Wikis as collaborative knowledge management tools in socio-environmental modelling studies. (December 2022)

• Record Type: Journal Article
• Authors: Roxburgh, Nicholas; Stringer, Lindsay C.; Evans, Andrew J.; Williams, Tim G.; Müller, Birgit
• Is Part Of: Environmental modelling & software. Volume 158(2022)
• Publication Date: 2022-12
• Subjects: Wiki -- Participatory research -- Fieldwork -- Data management -- Open data -- Knowledge reuse; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2022.105538
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: The data requirements of many socio-environmental system (SES) modelling studies have increased substantially in recent years. This has made the already challenging task of data compilation, retrieval, and sharing progressively more difficult. Recognising the current lack of best practice for knowledge management in SES modelling studies, we propose using SES wikis as a means of addressing these challenges. Wikis have attributes that make them well suited to complex knowledge management tasks and their hierarchical, interconnected, algorithmic logic closely fits with the logic needed in SES model design. In this article, we describe how wikis can be used at each stage of the SES modelling cycle, and we discuss our experiences of putting the approach into practice. We conclude that while SES wikis can be time consuming to initially develop, they have the potential to significantly improve the quality, transparency, and efficiency of SES modelling projects. Highlights: SES modelling lacks established guidance for collaborative knowledge management. Wikis are a promising approach to integrate knowledge on interconnected subjects. We share experiences of utilising the wiki method in the development of an ABM. We offer guidance for SES modellers to leverage wikis within the modelling cycle.