Introduction

The event is the first of a series of annual meetings of the CLARIN-CH community. It is organized by the CLARIN-CH consortium in cooperation with its member institutions and aims to support the scientific community in their challenges when it comes to Open Research data. It seeks to foster exchange and to enable the encounter between researchers and data management experts, as well as legal experts.

2. World Café

Participate in discussions with the invited experts:

• Brian Kleiner (FORS) - data protection
• Simone Mäder (UNIBAS) - data protection
• Suzanna Marazza (CCdigitallaw, USI) - copyright and other legal aspects
• Gerold Schneider (LiRI, UZH) - data formats and technical issues
• Teodora Vukovic (LiRI, UZH) - data formats and technical issues
• Christian Futter (UB UZH, Open Science Services and the Language Repository of Switzerland) - data storing and sharing
• Stefanie Strebel (UB UZH, Open Science Services and the Language Repository of Switzerland) - data storing and sharing)

The world café format will provide time for in-depth discussions, allowing participants to explore solutions to the challenges presented during the data pitches. This interactive setting is designed to foster meaningful exchanges and collaborative brainstorming.

Call for participation

For the morning sessions, we welcome submissions for data pitches on one or several of the four topics listed below. Data pitches should address challenges you face(d) related to the chosen theme(s) and if possible, present solutions. Each data pitch should be no longer than 5-10 minutes and held in English. Presentation slides are recommended. Submissions may also be made if the data has not been yet collected, but it presents potential challenges and/or opportunities.

Topics

1. Copyright describes the rights that creators have over their literary and artistic works, including their data. Researchers can encounter several challenges related to copyright when handling their data. These challenges can impact data sharing and reuse. Some key issues include questions around what can be shared, how to attribute sources, and whether specific data can be used freely or requires permission. Copyright considerations also come into play when deciding how to license the data for sharing.
   
   
2. When it comes to data protection and the management of personal and sensitive data, several critical issues arise: Researchers need to find the right balance between sharing data for research purposes and safeguarding individuals’ privacy. De-identification techniques can help here. They come with their own risks, however: It is quite impossible to render a dataset completely anonymous without also jeopardizing data utility, other datasets and additional information can potentially lead to re-identification of individuals and some types of linguistic data are less suited for these techniques. Security measures need to be taken to safe-guard personal and sensitive data, which poses additional problems, e.g. in collaborative projects. Also, linguists collecting data in other countries or from specific target groups need to navigate the complex legal landscape to ensure that the management and sharing of linguistic data comply with all relevant laws and regulations.
   
   
3. With regard to data formats (e.g. audio, video, text) and their technical aspects, linguists can also encounter various challenges. These include integrating diverse data formats for comprehensive linguistic analyses, harmonizing multimodal data, with annotating linguistic data consistently across formats, maintaining uniformity in transcription conventions, in part-of-speech tagging and in semantic labeling, with storing large-scale data (especially video) efficiently and having appropriate retrieval solutions, with optimizing storage formats, indexing and query performance, and with applying standardized formats across various systems.
   
   
4. To store and share their data, linguists are further presented with the issue of selecting appropriate repositories that align with their data type (and the intended audience), of storing the data in appropriate (standardized) formats, and of working collaboratively while effectively with other team members. Additionally, they are faced with the challenges of safeguarding sensitive and personal data while also making it accessible and taking into account expectations and value-systems of participants, as well as ensuring the researchers’ responsibility towards the population from which data has been gathered (according to the CARE principles).