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York University

How Software Transparency Can Mitigate Conflicts Among Different Stakeholders in the Animal Experimentation Domain

Abstract

dc:description.abstract

The arguments of whether animals should be used in the experiments have existed for decades. Stakeholders such as animal advocates, scientists, and mediators have been calling for more transparency to tackle the conflicts. They all claim that being transparent is a way to understand each other and to know the whole picture of the animal experiments. It is believed that laboratories software should provide aspects of transparency to help mitigate the conflicts among different stakeholders points of view. In this thesis, a Systematic Literature Review was conducted to collect requirements and potential solutions from the literature from the perspectives of different stakeholders and put them together in a set of softgoal interdependency graphs (SIGs) that illustrating the possible solutions to achieve transparency. The resulted SIGs may help the laboratories to adopt software that provides a level of transparency for the research process, and it will also help to mitigate current problems involving researchers, mediators, and groups contrary to the use of animals.

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Chen, Ren-Luen
Advisor dc:contributor.advisor
  • Cysneiros, Luiz Marcio

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • Author owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
Language dc:language
en

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/10315/37762
OAI identifier oai:identifier
oai:yorkspace.library.yorku.ca:10315/37762

Chain of custody

source
Harvested from
York University
Base URL
yorkspace.library.yorku.ca/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Chen, Ren-Luen. How Software Transparency Can Mitigate Conflicts Among Different Stakeholders in the Animal Experimentation Domain. 2020. http://hdl.handle.net/10315/37762