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This paper provides insights into the ongoing international research project Unserdeutsch (Rabaul Creole German): Documentation of a highly endangered creole language in Papua New Guinea, based at the University of Augsburg, Germany. It elaborates on the different stages of the project, ranging from fieldwork to corpus development, thereby outlining the methods and software background used for the intended purposes. In doing so, we also give some approaches to solving specific problems, which have arisen in the course of practical work until now.
The European digital research infrastructure CLARIN (Common Language Resources and Technology Infrastructure) is building a Knowledge Sharing Infrastructure (KSI) to ensure that existing knowledge and expertise is easily available both for the CLARIN community and for the humanities research communities for which CLARIN is being developed. Within the Knowledge Sharing Infrastructure, so called Knowledge Centres comprise one or more physical institutions with particular expertise in certain areas and are committed to providing their expertise in the form of reliable knowledge-sharing services. In this paper, we present the ninth K Centre – the CLARIN Knowledge Centre for Linguistic Diversity and Language Documentation (CKLD) – and the expertise and services provided by the member institutions at the Universities of London (ELAR/SWLI), Cologne (DCH/IfDH/IfL) and Hamburg (HZSK/INEL). The centre offers information on current best practices, available resources and tools, and gives advice on technological and methodological matters for researchers working within relevant fields.
The QUEST (QUality ESTablished) project aims at ensuring the reusability of audio-visual datasets (Wamprechtshammer et al., 2022) by devising quality criteria and curating processes. RefCo (Reference Corpora) is an initiative within QUEST in collaboration with DoReCo (Documentation Reference Corpus, Paschen et al. (2020)) focusing on language documentation projects. Previously, Aznar and Seifart (2020) introduced a set of quality criteria dedicated to documenting fieldwork corpora. Based on these criteria, we establish a semi-automatic review process for existing and work-in-progress corpora, in particular for language documentation. The goal is to improve the quality of a corpus by increasing its reusability. A central part of this process is a template for machine-readable corpus documentation and automatic data verification based on this documentation. In addition to the documentation and automatic verification, the process involves a human review and potentially results in a RefCo certification of the corpus. For each of these steps, we provide guidelines and manuals. We describe the evaluation process in detail, highlight the current limits for automatic evaluation and how the manual review is organized accordingly.