This introductory session of our CLARIN-CH Training Sessions 2025 will provide an overview of the CLARIN-CH ecosystem of infrastructures, highlighting their role in supporting research involving language resources and language technology. Participants will gain insights into the various infrastructures available within CLARIN-CH and how they facilitate Open Research Data (ORD) practices in language research. Each of the infrastructures will be further adressed, both from a theoretical and a hands-on perspective, in decidated sessions during March-June 2025.
Topics covered in the introductory session:
- What is CLARIN-CH?
- The Importance of ORD and FAIR in Language Research
- Open Science, Open Research Data (ORD) and FAIR (Findable, Accessible, Interoperable, Reusable) data
- How ORD and FAIR practices enhance reproducibility, trust, collaboration and data sharing (e.g. linking your research data to your scientific paper)
- Hands-on: analysis of case studies
- Overview of the CLARIN-CH ecosystem of infrastructures
- The LiRI Corpus Platform
- The swissdox@LiRI media database
- ZHAW Swiss-AL
- Language Repository of Switzerland (LaRS) and the SWISSUbase repository
- The CLARIN-CH Documentation Platform
- Introduction to key ORD projects, such as UpLORD and FAIR-FI-LD, and their main outcomes
- Metadata interoperability and harvesting by CLARIN Virtual Language Observatory
- Curation workflow by LaRS team
- Standard data formats
- CLARIN Federated Content Search technology
- Videoscope @ USI
- Challenges of ORD and FAIR for Language Data
- Handling sensitive and complex linguistic data, including ethical and legal considerations.
- Encouraging researchers and institutions to engage with CLARIN-CH
Who should attend?
This session is designed for researchers using language data, irrespective of scientific discipline, sub-field of linguistics or approach, as well as data stewards, who want to learn more about the CLARIN-CH research data ecosystem and its tools.
By the end of the session, participants will have a clearer understanding of how to navigate the CLARIN-CH infrastructures, apply ORD principles effectively, and address challenges in language data management. This will make your life much easier when publishing your data and when write your DMP.