Bastian Greshake Tzovaras’s research while affiliated with The Alan Turing Institute and other places

This chapter outlines new methods with which to understand an autistic ‘phenomenology’ which is representative of the diversity of autistic people. A neurodiverse research team works in co-production. Diverse autistic (and some comparator non-autistic) individuals undertake individual interviews using Interpretative Phenomenological Analysis, to understand their experiences at depth. Themes are in parallel explored at breadth using a citizen science digital platform, allowing contributions on experience from a wide range of autistic (and some non-autistic) people. Further methods to reach those with different (often non-verbal) expressive ability use innovative participatory practices including immersive multisensory environments, with neuroscience tools capturing engagement, attention and response. This interdisciplinary method allows identification of common elements of experiences, including those with complex communication needs or intellectual disabilities. It empirically generates for the first time a shared, autistic phenomenology—with benefits, including: (i) shared understanding through mutual empathy and common language between professionals and the autistic community; (ii) new foci for scientific research through aspects of autistic experience previously neglected; (iii) added richness and utility for clinical phenotyping and diagnostic definitions; and (iv) helping identify new care pathways and supportive innovations for health care and education.

Even though citizen and patient engagement in health research has a long tradition, citizen science in health has only recently gained attention and recognition. However, at present, there is no clear overview of the specifics and challenges of citizen science initiatives in the health domain. Such an overview could contribute to highlighting and articulating the different needs of stakeholders engaged in any form of citizen science in the health domain. It may also encourage the input of citizens and patients alike in health research and innovation, policy, and practice. This paper reports on a survey developed by the European Citizen Science Association (ECSA)’s Working Group “Citizen Science for Health,” to highlight the perceived characteristics and enabling factors of citizen science in the health domain, and to formulate a direction for future work and research. The survey was available in six languages and was open between January and August 2022. The majority of the 254 respondents were from European countries, and the largest stakeholder respondent group was researchers. Respondents were asked about their perspectives on the particular characteristics of citizen science performed in health and biomedical research, as well as the challenges and opportunities it affords. Ethics, the complexity of the health domain, and the overlap in roles whereby the researcher is sometimes also the subject of research, were the main issues suggested as being specific to citizen science in health. The top two areas that respondents identified as in need of development were “balanced return on investment” and “ethics.” This publication discusses these and other conditions with references to current literature.

Personal science is the practice of addressing personally relevant health questions through self-research. Implementing personal science can be challenging, owing to the need to develop and adopt research protocols, tools and methods. While online communities can provide valuable peer support, tools for systematically accessing community knowledge are lacking. The objective of this study is to apply a participatory design process involving a community of personal science practitioners to develop a peer-produced knowledge base that supports the needs of practitioners as consumers and contributors of knowledge. The process led to the development of the Personal Science Wiki, an open repository for documenting and accessing individual self-tracking projects while facilitating the establishment of consensus knowledge. After initial design iterations and a field testing phase, we performed a user study with 21 participants to test and improve the platform, and to explore suitable information architectures. The study deepened our understanding of barriers to scaling the personal science community, established an infrastructure for knowledge management actively used by the community and provided lessons on challenges, information needs, representations and architectures to support individuals with their personal health inquiries.

The moderation of user-generated content on online platforms remains a key solution to protecting people online, but also remains a perpetual challenge as the appropriateness of content moderation guidelines depends on the online community that they aim to govern. This challenge affects marginalized groups in particular, as they more frequently experience online abuse but also end up falsely being the target of content-moderation guidelines. While there have been calls for democratic, community-moderation, there has so far been little research into how to implement such approaches. Here, we present the co-creation of content moderation strategies with the users of an online platform to address some of these challenges. Within the context of AutSPACEs—an online citizen science platform that aims to allow autistic people to share their own sensory processing experiences publicly—we used a community-based and participatory approach to co-design a content moderation solution that would fit the preferences, priorities, and needs of its autistic user community. We outline how this approach helped us discover context-specific moderation dilemmas around participant safety and well-being and how we addressed those. These trade-offs have resulted in a moderation design that differs from more general social networks in aspects such as how to contribute, when to moderate, and what to moderate. While these dilemmas, processes, and solutions are specific to the context of AutSPACEs, we highlight how the co-design approach itself could be applied and useful for other communities to uncover challenges and help other online spaces to embed safety and empowerment.

More than ever, humanity relies on robust scientific knowledge of the world and our place within it. Unfortunately, our contemporary view of science is still suffused with outdated ideas about scientific knowledge production based on a naive kind of realism. These ideas persist among members of the public and scientists alike. They contribute to an ultra-competitive system of academic research, which sacrifices long-term productivity through an excessive obsession with short-term efficiency. Efforts to diversify this system come from a movement called democratic citizen science, which can serve as a model for scientific inquiry in general. Democratic citizen science requires an alternative theory of knowledge with a focus on the role that diversity plays in the process of discovery. Here, we present such an epistemology, based on three central philosophical pillars: perspectival realism, a naturalistic process-based epistemology, and deliberative social practices. They broaden our focus from immediate research outcomes towards cognitive and social processes which facilitate sustainable long-term productivity and scientific innovation. This marks a shift from an industrial to an ecological vision of how scientific research should be done, and how it should be assessed. At the core of this vision are research communities that are diverse, representative, and democratic.

The moderation of user-generated content on online platforms remains a key solution to protecting people online, but also remains a perpetual challenge as the appropriateness of content moderation guidelines depends on the online community that they aim to govern. This challenge affects marginalised groups in particular, as they more frequently experience online abuse but also end up falsely being the target of content-moderation guidelines. While there have been calls for democratic, community-moderation, there has so far been little research into how to implement such approaches. Here, we present the co-creation of content moderation strategies with the users of an online platform to address some of these challenges. Within the context of AutSPACEs – an online citizen science platform that aims to allow autistic people to share their own sensory processing experiences publicly – we used a community-based and participatory approach to co-design a content moderation solution that would fit the preferences, priorities and needs of its autistic user community. We outline how this approach helped us discover context-specific moderation dilemmas around participant safety and wellbeing and how we addressed those. These trade-offs have resulted in a moderation design that differs from more general social networks in aspects such as how to contribute, when to moderate, and what to moderate. While these dilemmas, processes and solutions are specific to the context of AutSPACEs, we highlight how the co-design approach itself could be applied and useful for other communities to uncover challenges and help other online spaces to embed safety and empowerment.

Resource allocation is essential to the selection and implementation of innovative projects in science and technology. With large stakes involved in concentrating large fundings over a few promising projects, current “winner-take-all” models for grant applications are time-intensive endeavours that mobilise significant researcher time in writing extensive project proposals, and rely on the availability of a few time-saturated volunteer experts. Such processes usually carry over several months, resulting in high effective costs compared to expected benefits. Faced with the need for a rapid response to the COVID-19 pandemic in 2020, we devised an agile “community review” system, similar to distributed peer review (DPR) systems, to allocate micro-grants for the fast prototyping of innovative solutions. Here we describe and evaluate the implementation of this community review across 147 projects from the “Just One Giant Lab’s OpenCOVID19 initiative” and “Helpful Engineering” open research communities. The community review process uses granular review forms and requires the participation of grant applicants in the review process. We show that this system is fast, with a median duration of 10 days, scalable, with a median of 4 reviewers per project independent of the total number of projects, and fair, with project rankings highly preserved after the synthetic removal of reviewers. We investigate potential bias introduced by involving applicants in the process, and find that review scores from both applicants and non-applicants have a similar correlation of r=0.28 with other reviews within a project, matching previous observations using traditional approaches. Finally, we find that the ability of projects to apply to several rounds allows to both foster the further implementation of successful early prototypes, as well as provide a pathway to constructively improve an initially failing proposal in an agile manner. This study quantitatively highlights the benefits of a frugal community review system for agile resource allocation.

In this article we present a “methodological assemblage” and technological prototype connecting autoethnography to the practices of self-research in personal science. As an experimental process of personal data gathering, one of the authors used a low-tech device for the active registration of events and their perception, in a case study on disengaging from his smartphone. For the visualization of this data the other author developed a novel treatment of fieldnotes in analytic autoethnography through an open source, interactive notebook. As a proof of concept, we provide a detailed description of the corresponding protocol and prototype, also making available the notebook source code and the quantitative-qualitative open dataset behind its visualization. This highly personalized methodological assemblage represents a technological appropriation that combines self-research and autoethnography—two disciplinary perspectives that share a type of inquiry based on situated knowledge, departing from personal data as empirical basis. Despite recent autoethnographic literature on the phenomenon of self-tracking and the Qualified Self, our contribution addresses a lack of studies in the opposite direction: how the practice of self-research mediated by technology can lead to bridges with digital autoethnography, validating their hybrid combination. After addressing diverse conceptual, ontological and methodological similarities and differences between personal science and autoethnography, we contextualize the case study of digital disengagement and provide a detailed description of the developed self-protocol and the tools used for data gathering.