GMU:Data as Artistic Material: Difference between revisions

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Di, 09.15 -12.30
Di, 09.15 -12.30, DBL


First meeting Mo, 15.04. voraussichtlich um18:00 (to be confirmed) + Di 16.04. 09:15 - 12:30
First meeting Mo, 15.04. 18:00 (to be confirmed) + Di 16.04. 09:15 - 12:30


Juliane Götz, Sebastian Neitsch (Quadrature) mail[@]quadrature.co
Juliane Götz, Sebastian Neitsch (Quadrature) >>> mail[@]quadrature.co


See for English version bellow


Das Projekt widmet sich den verschiedenen Arten von Daten - privat, öffentlich, ökologisch, live, gespeichert, geheim, historisch, aktuell oder zukünftig -, die von Sensoren, Apps, Wissenschaft, Regierungen, Gesellschaften oder individuellen Erfahrungen stammen. Die Fülle der Daten lädt dazu ein, relevante Bits aus dem Haufen der Trivialitäten auszugraben und Muster und Erzählungen durch Zeit und Raum zu enthüllen. Im Gegensatz zur traditionellen akademischen Forschung zielt die künstlerische Forschung in diesem Projekt nicht darauf ab, eine einzige Wahrheit aufzudecken, sondern subjektive Erzählungen, spekulative Aussagen oder rein poetische Ansätze zu liefern: Daten als Dada; künstlerische Reflexion anstelle von klassischen Visualisierungen; Analyse von Datensettings anstelle von Datensätzen.


Der Kurs wird Diskussionen über verschiedene Daten und damit verbundene Kunstwerke beinhalten, wobei Technologie als ein Werkzeug zum Lesen und Schreiben von Realitäten betrachtet wird. Ziel ist es, die Zahlen, die die Welt um uns herum bietet, zu interpretieren, zu übersetzen und mit ihnen zu experimentieren - Datenkompetenz als neugieriger, kritischer und kreativer Umgang mit Daten.Letztlich ermutigt dieses Projekt die Studierenden, Daten als eine neue Art von Rohmaterial zu betrachten, das neue ästhetische Optionen, außergewöhnliche Einsichten und künstlerischen Ausdrucksmöglichkeiten bietet ( (und eine ganze Reihe von Problemen).
Es wird von den Teilnehmenden erwartet, dass sie in kleinen Teams ein selbst definiertes Kunstwerk konzipieren, entwickeln und realisieren.
Geplant ist eine Exkursion (voraussichtlich 30.05. - 02.06.), die den Studierenden Einblicke in das Leben als freischaffende:r Künstler:in und in deren natürlichen Lebensraum bietet.
Von den Studierenden wird die Fähigkeit und Bereitschaft erwartet, selbstorganisiert zu arbeiten und sich aktiv in den Diskurs des Moduls einzubringen.
== English version ==
The project recognizes the diverse forms of data – private, public, environmental, live, stored, secret, past, present, and future - sourced from sensors, apps, science, governments, societies, and personal experiences. The abundance of data invites us to excavate relevant bits from the trivia pile, unveiling patterns and narratives within time and space. Unlike traditional academic research, artistic research within this project aims not to uncover a single truth but to provide subjective narratives, speculative statements, or even purely poetic approaches: Data as Dada;  artistic reflection instead of standard visualisations; analysing data settings rather than data sets.
The project recognizes the diverse forms of data – private, public, environmental, live, stored, secret, past, present, and future - sourced from sensors, apps, science, governments, societies, and personal experiences. The abundance of data invites us to excavate relevant bits from the trivia pile, unveiling patterns and narratives within time and space. Unlike traditional academic research, artistic research within this project aims not to uncover a single truth but to provide subjective narratives, speculative statements, or even purely poetic approaches: Data as Dada;  artistic reflection instead of standard visualisations; analysing data settings rather than data sets.


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Ultimately, this project encourages students to consider data as a new type of raw material, offering new aesthetic opportunities, extraordinary insights, and artistic expression. Emphasizing collaborative work, participants are expected to work in small teams to conceptualise, develop and realise a self-defined artwork.
Ultimately, this project encourages students to consider data as a new type of raw material, offering new aesthetic opportunities, extraordinary insights, and artistic expression. Emphasizing collaborative work, participants are expected to work in small teams to conceptualise, develop and realise a self-defined artwork.


A field trip is planned (probably 30.05. - 02.06.), offering students insights into the life of freelance artists and their natural habitat.
A field trip is planned (probably 30.05. - 02.06.), offering students insights into the life of freelance artists and their natural habitat. Focus is on collaborative practice.  


Students are expected to be able and willing to work in a self-organised manner and to actively participate in the discourse of the module.
Students are expected to be able and willing to work in a self-organised manner and to actively participate in the discourse of the module.
[[Category:Syllabus]]
 
'''Important: '''If you are interested to work with A.I., please also choose the Fachmodul "Critique and (Artificial) Intelligence - Machine learning and critical theory" by Dr. Alexander König!
 
'''====== Some Books ======'''
John D. Kelleher, Brendan Tierney: Data Science, ISBN 978-0-262-53543-4
Catherine D'Ignazio, Lauren F. Klein: Data Feminism, ISBN 978-0-262-54718-5
Christoph Grünberger: The Age of Data
Luci Pangrazio, Neil Selwyn: Critical Data Literacies
Thomas Piketty: Eine kurze Geschichte der Gleichheit
 
'''====== Some Artists / Artworks ======'''
[https://simonweckert.com/nullisland.html Simon Weckert]
[http://annaridler.com/myriad-tulips]
[https://driesdepoorter.be/thefollower/]
https://www.ryojiikeda.com/project/datamatics/
https://refikanadol.com/works/unsupervised/
https://mimionuoha.com/the-library-of-missing-datasets
https://deweyhagborg.com/projects/probably-chelsea
https://wwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwww.bitnik.org/1-star
http://peripheriques.free.fr/blog/index.php?/works/2016-blacklists/
https://disnovation.org/bestiary_exhibit.php
https://www.cyborgarts.com/moon-ribas
https://www.daisyginsberg.com/work/pollinator-pathmaker
https://www.marcobarotti.com/Corals
https://semiconductorfilms.com/art/20hz/
http://rayzhekov.com/projects/fragile-perspectives/

Revision as of 16:51, 6 April 2024

Di, 09.15 -12.30, DBL

First meeting Mo, 15.04. 18:00 (to be confirmed) + Di 16.04. 09:15 - 12:30

Juliane Götz, Sebastian Neitsch (Quadrature) >>> mail[@]quadrature.co


The project recognizes the diverse forms of data – private, public, environmental, live, stored, secret, past, present, and future - sourced from sensors, apps, science, governments, societies, and personal experiences. The abundance of data invites us to excavate relevant bits from the trivia pile, unveiling patterns and narratives within time and space. Unlike traditional academic research, artistic research within this project aims not to uncover a single truth but to provide subjective narratives, speculative statements, or even purely poetic approaches: Data as Dada;  artistic reflection instead of standard visualisations; analysing data settings rather than data sets.

The project will involve discussions on various data and related artworks, viewing technology as a tool to read and write realities. The objective is to interpret, translate, and experiment with the numbers offered by the world around us – a practice of data literacy: curious, competent, critical, and creative approaches to data.

Ultimately, this project encourages students to consider data as a new type of raw material, offering new aesthetic opportunities, extraordinary insights, and artistic expression. Emphasizing collaborative work, participants are expected to work in small teams to conceptualise, develop and realise a self-defined artwork.

A field trip is planned (probably 30.05. - 02.06.), offering students insights into the life of freelance artists and their natural habitat. Focus is on collaborative practice.

Students are expected to be able and willing to work in a self-organised manner and to actively participate in the discourse of the module.

Important: If you are interested to work with A.I., please also choose the Fachmodul "Critique and (Artificial) Intelligence - Machine learning and critical theory" by Dr. Alexander König!

====== Some Books ====== John D. Kelleher, Brendan Tierney: Data Science, ISBN 978-0-262-53543-4 Catherine D'Ignazio, Lauren F. Klein: Data Feminism, ISBN 978-0-262-54718-5 Christoph Grünberger: The Age of Data Luci Pangrazio, Neil Selwyn: Critical Data Literacies Thomas Piketty: Eine kurze Geschichte der Gleichheit

====== Some Artists / Artworks ====== Simon Weckert [1] [2] https://www.ryojiikeda.com/project/datamatics/ https://refikanadol.com/works/unsupervised/ https://mimionuoha.com/the-library-of-missing-datasets https://deweyhagborg.com/projects/probably-chelsea https://wwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwww.bitnik.org/1-star http://peripheriques.free.fr/blog/index.php?/works/2016-blacklists/ https://disnovation.org/bestiary_exhibit.php https://www.cyborgarts.com/moon-ribas https://www.daisyginsberg.com/work/pollinator-pathmaker https://www.marcobarotti.com/Corals https://semiconductorfilms.com/art/20hz/ http://rayzhekov.com/projects/fragile-perspectives/