The University of Southampton
University of Southampton Institutional Repository

The DNA of Web Observatories

The DNA of Web Observatories
The DNA of Web Observatories
This thesis investigates the proposed Web Observatory (WO) which will offer access to globally shared data and apps,delivering insights into the nature of the Web and also society-on-the-Web. Understanding how different groups conceptualise and engage with WO concepts is vital to understanding the drivers for adoption and the requirements for adoption between groups.

Observations from the field and analysis of work relating to WOs are combined and compared with established theories of innovation and adoption. I argue that a purely technological definition of WO is necessary-but-not-sufficient to capture the set of complex interactions and interests that a network of Observatories at Web scale would need to reflect.

A new socio-technical 'DNA' model of Web Observatories is developed combining technical and architectural definitions (D factors) with socially-embedded narratives (N factors) and group perspectives and motivations (A factors) .Visual model of D's, N's and A's and a new perspective on parallel modelling for technically- vs socially constructed models is introduced .

An inductive approach, which combines case studies, content analysis and extensive interviews/ observations blends data from a broad range of sources across academia, business and government. A new WO taxonomy is established and iterative analysis refines a multi-perspective model of WOs
employing a constructivist grounded theory (CGT) lens. An approach combining Interpretative Phenomenological Analysis (IPA) and visual mapping techniques using a hybrid concept mapping/TRIZ approach is developed to model the findings.

Social theories are considered around individual/shared meanings to enable a definition of WO to be embedded (framed) within the social context of the individuals and groups who seek to use WO to address specific problems and outcomes.

This thesis has implications for how new Observatories may be designed and built and also for how existing systems and sources may be recruited into a global Observatory eco-system through a better understanding not only of how participants may join but also, critically, why they would choose to
do so. The models/techniques developed here may find a wider application for the study of socio-technical systems and social machines.
University of Southampton
Brown, Ian C.
555fc78f-5a85-400e-821d-a6d0594583c8
Brown, Ian C.
555fc78f-5a85-400e-821d-a6d0594583c8
Hall, Wendy
11f7f8db-854c-4481-b1ae-721a51d8790c

Brown, Ian C. (2017) The DNA of Web Observatories. University of Southampton, Doctoral Thesis, 425pp.

Record type: Thesis (Doctoral)

Abstract

This thesis investigates the proposed Web Observatory (WO) which will offer access to globally shared data and apps,delivering insights into the nature of the Web and also society-on-the-Web. Understanding how different groups conceptualise and engage with WO concepts is vital to understanding the drivers for adoption and the requirements for adoption between groups.

Observations from the field and analysis of work relating to WOs are combined and compared with established theories of innovation and adoption. I argue that a purely technological definition of WO is necessary-but-not-sufficient to capture the set of complex interactions and interests that a network of Observatories at Web scale would need to reflect.

A new socio-technical 'DNA' model of Web Observatories is developed combining technical and architectural definitions (D factors) with socially-embedded narratives (N factors) and group perspectives and motivations (A factors) .Visual model of D's, N's and A's and a new perspective on parallel modelling for technically- vs socially constructed models is introduced .

An inductive approach, which combines case studies, content analysis and extensive interviews/ observations blends data from a broad range of sources across academia, business and government. A new WO taxonomy is established and iterative analysis refines a multi-perspective model of WOs
employing a constructivist grounded theory (CGT) lens. An approach combining Interpretative Phenomenological Analysis (IPA) and visual mapping techniques using a hybrid concept mapping/TRIZ approach is developed to model the findings.

Social theories are considered around individual/shared meanings to enable a definition of WO to be embedded (framed) within the social context of the individuals and groups who seek to use WO to address specific problems and outcomes.

This thesis has implications for how new Observatories may be designed and built and also for how existing systems and sources may be recruited into a global Observatory eco-system through a better understanding not only of how participants may join but also, critically, why they would choose to
do so. The models/techniques developed here may find a wider application for the study of socio-technical systems and social machines.

Text
final thesis - Version of Record
Available under License University of Southampton Thesis Licence.
Download (16MB)

More information

Published date: 2017

Identifiers

Local EPrints ID: 415346
URI: http://eprints.soton.ac.uk/id/eprint/415346
PURE UUID: daace221-9d1f-42a2-bfe5-998b4e57b10a
ORCID for Ian C. Brown: ORCID iD orcid.org/0000-0003-4705-7015
ORCID for Wendy Hall: ORCID iD orcid.org/0000-0003-4327-7811

Catalogue record

Date deposited: 07 Nov 2017 17:30
Last modified: 16 Mar 2024 02:33

Export record

Contributors

Author: Ian C. Brown ORCID iD
Thesis advisor: Wendy Hall ORCID iD

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

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×