Making local knowledge matter: Exploring the appropriateness of pictorial decision trees as interaction style for non-literate communities to capture their traditional ecological knowledge

Sustainable natural resource management is one of the fundamental development challenges humanity faces today. The scale of the issues involved and the inadequacy of existing paradigms mean that there is an urgent need for innovative and appropriate solutions to enable scientifically-informed sustainable resource management of key environments. Local and indigenous communities often possess unique Traditional Ecological Knowledge (TEK) about their natural resources, which despite being increasingly recognised as critical for sustaining and protecting the environment, it is difficult to capture in a digital format, in particular given the environment in which many communities live and their lack of technical knowledge. Yet, their knowledge is required in digital form to reach a wide audience and particularly those stakeholders who need to base their decisions on the knowledge provided. This thesis draws knowledge from Human-Computer Interaction (HCI), HCI for Development (HCI4D), Software Engineering, Information and Communications Technologies for Development (ICT4D), Participatory Geographic Information Systems (PGIS) and Citizen Science to develop and evaluate methods and Information and Communications Technology (ICT) tools to enable communities to capture and share their local environmental conditions, information that can in turn lead to improvements in environmental governance and social-environmental justice. One core challenge in this endeavour is to enable lay users, especially those with limited technical skills or no prior exposure to technology and no (or basic) literacy or no formal education, to use smartphones to capture their TEK and share data with relevant stakeholders. To achieve that, this thesis explores whether pictorial decision trees are appropriate as an interaction mode for non-literate participants to capture geographical data. In the context of three case studies, taking place in Republic of the Congo and focusing on enabling local communities to participate in socio-environmental monitoring schemes regarding their forest, this thesis explores the opportunities and challenges in collaboratively developing software to realise this vision. The research findings and the methodological framework provide an approach and guidelines for the development and evaluation of ICT solutions in similar, challenging vii environments. The most significant finding of the thesis is that while pictographs are easily understood by participants, when employed in pictorial decision trees they proved to be challenging for them due to the categorisation and hierarchical structure of decision trees. Alternatively, interaction modes that employ audio or physical interfaces can alleviate these issues and assist participants to collect geographical data. This thesis also demonstrates how a participatory and iterative design approach led to the conception and evaluation of interaction modes that increase participants’ accuracy from 75% towards 95% and improve participants’ satisfaction, which could in turn increase the sustainability of the project. Finally, a number of methodological approaches were evaluated and amended in order to design and evaluate ICT solutions with non-literate, forest communities

Quantifying Quality of Life

Describes technological methods and tools for objective and quantitative assessment of QoL Appraises technology-enabled methods for incorporating QoL measurements in medicine Highlights the success factors for adoption and scaling of technology-enabled methods This open access book presents the rise of technology-enabled methods and tools for objective, quantitative assessment of Quality of Life (QoL), while following the WHOQOL model. It is an in-depth resource describing and examining state-of-the-art, minimally obtrusive, ubiquitous technologies. Highlighting the required factors for adoption and scaling of technology-enabled methods and tools for QoL assessment, it also describes how these technologies can be leveraged for behavior change, disease prevention, health management and long-term QoL enhancement in populations at large. Quantifying Quality of Life: Incorporating Daily Life into Medicine fills a gap in the field of QoL by providing assessment methods, techniques and tools. These assessments differ from the current methods that are now mostly infrequent, subjective, qualitative, memory-based, context-poor and sparse. Therefore, it is an ideal resource for physicians, physicians in training, software and hardware developers, computer scientists, data scientists, behavioural scientists, entrepreneurs, healthcare leaders and administrators who are seeking an up-to-date resource on this subject

Quantifying Quality of Life

Describes technological methods and tools for objective and quantitative assessment of QoL Appraises technology-enabled methods for incorporating QoL measurements in medicine Highlights the success factors for adoption and scaling of technology-enabled methods This open access book presents the rise of technology-enabled methods and tools for objective, quantitative assessment of Quality of Life (QoL), while following the WHOQOL model. It is an in-depth resource describing and examining state-of-the-art, minimally obtrusive, ubiquitous technologies. Highlighting the required factors for adoption and scaling of technology-enabled methods and tools for QoL assessment, it also describes how these technologies can be leveraged for behavior change, disease prevention, health management and long-term QoL enhancement in populations at large. Quantifying Quality of Life: Incorporating Daily Life into Medicine fills a gap in the field of QoL by providing assessment methods, techniques and tools. These assessments differ from the current methods that are now mostly infrequent, subjective, qualitative, memory-based, context-poor and sparse. Therefore, it is an ideal resource for physicians, physicians in training, software and hardware developers, computer scientists, data scientists, behavioural scientists, entrepreneurs, healthcare leaders and administrators who are seeking an up-to-date resource on this subject