Sustainable Development Goals Research Scout

The SDG Research Scout infrastructure project aims to use cutting-edge NLP, AI, and interactive
visual data analysis to identify content relevant to the UN Sustainable Development Goals (SDGs) in scientific publications, making it easier for UZH members to engage with SDG-relevant research. SDG definitions are analyzed both at the goal and the target levels to get rich semantic information. By combining expertise from the Department of Informatics (IFI), the Department of Computational Linguistics (CL), and the Sustainability Team, the project will develop an intelligent system to identify and explore SDG-related output in ZORA and potentially other similar repositories. In the best case, other universities may join our initiative.

The primary goal of the SDG Research Scout is to provide interactive data science support for UZH to enable effective mapping and relevancy assessment of SDG goals and targets for scientific publications by sustainability experts, and to help UZH members explore SDG-related publications interactively. The system will offer UZH members flexible and intelligent access to all UZH publications with relevance for the SDGs, and will serve as a pilot model for the combination of AI and sustainability research. Furthermore, the SDG-based classification labels generated by the system can be integrated into the UZH repositories to support publication discovery.

The project will be supervised by Eduard Čuba andProf. Jürgen Bernard.

The project should start at the end of the spring term and the duration of the project will be no longer than 8 months. A group of ~3 students will be working on the project.

The project language is English, therefore, you are required to have good English knowledge (written and oral).

The programming languages of the project are not yet defined and are up for discussion by the project team (preferably Python for the back end and JavaScript for the front end). The code will be versioned through GitLab and the tool will be hosted on the IFI server.

You should have the following skills for this project:

• Profound programming skills (preferably with Python and/or JavaScript), ideally with full-stack background
• Basic knowledge of databases (e.g. how to write a database statement to retrieve data)
• Experience in working with version control systems (e.g. Git, we will be using GitLab)
• Interest in research

In addition, it would be nice if you have experience in one of the following areas (but it is not a must):

• UI / UX design
• Testing (e.g. Unit Testing)
• DevOps such as CI/CD and application deployment
• REST or any other framework that supports the communication between the back and front end
• CSS and HTML
• Front end frameworks such as ReactJS, Angular, Material Design, Bootstrap
• Back end frameworks such as Django, Flask, Spring

The topic will be assigned through the "Master Project Market" in Spring 2023. Watch out for the event sop that you don't miss it!

Interested students should send their complete application to Prof. Jürgen Bernard.

Applications should include:

• Short, informal letter of motivation including your expectation for the project, the skills you want to learn, and your experience with data visualizations (if any)
• CV
• Transcript of records from your Master's and Bachelor's Degree

If you have any questions about the project, please feel free to contact Eduard Čuba orProf. Jürgen Bernard.