Architectonic Studies of Radio Signals: Reorganizing Archives of Data/Natures In Their Own Terms
Loading...
Files
[pdf slides of the presentation]
[keynote slides of the presentation]
Authors
Author (Corporation)
Publication date
18.08.2020
Typ of student thesis
Course of study
Type
06 - Presentation
Editors
Editor (Corporation)
Supervisor
Parent work
Special issue
DOI of the original publication
Series
Series number
Volume
Issue / Number
Pages / Duration
Patent number
Publisher / Publishing institution
Place of publication / Event location
Prague
Edition
Version
Programming language
Assignee
Practice partner / Client
Abstract
As we slowly accustom to thinking about planetary issues through the notion of ‘assemblage’ rather than that of the ‘system’, we get better at acknowledging complex entanglements between living and inert, between social and technical. This paper presents a critical reflection on the use of machine learning techniques to support reasoning about natural phenomena. It engages data/natures by focusing on data radio signals: a phenomenon that pertains to both culture (telecommunications) and nature (atmospheric lightning discharges). Signal Identification Guide Wiki, a rich archive of signals observed and documented by a community of radio enthusiasts is the starting point of this study. In order to articulate alternative ways to study and engage with radio signals, I develop 'digital observatories': new methods for organizing and navigating abundant digital information based on critical use of self-organising map algorithm. I present a study of distribution patterns and clustering of signal qualities, when signals are reduced to spectrograms (visual representation of signal frequency composition). This 'digital observatory' aims to facilitate speculation on the connection between signal representation and technical communication protocols, by enabling the observer to identify criteria of similarity, and intervene in this organised space by adding new (real or imaginary) data. The project contributes to the fields of STS and experimental design research with an interest in the digital, unsettling the dichotomies previously described and providing avenues for recognition of the entangled nature of matter and information, of human and other-than-human, beyond simple ontological distinctions.
Keywords
radio, machine learning, nature/culture, data/nature, data, digital observatory
Subject (DDC)
Event
EASST/4S CONFERENCE Locating and Timing Matters: Significance and Agency of STS in Emerging Worlds
Exhibition start date
Exhibition end date
Conference start date
Conference end date
Date of the last check
ISBN
ISSN
Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Published
Review
Peer review of the abstract
Open access category
Citation
SAVIC, Selena, 2020. Architectonic Studies of Radio Signals: Reorganizing Archives of Data/Natures In Their Own Terms. EASST/4S CONFERENCE Locating and Timing Matters: Significance and Agency of STS in Emerging Worlds. Prague. 18 August 2020. Verfügbar unter: https://doi.org/10.26041/fhnw-3546