 and 2022.

Part2: chasing: Emission data from “plume chasing”, vehicles with measuring devices following other vehicles in city traffic in the Czech Republic in 2022.

Legend:

Part 1: stations

• Scene time is linearly mapped to the progression through the time of day, so that a full day is contained in the time for which the scene is visible
• Each measuring station becomes a visual tunnel, laid out next to each other; in a tunnel’s confines, data points from a particular day at the station are triggered as the time passes; each data point causes an event that

a) is marked by a frame that moves down the tunnel b) is annotated with anonymized vehicle data of the emission source c) triggers a burst of particle births in proportion to the concentration of nanoparticles in the vehicle exhaust

Part 2: chasing

• Geolocation- and timestamped exhaust data from several days is visualized in scene space
• The chasing sequences are built up after each other, in linear time with respect to data point index
• For each n-th data point, a particle is spawned that grows over time based on the concentration of nanoparticles in the vehicle exhaust

Both parts look specifically at nanoparticles from 23nm (smallest size that can be reliably measured with current instruments) to 300nm contained in vehicle exhaust.

Credits:

Emission Data: Alexander Bergmann, Markus Knoll; Graz University of Technology Institute of Electrical Measurement and Sensor Systems Denis Pöhler; Airyx GmbH Ake Sjödin; Swedish Environmental Research Institute Project: CARES – City Air Remote Emission Sensing

City Map Data: © Mapbox, © OpenStreetMaps

Datasets:

Glacier text: IPCC (The Intergovernmental Panel on Climate Change) Ocean tide: OFES (Ocean General Circulation Model for the Earth Simulator) dataset by JAMSTEC

Legend:

• Regarding the IPCC report, the artist decided to use the text itself as a graphics element.
• By applying fluid simulation to a uniformly displayed string of text, the team aimed to achieve complex text animation and provide an emotional experience for the viewer.
• For example, the words “Capitalism” and “Temperature” rise, thereby melting the glaciers in the string.
• The other data, the OFES dataset, is ocean current data simulated by a supercomputer. The team extracted the flow of the ocean near Japan and realized a large-scale visualization in 8K.
• In all scenes, the visualization was smartly done in a scientifically correct manner at first, but gradually, creative deviations were made in the data, parameters were extended to improbable levels, and errors in the simulation were converted directly into the representation.
• The team mixed scenes based on original physical/chemical mathematical models with scenes based on data.

Credits:

Artist: Akira Wakita Software: Yuki Kuwashima, Yuta Morofuji Sound: Kairi Haruna Research: Yoshinori Shibahara,Kazuki Nagata, Taisho Nishihara Technical support: ASTRODESIGN INC., Masaki Yamabe

Legend:

Sound:

• For the sound experience, original Whinchat and harvester recordings were used to create the auditive narrative.
• Digital archives of bird songs already showcase songs of birds that have already grown extinct – and will even more do in the in the future, thus forming a natural heritage one can turn to, when the world falls silent.
• The composition follows a data driven score that reacts to the decline in population numbers with the polyphonic amount and dynamic.
• The decreased whinchat population of the used data set shows off in the decreasing amount of bird recordings within the auditive experience.
• The sounds were deformed by modular system components to simulate the process of increasing disappearance of the bird population through technology

Visual:

• The Whinchat was chosen as representative species of birds which according to BirdLife reports an acutely endangered bird species in the upper Austrian rural area.
• Light effects are directly related to the audio data.
• By deforming and displacing RGB values from an actual whinchat photography, the bird becomes a digital metaphor for an agricultural landscape.