We are thrilled to announce that the EWADA Team has achieved significant success, with four major research papers accepted for publication by Nature Machine Intelligence, CHI2024, and WWW2024. These prestigious academic venues are highly competitive, and our researchers have put in tremendous effort to achieve these outstanding results. The papers cover a diverse range of topics, including the research agenda for supporting child-centered AI, the development and assessment of new ways to enhance families’ critical thinking regarding datafication, children’s data autonomy, and users’ ability to navigate data terms of use in decentralized settings.

Ge Wang, Jun Zhao, Max Van Kleek and Nigel Shadbolt. Challenges and opportunities in translating ethical AI principles into practice for children. Nature Machine Intelligence. To appear

Led by Tiffany Ge and Dr Jun Zhao, the perspective paper discusses the current global landscape of ethics guidelines for AI and their correlation with children. The article critically assesses the strategies and recommendations proposed by current AI ethics initiatives, identifying the critical challenges in translating such ethical AI principles into practice for children. The article provides timely and crucial recommendations regarding embedding ethics into the development and governance of AI for children.

Ge Wang, Jun Zhao, Max Van Kleek and Nigel Shadbolt. KOALA Hero Toolkit: A New Approach to Inform Families of Mobile Datafication Risks. CHI 2024. Overall acceptance rate 26.3%. To appear

This is the final evaluation study of the KOALA Hero research project, led by Dr Jun Zhao and partially supported by EWADA. In this work we present a new hybrid toolkit, KOALA Hero, designed to help children and parents jointly understand the datafication risks posed by their mobile apps. Through user studies involving 17 families, we assess how the toolkit influenced families’ thought processes, perceptions and decision-making regarding mobile datafication risks. Our findings show that KOALA supports families’ critical thinking and promotes family engagement, providing timely inputs on global efforts aimed at addressing datafication risks and underscoring the importance of strengthening legislative and policy enforcement of ethical data governance.

This work has also contributed to Dr Zhao’s discussion paper to be publised by the British Academy, jointly authored with Dr Ekaterina Hertog from Oxford Internet Institute and Ethics in AI Institute and Professor Netta Weinstein from University of Reading.

Ge Wang, Jun Zhao, Max Van Kleek and Nigel Shadbolt. CHAITok: A Proof-of-Concept System Supporting Children’s Sense of Data Autonomy. CHI 2024. Overall acceptance rate 26.3%. To appear

A core part of EWADA’s mission, CHAITok explores children’s ‘sense of data autonomy’. In this paper, we present CHAITok, a Solid-Based Android mobile application designed to enhance children’s sense of autonomy over their data on social media. Through 27 user study sessions with 109 children aged 10–13, we offer insights into the current lack of data autonomy among children regarding their online information and how we can foster children’s sense of data autonomy through a socio-technical journey. Our findings provide crucial insights into children’s values, how we can better support children’s evolving autonomy, and design for children’s digital rights. We emphasize data autonomy as a fundamental right for children, call for further research, design innovation, and policy changes on this critical issue.

Rui Zhao and Jun Zhao. Perennial Semantic Data Terms of Use for Decentralized Web. WWW 2024. Overall acceptance rate 20.2%. To appear.

Our latest research article address a significant challenge in decentralized Web architectures, such as Solid, specifically focusing on how to help users navigate numerous applications and decide which application can be trusted with access to their data Pods.

Currently, this process often involves reading lengthy and complex Terms of Use agreements, which users often find daunting or simply ignore. This compromises user autonomy and impedes detection of data misuse. To address this issue, EWADA researchers have developed a novel formal description of Data Terms of Use (DToU), along with a DToU reasoner. Users and applications can specify their own parts of the DToU policy with local knowledge, covering permissions, requirements, prohibitions and obligations. Automated reasoning verifies compliance, and also derives policies for output data. This constitutes a perennial DToU language, where the policy authoring occurs only once, allowing ongoing automated checks across users, applications and activity cycles. Our solution has been successfully integrated into the Solid framework with promising performance results. We believe this work demonstrates a practicality of a perennial DToU language and the potential for a paradigm shift in how users interact with data and applications in a decentralized Web, offering both improved privacy and usability.

All papers are currently in preparation for the camera-ready stage. Once finalised, you can find them on our publication page. We welcome your feedback and any follow-up questions.

Summer 2023 marks the third year of our highly successful internship program. We are delighted to host four internships with outstanding candidates, along with a master’s student who conducted their graduate project with us. Each student has made significant contributions to EWADA, and this report provides a summary of the key outcomes from these projects.

Overview of the projects

The four projects addressed various challenges aligned with EWADA’s core vision, including: A Solid-based application designed to assist families in managing children’s health data

• Extending our previous research on privacy-preserving computation with an ability to generate privacy-preserving synthetic data
• Extending our earlier work on decentralised recommendation algorithms with an ability to generate privacy-preserving movie recommendations
• Extending our prior research on supporting gig workers with a Solid-based approach to help workers manage their data

A Solid-based application to assist families in managing children’s health data

The project aimed to ensure that children, especifically those with ADHD, can exercise better control over the sharing of their data within an ecosystem involving parents/guardians, teachers, the broad school community, as well as clinicians or hospital staff. This is crucial challenge as the current scenario sees parents/guardians as the sole stakeholders with access to children’s information, determining how the data is accessed by and shared. Thus, the project seeks to explore a new model, in which children will be equipped with smartwatches and parents/guardians could examine the data through smartphones.

The project focused on building an architecture on top of SOLID, to collect, store and synchronise data generated by children’s smartwatches. It provides a web interface that allows a child with ADHD to share data and control the extent of information to share with requesting stakeholders. Different types of data that can be collected, including emotional dysregulation, medication usage, food intake, sleep and heart rate, step count, and location. A primary objective is to build a more empowered ecosystem of communication within schools regarding how health data may be shared with clinicians.

The approach is grounded in extending the experience sampling method (ESM), a research technique used in psychology and other fields to study individuals’ experiences, behaviours, and thoughts in real-time, as they occur in their natural environment.

For this project, location serves as the primary use case data due to its personal and sensitive nature. We want to explore whether visualization of data sharing could help children decide the extent to which they want to share their location data or any other data.

Privacy-preserving Decentralised Information Filtering

This work is based on our SolidFlix project, which is a Solid-based application allowing friends to share movie interests by storing this information in their individual pods. The movie recommendation algorithm used by SolidFlix is content-based, whereas a collaborative filter could provide more personalised recommendations by suggesting movies based on what a user’s friends are interested in watching.

However, conventionally, this kind of recommendation algorithm requires centralised access to all users’ data. The challenge lies in supporting collaborative recommendations without compromising the decentralised architecture and our commitment to preserve users’ data privacy.

The approach taken by the project team was to first compute similarities between each user’s movie list, and then generate recommendation. In the first step, a hash is created for each user’s movie list, which is then locally stored in their Solid pod. Using the hash code, then users could be categorised into distinct buckets, and individuals within the same bucket are considered similar, thus receiving identical recommendations.

In the context of movie recommendations, when a user, Bob, seeks a recommendation, he fetches the min hashes from all his friends’ pods, which will trigger the delivery of personalised recommendations. Bob can then request access to these movies from friends.

There are several advantages to this approach. To begin with, using collaborative filtering might be more feasible as it does not rely on the use of movie metadata, which is not always provided. Also, the approach is more scalable approach because it is built on pre-computed hashes, although there is a dependency on users sharing their min hashes.

A more detailed technical description and a recorded presentation can be found in Dr Goel’s blog post.

Decentralised Scalable and Privacy Preserving Synthetic Data Generation

For AI model development, we require more diverse datasets. However, sharing real data can become problematic because of privacy-related issues. This is solved by using synthetic data.

The objective of this project is to take a holistic approach to working with synthetic data. However, there is a need to organise the curation of this data. Various models for curating synthetic data exist, including a central differential privacy approach and a local differential privacy approach: the central differential privacy approach assumes a trusted curator collects individual data and then engages in the synthetic dataset generation; and the local differential privacy approach assumes that everyone locally adds noise before sending it to the central curator. The disadvantage of the central approach is that it might be compromised, as someone can gain control of these datasets and compromise its privacy; and that of the local approach is the potential for a significant amount of noise and requires substantial local computational capability.

The approach explored in this project involves curating data from Solid users, with users having the ability to determine their participation in the synthetic data generation process. Importantly, the architecture is based on Solid pods enhanced with a multi-party computation protocol to preserve the security and privacy of this process. Initial results show promising performance, and further details about the approach can be found in the arxiv paper.

A Solid-based approach to help workers manage their data

This project continues last year’s efforts, and its key objective is to determine how we can better manage incompatible datasets across different gig workers contexts and platforms. This is a crucial challenge because gig workers regularly face the task of managing data from different, in compatible platforms. To address this issue, we propose a solution called “Frankenstein drivers”. The goal is to experiment with different methods of managing gig worker data across diverse content using the SOLID protocols. Central to this solution is the use of an embedded model that matches semantic information, and LLM as a data wrangler tool to extract information from different sources and create meaningful visualisations. This transformation has significantly increased the productivity of a previously manual process, and the team is looking into exploring the possibility of establishing a direct integration between the LLM models and Solid pods.

This wide range of summer projects produced rich results, and we hope that he work will continue with the aim of building a community around these topic areas and integrating this work in the core EWADA pipeline. We thank the contributions by Sydney C., Yushi Y, Vishal R, Vid V, and the supervisions by Jake Stein, Rui Zhao, Naman Goel and Jun Zhao.

We are really excited to welcome our new full-time EWADA DPhil joining the project - Jesse Wright.

Jesse is previously a software engineer at Inrupt, a forward-thinking start-up creating data infrastructure software that enables enterprises and governments to deploy and manage Solid-compliant solutions.

Jesse is fully-funded by the prestigious Oxford Computer Science Departmental Studentship. His research will explore how to enable trust reasoning in the decentralised setting in order to empower true data autonomy for the users.

Jesse is co-supervised by Professor Nigel Shadbolt and Dr Jun Zhao.

On 22 May 2023, EWADA had our second annual project meeting, attended by 14 project members and affiliates.

We had an exciting list of discussions about our recent research progress over the last year, related to (1) privacy-preserving computation with Solid; (2) decentralised data governance structure for gig workers; (3) design considerations for supporting the expression of data terms of use; (4) social-behavioural challenges for empowering users’ digital autonomy and self-determination; and finally (5) integration of more advanced AI computations with Solid.

Some of these research investigations represent a deeper or more extensive investigation that we started last year; while others are new directions and perspectives that we are expanding into, built on the foundational understanding and technical capabilities that we created last year.

In the next few months, we will be looking forward to welcoming several summer interns to join the team this summer, to further explore some of the open challenges above (particularly items 3-5). We are also hoping to share some ongoing investigations of this work via public blog posts or reports to bootstrap community building.

If you are interested to learn more about any of these activities, please do not hesitate to get in touch with the EWADA team.

We are really excited to welcome a new full-time EWADA RA joining the project - Dr Samantha-Kaye Johnston.

Dr Johnston is from a psychology and education science background. She is currently a Supernumerary Fellow in Education at Jesus College and her wealth of extensive experience in qualitative and quantitative research in the context of EdTech would undoubtedly provide a great asset to the EWADA project.

Further details about Sam can be found on her college web page.

We are very excited to announce 3 summer internships in 2023!!!

Please join us if you want to develop privacy-friendly AI, with a group of world-leading computer scientists!

Detailed job description

You will be working as part of the Oxford Martin School programme EWADA (Ethical Web and Data Infrastructure in the Age of AI) [1]. Data-driven algorithms are positively changing every walk of our life. However, from simple data aggregation algorithms for drawing collective insights to more advanced machine learning algorithms, all involve computations that are currently performed using centralised access to the users’ data. During the internship, you will be responsible for building scalable systems to perform privacy-preserving artificial intelligence (AI) computations in decentralized personal data architectures to contribute to the creation of a more ethical AI ecosystem. Specifically, you will use the Solid (Social Linked Data) architecture [2], upon which to build such AI systems and algorithms. Interns will demonstrate the practical significance of their work in application use cases and we have a range of application use cases for the internship, including but not limited to the:

• Personalised Recommender Systems
• Large Language Models like GPT
• Open (Health) Data
• Algorithmic Fairness and Transparency

Background of the project

EWADA is an ambitious 3-year programme that aims to reform the concentration of power on the Web by developing and deploying new forms of technical and legal infrastructure. The project is led by Prof Sir Nigel Shadbolt and Prof Sir Tim Berner-Lee and aims to investigate novel re-decentralisation architectures and develop privacy-preserving AI methods to re-establish citizens’ self-autonomy on the Web.

Selection criteria

You must have hands-on programming experience with machine learning, strong problem-solving skills and a demonstrated passion for building large-scale systems and performing comprehensive empirical evaluations. You either have prior experience or are interested and willing to learn quickly about privacy-preserving techniques like multi-party computation and Solid ecosystems. Successful candidates are also expected to be able to work independently.

Application

The post is expected to be full-time (36.5 hours) for 12 weeks, starting mid-July 2023 and ending in September 2023, £14.09 - £15.66 (Grade 3.8 - 4.7) per hour, depending on experience. If you are a student holding a Tier 4 visa, then you are permitted to work full-time for 8 weeks, plus 4 weeks part-time (max 20 hrs per week).

The post does not have to be based in Oxford but will be subject to the right to work in the UK. We CAN NOT sponsor visa applications due to the short duration of the project.

Applications should be submitted to Human Resources Department at hr@cs.ox.ac.uk with a resume or CV. A short paragraph on your background, interests and motivation to apply will be helpful.

The subject of the email should be: “Internship Application for Privacy-Preserving AI in Decentralized Personal Data Architectures”

The closing date for applications is noon on Friday 16th June 2023. Candidates will be shortlisted and invited for an interview in late June.

Selection criteria

Essential

• Fundamental understanding and hands-on experience with implementing machine learning.
• Proficiency in Python and ability to work with Linux-based Operating Systems.
• The ability and desire to learn about Solid, to quickly acquire domain expertise needed for effectively developing new systems on top of Solid.
• The ability to communicate information clearly, including technical content.
• The ability to work independently and think creatively.
• The ability to effectively manage time, to complete projects efficiently.

Desirable

• Experience with deep learning.
• Experience in privacy-friendly techniques like multi-party computation, homomorphic encryption, differential privacy, federated learning etc.
• Experience with distributed and decentralized systems.
• Familiarity with basic cryptographic techniques.
• Excellent writing and presentation skills.

[1] https://www.oxfordmartin.ox.ac.uk/ethical-web-and-data-architectures/

[2] https://solidproject.org

On March 4, 2023, we are excited to have Sir Tim Berners-Lee to host a short introduction workshop about Solid for a small group of undergraduate and postgraduate students in Oxford CS, who will be doing solid-related student projects in Trinity or the academic year of 2023/24.

This is the first year we put up Solid-related projects at our department for UG and Msc students, and they have been extremely well-received. We have received quite a lot of interests from our students, who have shown a strong passion for exploring and building an alternative to the current platform-centric data ecosystem. However, during our initial tutorials, we realised that running an introductory workshop on Solid and its vision and history would be beneficial to all students and lay down a good foundation for their projects. This first Solid hands-on workshop was created for this purpose.

We have been very fortunate to have Tim to open the workshop and provide the introduction about Solid. It has been amazing to see how Tim walked through the beginning of Web 1.0, to the journey from Web 2.0 (the social web) to the so-called Web3.0 (the decentralised web), and how the stack of standard protocols underpinning these technologies have made it possible for us to have an open and interoperable World Wide Web.

Even for many of the EWADA researchers in the room, it has been exciting to see how Solid is perceived to sit along existing standard protocols, and be the nucleus of a solid ecosystem, with all the possibilities of enabling data autonomy and creating a wave of new, ethical, and open data applications for the governments, companies and individuals.

Following this informative introduction, we continued the workshop with some demonstrations of solid-based web applications by both Prof Ruben Verborgh from Ghent University and the EWADA team.

In the second half of the workshop, we undertook a productive one-hour hands-on exercises with Solid. Everyone managed to create a WebID, log into the SolidFlix application built by EWADA, create and share movie data with everyone in the room. Most excitingly, Tim suggested that why don’t we also take this opportunity and create a Solid chat room, so that it will ease the communication amongst this exciting team and relieve us from proprietary platforms.

We will continue and run another public Solid workshop at Oxford CS in the Trinity Term. All resources used by this workshop can be found below:

• Introduction to Solid by Tim
• SolidFlix
• Hands on exercise slide
• Additional resources about Solid

Ethical Web and Data Architectures – they give our project its name, but what precisely makes a technical artefact like a web or data architecture, ethical? This is an excellent question and one we receive often.

This is also a question for which the existing web provides some good examples. Wikipedia seems to miraculously negotiate consensus across millions of voices to deliver truth in a mis-and-disinformation-ridden web. The SOLID project promises to enable a new age of web interoperability and personal data control through new protocols. Data trusts, collaboratives, and cooperatives put forward a diverse vision for collective governance in their own respective, brighter, data futures (Brandusescu, Ana and van Geus, Jonathan 2020).

These proposals all latently embody values of fairness or autonomy, but are dotted with intricate voting mechanisms, technical implementations, and esoteric concepts for what the future technologies might look like. Seldom are these designs for data futures relatable to, nor designed by the data subjects who they aim to benefit. For those who will inevitably experience these data futures, design questions are not focused on the lightning rod terms of data governance like quadratic voting, homomorphic encryption, or ephemeral services. They are more along the lines of how do I stay safe, make more money, or connect with community with the help of my data, rather than in spite of it (Zhang et al. 2022)? Though Human Computer Interaction (HCI) values user participation in design, existing research has steered clear of allowing users to participate in data stewardship, labelling data architectures and protocols as too technically complex for the data literacy of the average web user, or simply a matter of implementation details (Bødker and Kyng 2018). We see these architectures differently. They are the product of the socio-technical systems and relations which they create, support, or automate and can themselves be as (un)ethical as those systems too.

In a new paper accepted to this year’s ACM CHI Conference on Human Factors in Computing Systems (CHI23), EWADA researchers challenged this assumption. The paper, led by EWADA PhD student Jake Stein with help from EWADA summer intern Vid Mikucionis, developed new methods to elicit what data architectures should embody based on the direct input of data subjects themselves. In the paper, the EWADA team engaged with gig workers driving and riding with platforms like Uber, Lyft and Deliveroo, whose algorithmic management practices makes workers particularly vulnerable to exploitative information asymmetries. The research provides meaningful strides bridging the gap between novel data infrastructures and the practical everyday challenges created by data stewardship. The EWADA team puts forward a new methodology that retools canonical HCI methods from their typical domain of interface and interaction design to address the fundamentally contingent and socially-bound dynamics of data architecture building.

Contrary to prevailing thinking, the team found data subjects of varying data literacy levels were excited to participate in collective data stewardship. In simulated data stewardship tasks, the participants were able to first internalise the affordances of separate data structures, then provide meaningful input into the design of collective data infrastructures based on their reflection. In our methodology, the EWADA team highlighted the great potential of using existing legal tools including Data Subject Access Requests to augment commonly used participatory design tools like online whiteboards.

Beyond demonstrating new means for participatory data architecture design, the participants expressed important considerations that should be included in designs for collectively governed data architectures. These included the need for dispute, discussion, correction and contextualization mechanisms, granular permissions affordances, and community-facing analytics portals. Participants also contributed a wide variety of ideas about which stakeholders should participate in new data institutions and their respective roles from labour unions and governments, to autonomous collectives, affinity groups based on ethnicity and gender identity, and online communities. The study concludes by providing two points of reflexive consideration. It questions researchers’ role in gig economies, questioning how researchers can intervene to expose information asymmetries without replicating gig-like work conditions and providing valuable information to workers. Finally, it calls for future research to continue developing participatory design methods suitable for data data architecture design pointing to the danger for architectures to repeat patterns they aim to resist.

• BØdker, Susanne, and Morten Kyng. 2018. ‘Participatory Design That Matters—Facing the Big Issues’. ACM Transactions on Computer-Human Interaction 25(1):1–31. doi: 10.1145/3152421.

• Brandusescu, Ana and van Geus, Jonathan. 2020. Shifting Power through Data Governance. Mozilla Data Futures Lab.

• Zhang, Angie, Alexander Boltz, Chun Wei Wang, and Min Kyung Lee. 2022. ‘Algorithmic Management Reimagined For Workers and By Workers: Centering Worker Well-Being in Gig Work’. Pp. 1–20 in CHI Conference on Human Factors in Computing Systems. New Orleans LA USA: ACM.

The key goal of the EWADA project is “to develop and deploy new forms of technical and legal infrastructure, to re-design and promote a more equitable and ethical treatment of individual users and collectives in a sustainable way”. One of the applications of this initiative is to explore how we can better support children and families’ data autonomy. In fact, digital technologies have become so deeply embedded in children’s everyday lives, providing vital access to educational, social, and entertainment experiences and resources. Children of this generation are often the early adopters of emerging services and technologies, having grown up as ‘digital natives’. This has raised concerns and questions about how digital environments including digital apps, systems, services, platforms and more, are affecting children’s well-being, and whether such environments adequately support their developmental needs.

From a human-centred point of view, two lead EWADA researchers (Dr Jun Zhao and [Ge Wang][https://www.tiffanygewang.com]) explored what children and their families recognise as being supportive and ethical, how they would like these components to look like and what supports are needed. Our understandings about this topic have been furthered in this process, as captured by our two CHI’2023 paper:

1. 12 Ways to Empower: Designing for Children’s Digital Autonomy pdf

In this paper, we examine existing HCI literature discussing definitions and designs for children’s digital autonomy. Our aim is to contribute an understanding of how digital autonomy for children is positioned in the current HCI community, and to identify how specific kinds of designs have been explored to support digital autonomy development in children. To do so, we conducted a systematic review of the use of autonomy-supportive design mechanisms in HCI research, with the goal of laying out its design space, specifically answering two research questions as follows: RQ1 - How does the HCI literature conceptualise digital autonomy for children? RQ2 - What autonomy-supportive design mechanisms have been explored in apps and systems for children? Our findings provide a critical understanding of current support for children’s digital autonomy in HCI. We highlight the importance of considering children’s digital autonomy from multi-perspectives, and suggest critical factors and gaps to be considered for future more autonomy-supportive designs.

2.”Treat me as your friend, not a number in your database’’: Co-designing with Children to Cope with Datafication Online pdf

Datafication refers to the practices through which children’s online actions are pervasively recorded, tracked, aggregated, analysed, and exploited by online services in ways including behavioural engineering and monetisation. Previous research has shown that not only do children care significantly about various aspects of datafication, but they demand a chance to take action. Through 10 co-design sessions with 53 children, we examined how children in the UK want to be supported to cope with the datafication practices. Our findings provide insights for creating age-appropriate support for children’s algorithmic literacy development, highlighting and unpacking the importance of no one-size-fitting-all designs to support children’s coping with datafication. We contribute a first understanding of how children aged 7–14 would like to be supported with datafication and what future data-driven digital experiences should be like for them, who demand a shift of the current data ecosystem towards a more humane-by-design and autonomy-supportive future.

Please follow the above links for further reading and contact the authors if you wish for further information.

On 8 December, the EWADA team members, Jun, Rui and Hunar, represented the project team on the remote gathering of Solid World, and shared with the Solid community some of our latest developments.

Solid World is a monthly online event that provides an opportunity for the community to meet others who are also working on Solid. The December event started with an introduction from Tim and Pierrer-Antoine about the formation of a W3C working group for Solid, and then followed by presentations by us about SolidFlix and Solid Calendar, and another presentation from Jackson Morgan about LDO.

Both Hunar and Rui provided a short presentation about SolidFlix and Solid Calendar respectively, which included a short screencast showing how the current implementation works, see videos linked below. In the presentation of SolidFlix, Hunar gave a nice summary of the architectural design of our application and its current ability of enabling social sharing of movies and performing simple movie recommendations based on what friends have watched/liked. In the presentation of Solid Calendar, Rui showed how the application can enable users to sync their existing calendars (such as Google Calendar and iCal) with their Solid pods, and thus make it easier for them to schedule meetings using this Solid-based application with friends, who may rely on different calendar systems. The application improves an existing application from Ghent University, Knoodle, with a more usable user interface and a refactoring of the original architectural design, which replaces the dependency of a custom-built Solid server with more modularised components.

The presentations were well received by the >60 attendees at the meeting and we received interesting questions including: whether we have performed any UX evaluations with our prototypes yet and how users reacted to it, whether SolidFlix is compatible with Media Kraken, and how we see the proposed architectural design of Solid Calendar could work with existing Solid designs.

To follow up, our next steps for the SolidFlix project include continuing internal user testing to improve the robustness of the initial log-in (onboard) process, and exploring a privacy-preserving movie recommendation. For the Solid Calendar project, we would also like to carry out further internal testing, deploy the new calendar import service (aka the orchestrator service) for broader access within Oxford, and explore the interoperability of our proposed architectural design with the rest of Solid stacks.

Below are links to our presentations and demo pages:

• Presentation of SolidFlix Google slides
• Presentation of Solid Calendar, including the screencast
• Demo page for SolidFlix - WebID required
• Demo page for Solid Calendar - WebID and access to a Google Calendar required

Please do not hesitate to get in touch with us via the contact page if you would like to know more about the work.