Luna Nane, Isa Teichmann: Art Doc Viz – Interactive Visualization of Artist Documentation

ArtDocViz

Abstract

Over the past two decades, digital archiving and building interfaces to access digital archives has been a major challenge at the intersection of computer sciences, arts and humanities. In our project, we approach social media data and website data from artists as a way of self-documentation that we want to archive and bring in context. In this text, we outline the making of Art Doc Viz, an interactive visualization that builds on an open source and machine-learning-based data pipeline designed to bring arbitrary amounts of artists’ self-documented work from different sources (for example Instagram and websites) into a visualization structure that makes it accessible interactively and in 3D, and that makes relations between the artists’ documentations visible. This is achieved by using a series of AI tools like entity recognition and image recognition and UMAP as a clustering algorithm. Finally, the visualization uses advanced 3D graphics to enable the user to explore the visualization in an intuitive way.

Authors

Luna Nane is a trans*-identifying artist and creative technologist in the field of interactive media. Since 2011, she has been working freelance with creative technologies, interactive and media arts, data visualization, procedural generation and AI.

Isa Teichmann is a transfemme computer engineering student. She has a background in social studies. She works freelance as a speaker and educator for queer topics, and is also a research assistant and programmer. For this project she supported Luna Nane as a research assistant for the topics Named Entity Recognition and Image Classification.

Download: Luna Nane, Isa Teichmann: Art Doc Viz – Interactive Visualization of Artist Documentation

DOI: https://doi.org/10.5281/zenodo.8143784



Diesen Blogbeitrag zitieren
Lukas Fuchsgruber (2023, 8. Mai). Luna Nane, Isa Teichmann: Art Doc Viz – Interactive Visualization of Artist Documentation. Reclaim your archive. Abgerufen am 20. Mai 2024, von https://doi.org/10.58079/tded

Das könnte dich auch interessieren …

Schreibe einen Kommentar

Deine E-Mail-Adresse wird nicht veröffentlicht. Erforderliche Felder sind mit * markiert

Diese Website verwendet Akismet, um Spam zu reduzieren. Erfahre mehr darüber, wie deine Kommentardaten verarbeitet werden.

Suche in OpenEdition Search

Sie werden weitergeleitet zur OpenEdition Search