Pret-a-LLOD · Ready-to-use Multilingual Linked Language Data for Knowledge Services across Sectors

Language technologies increasingly rely on large amounts of data and better access and usage of language resources will enable to provide multilingual solutions that would support the emerging Digital Single Market in Europe. However, data is rarely ‘ready-to-use’ and language technology specialists spend over 80% of their time on cleaning, organizing and collecting datasets. Reducing this effort promises huge cost savings for all sectors where language technologies are required. An essential part of the Extract-Transform-Load process involves linking datasets to existing schemas, yet few specialists take advantage of linked data technologies to perform this task. In this project we aim to increase the uptake of language technologies by exploiting the combination of linked data and language technologies, that is Linguistic Linked Open Data (LLOD), to create ready-to-use multilingual data. Prêt-à-LLOD aims to achieve this by creating a new methodology for building data value chains applicable to a wide-range of sectors and applications and based around language resources and language technologies that can be integrated by means of semantic technologies, in particular the usage of Linguistic Linked Open Data (LLOD). The project will develop novel tools for the transformation and linking of datasets, and apply these to both data and metadata in order to provide multi-portal access to heterogeneous data repositories. We will study how we can automatically analyze licenses in order to deduce how data may be lawfully used and sold by language resource providers. Finally, we will provide tools to combine language services and resources into complex pipelines by use of semantic technologies. This will lead to sustainable data offers and services that can be deployed to many platforms, including as-yet-unknown platforms, and can be self-described with linked data semantics. This toolkit will be validated in four pilots, where novel data value chains will be built for pharma