Abstract
This deep dive on data, knowledge graphs (KGs) and language resources (LRs) is the final of the four technology deep dives, as data as well as related models are the basis for technologies and solutions in the area of Language Technology (LT) for European digital language equality (DLE). This chapter focuses on the data and LRs required to achieve full DLE in Europe by 2030. The main components identified – data, KGs, LRs – are explained, and used to analyse the state-of-the-art as well as identify gaps. All of these components need to be tackled in the future, for the widest range of languages possible, from official EU languages to dialects to non- EU languages used in Europe. For all these languages, efficient data collection and sustainable data provision to be facilitated with fair conditions and costs. Specific technologies, methodologies and tools have been identified to enable the implementation of the vision of DLE by 2030. In addition, data-related business models and data-governance models are discussed, as they are considered a prerequisite for a working data economy that stimulates a vibrant LT landscape that can bring about European DLE.
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Kaltenböck, M. et al. (2023). Deep Dive Data and Knowledge. In: Rehm, G., Way, A. (eds) European Language Equality. Cognitive Technologies. Springer, Cham. https://doi.org/10.1007/978-3-031-28819-7_43
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DOI: https://doi.org/10.1007/978-3-031-28819-7_43
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Publisher Name: Springer, Cham
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