The HUMANE typology and method – supporting the analysis and design of human-machine networks
The HUMANE typology and method – supporting the analysis and design of human-machine networks
This white paper presents the HUMANE typology and method, intended to support the analysis and design for human-machine networks (HMN). The typology serves to characterise HMNs on dimensions pertaining to the actors of the network, the relations between the actors, network extent and network structure. The method supports profiling HMNs along these dimensions, to analyse implications of the network characteristics, identify similar networks, and enable the transfer of design knowledge and experience in the form of design patterns. The application of the typology and method is exemplified a summary presentations of one of the HUMANE case studies (eVACUATE).
white paper
Engen, Vegard
5ab4f73a-6cb5-4a58-9d89-ebced3182962
Folstad, Asbjorn
bb1a064c-e005-436b-878c-6bd6e41c172e
13 June 2017
Engen, Vegard
5ab4f73a-6cb5-4a58-9d89-ebced3182962
Folstad, Asbjorn
bb1a064c-e005-436b-878c-6bd6e41c172e
Engen, Vegard and Folstad, Asbjorn
(eds.)
(2017)
The HUMANE typology and method – supporting the analysis and design of human-machine networks
HUMANE 2020
Record type:
Monograph
(Project Report)
Abstract
This white paper presents the HUMANE typology and method, intended to support the analysis and design for human-machine networks (HMN). The typology serves to characterise HMNs on dimensions pertaining to the actors of the network, the relations between the actors, network extent and network structure. The method supports profiling HMNs along these dimensions, to analyse implications of the network characteristics, identify similar networks, and enable the transfer of design knowledge and experience in the form of design patterns. The application of the typology and method is exemplified a summary presentations of one of the HUMANE case studies (eVACUATE).
Text
The HUMANE typology and method – supporting the analysis and design of human-machine networks
More information
Accepted/In Press date: 1 June 2017
Published date: 13 June 2017
Keywords:
white paper
Identifiers
Local EPrints ID: 412958
URI: http://eprints.soton.ac.uk/id/eprint/412958
PURE UUID: 0b9de1c0-672b-4483-8676-353c41ec6632
Catalogue record
Date deposited: 10 Aug 2017 16:30
Last modified: 15 Mar 2024 15:37
Export record
Contributors
Editor:
Vegard Engen
Editor:
Asbjorn Folstad
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics