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# The Alan Turing Institute final report | ||
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12 September 2024 | ||
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This is the final report for AutSPACEs as a Turing funded project. | ||
It will contain main lessons and outputs to reflect the impact and facilitate the next phase. | ||
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The report aims to be concise and point towards further resources, reports and outputs that have been shared and published along the way. | ||
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## Contents | ||
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- [Project description & aims](#project-description-and-aims) | ||
- [Lessons learned](#-lessons-learned) | ||
- [Achievements](#achievements) | ||
- [Impact](#impact) | ||
- [Real world applications](#real-world-applications) | ||
- [Outputs](#outputs) | ||
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## Project description and aims | ||
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Short for **Aut**ism research into **S**ensory **P**rocessing for **A**ccessible **C**ommunity **E**nvironment**s**, [AutSPACEs is a co-created citizen science project](https://github.com/alan-turing-institute/AutSPACEs/) that was started in collaboration with the *[Autistica Foundation](https://www.autistica.org.uk/)*. | ||
The project was fully co-created with autistic participants that are involved in project design, management and implementation. | ||
The project was developing an online platform to collect qualitative experiences on sensory processing in autistic people, alongside recommendations & coping strategies to support autistic people, their friends/relatives, and policy makers. | ||
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The project had four goals: (1) Collect data to improve our understanding of sensory processing in people’s daily lives (2) Allow people to share their experiences and coping strategies to support others (3) Give non-autistic people a way to learn about the experiences of autistic people, allowing them to better understand the challenges and provide better support (4) Allow this data to be used by policy makers and creators of spaces and environments, to improve inclusion for autistic people. | ||
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## Lessons learned | ||
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One main lesson from the AutSPACEs project is that deep, engaged collaboration between academic researchers, open source developers and a community of volunteer contributors has significant potential to shape and implement a research project, in particular in a research environment that often is shaped by mutual distrust between "researchers" and "human subject". | ||
By approaching each group as equal collaborators, AutSPACEs managed to build a deep and sustained trust, leading to better and more ethical research than usually observed - especially in the fields of data science and AI. | ||
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The project also had to recognize that this approach comes with its own challenges. | ||
It requires a high level of engagement and buy-in from researchers - which not all researchers are willing to do. | ||
Due to the deliberative nature, this approach also moves slower than the typical academic, top-down governed research project where no deliberation takes place. | ||
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The flip side of this is that the deep deliberation can pre-empt challenges, which otherwise could become serious road blocks down the line: For example, the ethics and data protection reviews done within the Turing benefited dramatically from our deliberate approach, as we collectively not only considered a wide range of potential risks and harms to participants and how to protect their data, but also could demonstrate how we deliberatively agreed on tradeoffs in these situations. | ||
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### Managing a Citizen Science Project | ||
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In terms of project management citizen science requires a higher degree of adaptability and flexibility. | ||
As needs arise and change with community input and involve non-professional researchers and collaborators, a project manager in such a project should focus on helping everyone understand and navigate processes. | ||
The participation of individual collaborators and members of the public also makes it paramount to put mechanisms in place to enable and reward their contributions, all while ensuring this does not put them at any risk. | ||
The latter can be a challenge, in particular in the UK, when any income or attending an event can be cause of scrutiny for any state benefits. | ||
You should very carefully design this mechanisms and have clarity on existing and specific laws. | ||
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## Achievements | ||
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There a number of achievements across domains, given the interdisciplinary nature of the project. | ||
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### Citizen Science / Community engagement | ||
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- Over its lifetime, AutSPACEs managed to engage 100s of contributors, including autistic contributors, contributors who are parents/caretakers of autistic people, autism researchers, web/graphic designers, professional writers, open source developers, and many more - including virtually all intersections of these. Our diverse community, and the connections made within it, are one of the most lasting achievements that goes far beyond any traditional research. | ||
- Developing a wide range of modes of engagement. In these different modes, the contributors played in active role through: | ||
- Attending in-person focus groups and | ||
- monthly community meetings, | ||
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- participating in user testing - as well as actively interpreting the findings of those tests, and | ||
- co-leading on data interpretations and content moderation design | ||
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### Software / platform implementation | ||
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- AutSPACEs as a platform is now deployed as a pilot and collecting data, until September 30 when the platform will become _read only_ | ||
- All software outputs are openly licensed for re-use in the future | ||
- The whole stack is thoroughly documented to make this re-use and re-deployment by others easy | ||
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## Impact | ||
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The impact of AutSPACEs is two-fold: | ||
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1. The project has brought together a highly engaged and active community of contributors that support the project and each other. On this level, AutSPACEs has positively impacted a large number of its contributors, by providing a social network, but also opportunities to learn new skills (e.g. web design), building capacities and confidence (e.g. through public speaking opportunities), including opening up professional employment opportunities. | ||
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2. This collaborative approach has allowed the project to grow and sustain itself over a long period of time with modest funding, and also allowed the project to reach a wide range of stakeholders, including various autism researchers interested in modelling their own research after "the AutSPACEs model", both within the UK and abroad (e.g. in Spain and France) | ||
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## Real World Applications | ||
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The AutSPACEs approach to both the design itself and the software developed as part of it has already been used to teach students at institutions inside the UK (e.g. at UCL) and abroad (most recently at the University of Southern Denmark in Sept 2024). As such, the lessons learned (see above) and outputs (see below) continue to have real-world impact despite the Turing closing the project down on its side. | ||
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## Outputs | ||
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### Artefacts | ||
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- Software: The [AutSPACEs platform](https://github.com/alan-turing-institute/AutSPACEs), openly available under MIT license ([archived on Zenodo](https://zenodo.org/records/10667125)) | ||
- Data sets | ||
- The [data sets generated as part of the user tests](https://github.com/alan-turing-institute/AutSPACEs/tree/main/00-project-documentation/community/user-tests), openly licensed under MIT as well | ||
- The [data set of how the content moderation was designed](https://www.cambridge.org/core/journals/data-and-policy/article/how-to-cocreate-content-moderation-policies-the-case-of-the-autspaces-project/DF59760CB3F89901CB5634981C588B55) | ||
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### Publications | ||
- AutSPACEs features heavily as an example of ethics in citizen science within the [_Open Science Meets Citizen Science_](https://libereurope.eu/article/open-science-meets-citizen-science-a-guide/) guide of the _Association of European Research Libraries_, which was published on May 24, 2024 | ||
- The AutSPACEs team co-authored an [SSI speed blog on how RSEs can contribute to citizen science](https://www.software.ac.uk/blog/how-rses-can-engage-and-benefits-doing-so-citizen-science-projects) | ||
- An academic paper on [how the content moderation policy was designed](https://www.cambridge.org/core/journals/data-and-policy/article/how-to-cocreate-content-moderation-policies-the-case-of-the-autspaces-project/DF59760CB3F89901CB5634981C588B55) |
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Have we got any operational lessons learnt from the project management side? Apart from "build in project management time into grants"...
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Thinking in comment before writing into report:
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I added into the report, left out bits and in particular the last item, it felt long enough and also focused on the most important bits
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We should capture these internally in the doc hub for PMU though!