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Bibliographical data are one of the most important types of data for data-driven research and curation in the humanities. The goal of the panel is to introduce various aspects of current bibliographical data ecosystem which is shaped by constant interactions between various public and private stakeholders.

The presentation was held during the Mutual Learning Workshop for Improving Cultural Heritage Bibliographical Data (October 12-14, 2022) organised by the Bibliographical Data Working Group of the DARIAH-ERIC., The Mutual Learning Workshop for Improving Cultural Heritage Bibliographical Data has been supported by the DARIAH ERIC.

Rights management for language resources, CA18209 - European network for Web-centred linguistic data science (NexusLinguarum) 825182 - Ready-to-use Multilingual Linked Language Data for Knowledge Services across Sectors

This article provides a comprehensive and up-to-date survey of models and vocabularies for creating linguistic linked data (LLD) focusing on the latest developments in the area and both building upon and complementing previous works covering similar territory. The article begins with an overview of some recent trends which have had a significant impact on linked data models and vocabularies. Next, we give a general overview of existing vocabularies and models for different categories of LLD resource. After which we look at some of the latest developments in community standards and initiatives including descriptions of recent work on the OntoLex-Lemon model, a survey of recent initiatives in linguistic annotation and LLD, and a discussion of the LLD metadata vocabularies META-SHARE andlime. In the next part of the paper, we focus on the influence of projects on LLD models and vocabularies, starting with a general survey of relevant projects, before dedicating individual sections to a number of recent projects and their impact on LLD vocabularies and models. Finally, in the conclusion, we look ahead at some future challenges for LLD models and vocabularies. The appendix to the paper consists of a brief introduction to the OntoLex-Lemon model.

This paper describes the current status of the emerging OntoLex module for linguistic morphology. It serves as an update to the previous version of the vocabulary (Klimek et al. 2019). Whereas this earlier model was exclusively focusing on descriptive morphology and focused on applications in lexicography, we now present a novel part and a novel application of the vocabulary to applications in language technology, i.e., the rule-based generation of lexicons, introducing a dynamic component into OntoLex.

The article analyses the responsibility for ensuring compliance with the General Data Protection Regulation (GDPR) in research settings. As a general rule, organisations are considered the data controller (responsible party for the GDPR compliance). Research constitutes a unique setting influenced by academic freedom. This raises the question of whether academics could be considered the controller as well. However, there are some court cases and policy documents on this issue. It is not settled yet. The analysis serves a preliminary analytical background for redesigning CLARIN contractual framework for sharing data.

With 24 official EU and many additional languages, multilingualism in Europe and an inclusive Digital Single Market can only be enabled through Language Technologies (LTs). European LT business is dominated by hundreds of SMEs and a few large players. Many are world-class, with technologies that outperform the global players. However, European LT business is also fragmented, by nation states, languages, verticals and sectors, significantly holding back its impact. The European Language Grid (ELG) project addresses this fragmentation by establishing the ELG as the primary platform for LT in Europe. The ELG is a scalable cloud platform, providing, in an easy-to-integrate way, access to hundreds of commercial and non-commercial LTs for all European languages, including running tools and services as well as data sets and resources. Once fully operational, it will enable the commercial and non-commercial European LT community to deposit and upload their technologies and data sets into the ELG, to deploy them through the grid, and to connect with other resources. The ELG will boost the Multilingual Digital Single Market towards a thriving European LT community, creating new jobs and opportunities. Furthermore, the ELG project organises two open calls for up to 20 pilot projects. It also sets up 32 National Competence Centres (NCCs) and the European LT Council (LTC) for outreach and coordination purposes., Comment: Proceedings of the 12th Language Resources and Evaluation Conference (LREC 2020). To appear

This article aims to explain the extent to which the legal regime applicable to language data affects the development and use of language models. In their approach, the authors follow a process chart, starting from raw data to finished products containing language technology (eg a refrigerator with a speech interface). The raw data used in language technologies often include copyrighted works, objects of related rights (performances, sound recordings) and personal data (voice, other information about the person) stored in non-annotated and annotated databases. The legal issues of language data have already been studied. However, the legal aspects of language models have not been throughly explored. The authors are of the opinion that, as a rule, the legal status of the language models is not affect by the legal status of the used raw language data, since copyrighted works usually do not remain in the model. However, the use of a person’s voice in a language model can create legal problems. The authors analyze possible solutions to overcome these problems. The article also outlines the regulation of data mining introduced by the new copyright directive and its implementation in the context of development of language models.

Europe is a multilingual society with 24 EU Member State languages and dozens of additional languages including regional and minority languages and languages spoken by immigrants and trade partners. While languages are an essential part of our cultural heritage, language barriers continue to be unbreachable in many situations. The only option to enable and to benefit from multilingualism is through Language Technologies (LT) including Natural Language Processing (NLP) and Speech Technologies. The commercial European LT landscape is dominated by hundreds of SMEs. While the academic and industrial European LT community is world class, it is also massively fragmented. We describe the European Language Grid (ELG), Release 2. The system is targeted to evolve into the primary platform and marketplace for LT in Europe by providing one umbrella platform for the European LT landscape, including research and industry, enabling all stakeholders to showcase, share and distribute their services, products and resources. At the end of our EU-funded project, which will establish a legal entity in late 2021, the ELG will provide access to approx. 1300 commercial and non-commercial services for all European languages, as well as thousands of language resources (LRs). ELG will enable the whole European LT community to upload their technologies and resources and to deploy them through the ELG. The ELG is also meant to support digital language equality in Europe, i.e., to foster a situation in which all languages are supported through technologies equally well. We currently still have an extreme imbalance, characterised by a stark predominance of LTs for English.

With 24 official EU and many additional languages, multilingualism in Europe and an inclusive Digital Single Market can only be enabled through Language Technologies (LTs). European LT business is dominated by hundreds of SMEs and a few large players. Many are world-class, with technologies that outperform the global players. However, European LT business is also fragmented – by nation states, languages, verticals and sectors, significantly holding back its impact. The European Language Grid (ELG) project addresses this fragmentation by establishing the ELG as the primary platform for LT in Europe. The ELG is a scalable cloud platform, providing, in an easy-to-integrate way, access to hundreds of commercial and non-commercial LTs for all European languages, including running tools and services as well as data sets and resources. Once fully operational, it will enable the commercial and non-commercial European LT community to deposit and upload their technologies and data sets into the ELG, to deploy them through the grid, and to connect with other resources. The ELG will boost the Multilingual Digital Single Market towards a thriving European LT community, creating new jobs and opportunities. Furthermore, the ELG project organises two open calls for up to 20 pilot projects. It also sets up 32 national competence centres and the European LT Council for outreach and coordination purposes.

The article aims to increase legal clarity concerning the impact of data containing copyrighted content and personal data on the development of language technologies. The question is whether legal rights covering data affect language models.

The OpenMinTeD platform aims to bring full text Open Access scholarly content from a wide range of providers together with Text and Data Mining (TDM) tools from various Natural Language Processing frameworks and TDM developers in an integrated environment. In this way, it supports users who want to mine scientific literature with easy access to relevant content and allows running scalable TDM workflows in the cloud.

This article investigates the compatibility of the current CLARIN license categorization scheme with the open science paradigm. The first part presents the main concepts and theoretical framework required for the analysis, while the second part discusses the use of the CLARIN categorization system, divided into PUB (public), ACA (academic), and RES (restricted), and potential ways to change it. This paper serves to explore various suggestions for change and to begin discussion of a reformed CLARIN license category scheme.

A significant concern in processing natural language data is the often unclear legal status of the input and output data/resources. In this paper, we investigate this problem by discussing a typical activity in Natural Language Processing: the training of a machine learning\ud model from an annotated corpus. We examine which legal rules apply at relevant steps and how they affect the legal status of the results, especially in terms of copyright and copyright-related rights.

In this paper, we describe a generic language resources infrastructure providing language data and language processing services, as well as different instances of the infrastructure catering for different communities, operational frameworks and constraints. We maintain that similar approaches can be employed to support and systematize the storage, documentation, archiving and long-term maintenance of scientific publications, as well as their discoverability, uniform access and processing through interoperable text mining services, and conclude with a discussion of the merits of the approach.

This paper is a first analysis of the legal interoperability issues in the framework of the OpenMinTeD (OMTD) project (www.openminted.eu), which aims to create an open, service-oriented e-Infrastructure for Text and Data Mining (TDM) of scientific and scholarly content. The paper offers an overview into the methods for achieving such interoperability.

This paper presents the metadata schema for describing language resources (LRs) currently under development for the needs of META-SHARE, an open distributed facility for the exchange and sharing of LRs. An essential ingredient in its setup is the existence of formal and standardized LR descriptions, cornerstone of the interoperability layer of any such initiative. The description of LRs is granular and abstractive, combining the taxonomy of LRs with an inventory of a structured set of descriptive elements, of which only a minimal subset is obligatory; the schema additionally proposes recommended and optional elements. Moreover, the schema includes a set of relations catering for the appropriate inter-linking of resources. The current paper presents the main principles and features of the metadata schema, focusing on the description of text corpora and lexical / conceptual resources.