The Cybernetics Thought Collective: Machine-Generated Data Using Computational Methods

Research output: Contribution to journalArticlepeer-review

Abstract

This dataset comprises machine-generated data from the research records and personal archives of four founding members of the transdisciplinary field of cybernetics—W. Ross Ashby, Warren S. McCulloch, Heinz von Foerster, and Norbert Wiener. These archives (or, fonds) are held by the British Library, the American Philosophical Society, the University of Illinois at Urbana-Champaign, and MIT, respectively. The data were created for “The Cybernetics Thought Collective: A History of Science and Technology Portal Project” (2017–2019), a pilot project funded by the National Endowment for the Humanities (NEH). Using computational methods and tools—machine learning, named entity recognition, and natural language processing—on digitized archival records, the data were generated to enhance archival access in three distinct but interrelated ways: as archival metadata for the digitized records, as reusable data to facilitate digital scholarly analyses, and as the basis for a series of test visualizations. The data represent entities associated with cybernetic concepts and the main actors attached to the cybernetics movement and the exchange of its ideas. The dataset is stored along with the digitized records in the University of Illinois (U of I) Library’s multi-tiered repository, a replicated preservation service based on PREMIS (Preservation Metadata: Implementation Strategies). Reuse potential for this dataset includes historical/archival, linguistic, and artistic analyses of the data to examine connections between the cybernetic entities.
Original languageEnglish (US)
Pages (from-to)7
JournalJournal of Open Humanities Data
Volume6
Issue number1
DOIs
StatePublished - 2020

Keywords

  • Archive records
  • Social networks
  • Science and technology

Fingerprint

Dive into the research topics of 'The Cybernetics Thought Collective: Machine-Generated Data Using Computational Methods'. Together they form a unique fingerprint.

Cite this