The CLARIN-CH FAIRification pipeline

At CLARIN-CH, the Swiss national node of the European CLARIN research infrastructure, we are actively engaged in promoting the FAIR principles, making linguistic and language-based research data Findable, Accessible, Interoperable, and Reusable. Our FAIR-ification pipeline is a hands-on, researcher-centric approach that assists scholars in enhancing the long-term usability and visibility of their language data.

1. Outreach

Our engagement begins with personalised outreach. Researchers are contacted directly and invited to consider four options for making their data FAIR-compliant. These options are not mutually exclusive and include:

European CLARIN research infrastructure
FAIR principles and data
The CLARIN-CH FAIRification pipeline: a researcher-centered process supporting outreach, consultation, data transformation, and archiving to ensure FAIR-compliant language resources.

SWISSUbase

Publishing and archiving datasets on SWISSUbase, a national, FAIR-compliant repository harvested by CLARIN’s Virtual Language Observatory (VLO), ideal for finalised datasets requiring long-term preservation in compliance with SNSF requirements and FAIR principles.
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LiRI Corpus Platform (LCP)

LiRI Corpus Platform (LCP)

Contributing to the LiRI Corpus Platform (LCP), a corpus analysis environment hosted by the Linguistic Research Infrastructure (LiRI), particularly suitable for corpora that would benefit from web-based querying and corpus-linguistic analysis. This makes a resource immediately available for queries of various complexity and is especially useful when the raw data cannot be shared for legal or other reasons.
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SSH Open Marketplace

Showcasing resources via the SSH Open Marketplace, recommended for tools, services, and workflows that support reuse and method visibility across the social sciences and humanities.
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Resource Families

CLARIN Resource Families

Featuring datasets on the CLARIN Resource Families webpage, best suited for mature resources that fit within established categories like treebanks, speech corpora, or multilingual lexicons, and where increased international visibility is desired.
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2. Consultation & evaluation

Once a researcher expresses interest, we schedule a consultation to review their data and determine the best dissemination pathway. We evaluate the state of the dataset, including format, completeness of metadata, and potential need for preprocessing. For example, preparing a dataset for the LCP may require transforming files into a specific format of a set of relational CSV files, a task that can be challenging for researchers unfamiliar with tools such as Python or R. 

3. Transformation & archiving

Where needed, CLARIN-CH provides direct assistance in formatting, metadata enrichment, and the technical steps required for depositing. In some cases, especially for concluded projects where researchers lack the time or capacity, we manage the entire FAIRification process on their behalf to avoid the loss of a resource or tool.

Beyond one-on-one collaboration…

CLARIN-CH also supports the broader research community through thematic working groups, training activities, and extensive documentation. We facilitate interdisciplinary working groups on sensitive data management, learner corpora, and legal- ethical challenges, acting as intermediaries to support collaboration and project development. Our training activities cover topics from corpus querying and statistical methods to multimodal data processing. In addition, we maintain a comprehensive documentation platform that provides best practices across the entire data lifecycle, helping researchers see the full picture of sustainable and reusable data management.