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The challenges run over two semesters with a 3 ECTS module in Fall semester and a follow up module with 6 ECTS module Spring semester for successful projects. It is targeted to Master’s students from all disciplines.
In this module, interdisciplinary questions on challenges in the field of digital transformation are addressed in various projects. Under the guidance of a researcher from the Digital Society Initiative (DSI) network, students work in an interdisciplinary team of around 4 people, with each team member taking on defined tasks and also contributing specific digital skills. After an innovation phase, we facilitate an exchange between each team and experts from the DSI network. The teams receive advice on digital methods and approaches as well as information on ethical, legal, social and further aspects that should be taken into account in the project.
In the follow-up module in Spring, students can put their project ideas into practice.
| Date | Fall semester 2024 Highlights |
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Mon, Sept 16, 14:00-15:45 |
The Metadisciplinary Mashup - An Arts Research Workshop by Jonathon Keats World-Café Brainstorming Session on first challenge idea |
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Mon, Sept 23 and 30, |
World-Café Brainstorming Session on further challenge ideas |
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Mon, Oct 7, |
Introduction to Reproducibility and Good Research Practice by Eva Furrer, Managing Director of the Center for Reproducible Science |
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Mon, Oct 14, until Nov 4, |
Team building, development of project concept, design thinking, project management, and preparation for expert lunch |
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Mon, Nov 11, |
Expert lunch to get input from DSI Network experts and outreach partners |
| Mon, Nov 18, until Dec 9, 14:00-15:45 |
Develop project concept in challenge teams |
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Mon, Dec, 16, 14:00 - 18:00 |
DSI Minor End-of-Semester Celebration with World Café discussion on each project. |
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Spring semester 2025 Highlights |
| Mon, Feb 17, 12:00-15:45 |
Creativity workshop to get the semester started and get productive within the challenge team. |
| Mon, Feb 24 until May 15, 12:00-15:45 |
Realize project concept |
| Mon, May 19 14:00-18:00 |
DSI Minor End-of-Semester celebration with Poster-Session |
Sarah Ebling, DSI Community Communication
Yingqiang Gao | Institut für Computerlinguistik | UZH
Lukas Fischer | Institut für Computerlinguistik | UZH;
This challenge is concerned with automatically generating simplified texts along with images from standard-language texts. While automatic text simplification is an purelyestablished field of research by now, the task itself has so far been conceived as text-based, ignoring the importance of images for the target users. The aim of this challenge is to work with students to
1) automatically align images with textual units (words, sentences, paragraphs, …) in (human-generated) simplified-language texts, potentially creating additional artificial data (data augmentation).
2) automatically select existing images or synthesize new images along with generating text as part of an automatic text simplification step.
In synthesizing images, we will work with diffusion models. An important final step will be the validation of the automatically generated output among the target groups, e.g., persons with cognitive impairments. Thus, this challenge combines knowledge from the fields of computational linguistics (alignment, text generation), computer vision/graphics (image captioning, image synthesis), image theory/image didactics, and psycholinguistics (human evaluation).
Digital skills, that can be applied in this project idea:
Module/Course that allows students to acquire these digital skills:
Data, that can be worked with the project:
Kaspar Staub, DSI Community Health
Epidemics pose widespread challenges for society. Historical knowledge provides an invaluable resource for health policymakers, serving to raise awareness of potential risks. However, Switzerland, like many other regions, grapples with a collective memory gap concerning pandemics. The passage of a century without a significant pandemic has caused their presence and accessibility among researchers, policymakers, and the public to recede. In response to this challenge, we undertake the task of accessing knowledge concealed within historical sources, paving the way for a comprehensive understanding of past pandemic experiences in Switzerland. Our goal extends beyond research; it is to effectively reach and engage policymakers, media professionals, and the public, helping to bridge the memory gap of past pandemics in Switzerland.
Digital skills: Students can contribute to the “Bridging the Gap” (https://data.snf.ch/grants/grant/215863) project by incorporating the following educational resources and strategies, helping them develop a comprehensive skill set in digital tools and technologies:
1. Interactive Digital Archive (LEAD): Students can help improve the existing digital archive called LEAD Data Hub (www.leaddata.ch), where research data, publications, multimedia stories, and biographical videos related to past pandemics in Switzerland can be made easily accessible by the public, policymakers, and journalists. By ensuring that the database is searchable, well-organized, and includes metadata for easy retrieval of information, students can obtain skills regarding data management, digital archiving, and user experience design.
2. Data Visualization and Analytics: To develop data visualization skills, students can apply interactive maps, charts, and graphs, to help users gain insights into the spatial and temporal aspects of past pandemics. Students will be able to profit from two previous DSI initiatives regarding past pandemics and improve their knowledge in programming languages like Python.
3. Personalized Content Recommendations: Suggesting relevant content to users of the LEAD archive can help tailor the information to individual preferences and keep users engaged with the historical data. Students can therefore acquire skills related to recommendation algorithms through courses in machine learning and data analytics. Modules covering collaborative filtering, content-based filtering, and natural language processing can be beneficial.
4. User Feedback Mechanism: Students can implement a feedback system within the digital platform to collect user input, suggestions, and questions, providing in depth skills in user experience design and human-computer interaction. This information can help researchers better understand the needs and concerns of the target audiences and adapt their approach accordingly.
Module/Course that allows students to acquire these digital skills: None.
Data, that can be worked with the project: Numerous historical and modern health data series.
Hoda Allahbakhshi, DSI Community Mobility
The challenge involves developing a sustainable and scalable open digital platform that effectively maintains and updates spatial accessibility data within urban environments. MSc students are tasked with designing a system that can integrate diverse data sources, support real-time updates, and ensure data accuracy and reliability. The platform must be user-friendly, capable of handling large volumes of data, and adaptable to various urban contexts. Additionally, the project requires addressing challenges related to data privacy, security, and ethical considerations, while promoting open access and community engagement to ensure the platform's longevity and widespread adoption.
Digital skills:
Module/Course that allows students to acquire these digital skills:
Data, that can be worked with the project:
Dr. Markus Christen | Digital Society Initiative | UZH
Outreach Partner: Data Innovation Alliance / BRIDGE Lab
The EU AI Act (>400 pages long) requires compliance to its regulations by any company active on the EU market within the next two years. Many companies – in particular smaller ones and start-ups – don’t have the resources to fully understand how their new AI innovations may lead to compliance issues with this complex legislation. They need a solution for that problem that points them to be best supporter (consultant etc.) in order to address these issues.
In this Challenge, the team will support a project of the Data Innovation Alliance to create AILAS - a tool for any AI product/service developer to find out what kind of legal issues they face and where to get help to solve these issues. AILAS will interconnect users (companies that develop AI innovations) with supporters (consultants that have AI legal expertise) through a neutral intermediary (the Data Innovation Ethics Expert Group powered by academic expertise) in order to efficiently handle legal challenges imposed by the EU AI Act. In the Fall Semester 2024, the team will support a “shaping workshop” of the alliance to develop a framework. In the Spring Semester 2025, the team will support tool development including user studies.
Learning goals: In this challenge, students will achieve the following learning goals:
Digital skills: Contributing to this challenge will need the following skills:
Module/Course that allows students to acquire these digital skills:
Data, that can be worked with the project: Legal text (EU AI Act) for knowledge extraction. The project will also generate user data that would be analyzed using standard descriptive statistics.
Co-Supervisor:
Serhiy Kandul | Institute of Biomedical Ethics and History of Medicine (IBME) | UZH
Outreach Partner: Swiss Drone and Robotics Center
In this Challenge, students will work with data generated in several experiments where users interacted with a real AI for completing a landing task in a simulation (lunar lander). In the studies, users had to predict AI behavior and had to make decisions when to take over the AI task, respectively were confronted that AI took over their tasks when performing bad. In the Fall Semester 2024, the students will be introduced to the experimental paradigm and the data generated by the experiments and they will provide data analysis for supporting the wrap-up of the ongoing experimental phase. In the Spring Semester 2025, based on the previous experiences, the students will conceptualize and design a follow-up experiment to further understand factors that influence successful human-AI collaboration.
Learning goals: In this challenge, students will achieve the following learning goals:
Digital skills: Contributing to this challenge will need the following skills:
Module/Course that allows students to acquire these digital skills:
Data, that can be worked with the project: Experimental data, time series and video data on AI behavior.
Mario Angst, DSI Community Sustainability
Outreach Partner: Dr. Maximilian Schneider, Econetta | sustainable solutions since 1995
What are the most effective interventions to increase the sustainability of digital device usage among students at UZH?
The students should develop a project that:
- maps sustainability impacts of digital device usage among students at UZH, from device choice over device use to discharge
- develops interventions along this journey to reduce sustainability impacts. Interventions may be anything that helps on any point along the journey: from developing tools to recycle old devices, to providing education on device choice, aiding in setting up a laptop optimized to save energy, or maybe even policy recommendations for the rectorate. Whatever might be promising and impactful.
- formulates a theory of change for a given intervention
- evaluates a promising intervention (or multiple) against a baseline. For example, this may involve low-cost interventions (eg. information campaigns) versus likely high-impact, high-cost (eg. face to face set up sessions) but there likely are many other possible (and creative) ways to go about this.
- depending on the theory of change and intervention in question, uses quantitative or qualitative data such as usage data logs or user interview to evaluate the intervention
- develops recommendations to scale up the intervention (weighing costs of interventions against impact)
Digital skills, that can be applied in this project idea:
Module/Course that allows students to acquire these digital skills:
There are lots of online resources and at least one similar project in Switzerland focusing on setting up laptops for increasing privacy (without evaluation though).
Data, that can be worked with the project:
To actually evaluate the effects of interventions, students will need to evaluate usage data from consenting users. The form of data will vary depending on the intervention evaluated, but might require:
- develop a data privacy conscious way to get adequate measures of laptop usage from usage logs
- test the effects of information interventions on device purchase decisions
- measure energy use of refurbished laptops
- analyze interviews with users
Co-Supervisor:
Marcia Nißen, DSI Community Health
Co-Supervisor:
Tobias Kowatsch, DSI Community Health
Closing the Women’s Health1 Gap has the potential to significantly enhance the health and quality of life of half the global population and, eventually, nations’ economic prosperity. Yet, knowledge, research, and funding on the design and development of sex- and gender-specific digital health technologies (DHTs) are only evolving.
Women’s health is characterized by unique physiological and hormonal dynamics over the life course, such as those associated with the menstrual cycle, pregnancy, or the menopausal transition. These fluctuations orchestrate many physiological and psychological processes that shape women’s health, well-being, and behavior, influencing everything from cognitive function and emotional regulation to pain perception, energy levels, and mood. Despite the significant impact of these factors, they are often underrepresented in current research methodologies and clinical trials.
This DSI challenge, therefore, centers on the pressing need for systematically integrating female-specific data into (clinical) research in general and the development of DHTs in particular to enhance the understanding and management of women’s health over the life course.
One objective of this challenge could be to explore how digital health tools, such as wearable technologies, mobile health apps, and other digital platforms, can be utilized to collect, integrate, and analyze female-specific data and to develop a comprehensive framework or advance the development of an available app prototype (“CyMe”) to collect such data.
1We use the gender-specific term “women’s health” to refer to female-specific conditions and conditions that disproportionately or differently, though not exclusively, affect individuals assigned female at birth (AFAB).
Digital skills that can be applied to this project idea: Depending on the team’s focus and individual students’ background:
Conducting user studies online
Module/Course that allows students to acquire these digital skills:
Data, that can be worked with during the project: We have various datasets that could be leveraged ranging from
cross-sectional quantitative and qualitative data from user surveys and online experiments.
MA
3 ECTS
You can find more information about the module here.
