Korpuslinguistik
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In this article, we examine the current situation of data dissemination and provision for CMC corpora. By that we aim to give a guiding grid for future projects that will improve the transparency and replicability of research results as well as the reusability of the created resources. Based on the FAIR guiding principles for research data management, we evaluate the 20 European CMC corpora listed in the CLARIN CMC Resource family, individuate successful strategies among the existing corpora and establish best practices for future projects. We give an overview of existing approaches to data referencing, dissemination and provision in European CMC corpora, and discuss the methods, formats and strategies used. Furthermore, we discuss the need for community standards and offer recommendations for best practices when creating a new CMC corpus.
Dieser Beitrag beschreibt, welche Schritte nötig sind, um die Daten des Archivs der Grafen v. Platen (AGP) für Forschungsdateninfrastrukturen (FDI) zugänglich zu machen: die Daten konvertieren, die Metadaten extrahieren, Daten und Metadaten indizieren sowie die Datenmodelle für Daten und Metadaten so ergänzen, dass sie die Bestände des Archivs sinnvoll erfassen. Zugleich wird begründet, weshalb man überhaupt solchen Aufwand treiben sollte: nämlich, damit die Daten einem größeren Publikum zur Verfügung stehen und überdies mit Werkzeugen bearbeitet werden können, die in den Infrastrukturen zur Verfügung stehen, und damit eine weitere Verlinkung und Kombination mit externen Ressourcen erfolgen kann, sodass ein deutlicher Mehrwert entstehen kann.
Signposts for CLARIN
(2020)
An implementation of CMDI-based signposts and its use is presented in this paper. Arnold et al. 2020 present Signposts as a solution to challenges in long-term preservation of corpora, especially corpora that are continuously extended and subject to modification, e.g., due to legal injunctions, but also may overlap with respect to constituents, and may be subject to migrations to new data formats. We describe the contribution Signposts can make to the CLARIN infrastructure and document the design for the CMDI profile.
Towards Comprehensive Definitions of Data Quality for Audiovisual Annotated Language Resources
(2020)
Though digital infrastructures such as CLARIN have been successfully established and now provide large collections of digital resources, the lack of widely accepted standards for data quality and documentation still makes re-use of research data a difficult endeavour, especially for more complex resource types. The article gives a detailed overview over relevant characteristics of audiovisual annotated language resources and reviews possible approaches to data quality in terms of their suitability for the current context. Conclusively, various strategies are suggested in order to arrive at comprehensive and adequate definitions of data quality for this particular resource type.
This paper presents the QUEST project and describes concepts and tools that are being developed within its framework. The goal of the project is to establish quality criteria and curation criteria for annotated audiovisual language data. Building on existing resources developed by the participating institutions earlier, QUEST develops tools that could be used to facilitate and verify adherence to these criteria. An important focus of the project is making these tools accessible for researchers without substantial technical background and helping them produce high-quality data. The main tools we intend to provide are the depositors’ questionnaire and automatic quality assurance, both developed as web applications. They are accompanied by a Knowledge base, which will contain recommendations and descriptions of best practices established in the course of the project. Conceptually, we split linguistic data into three resource classes (data deposits, collections and corpora). The class of a resource defines the strictness of the quality assurance it should undergo. This division is introduced so that too strict quality criteria do not prevent researchers from depositing their data.
We present web services which implement a workflow for transcripts of spoken language following the TEI guidelines, in particular ISO 24624:2016 “Language resource management – Transcription of spoken language”. The web services are available at our website and will be available via the CLARIN infrastructure, including the Virtual Language Observatory and WebLicht.
This paper describes the development of a systematic approach to the creation, management and curation of linguistic resources, particularly spoken language corpora. It also presents first steps towards a framework for continuous quality control to be used within external research projects by non-technical users, and discuss various domain and discipline specific problems and individual solutions. The creation of spoken language corpora is not only a time-consuming and costly process, but the created resources often represent intangible cultural heritage, containing recordings of, for example, extinct languages or historical events. Since high quality resources are needed to enable re-use in as many future contexts as possible, researchers need to be provided with the necessary means for quality control. We believe that this includes methods and tools adapted to Humanities researchers as non-technical users, and that these methods and tools need to be developed to support existing tasks and goals of research projects.
This article describes the development of the digital infrastructure at a research data centre for audio-visual linguistic research data, the Hamburg Centre for Language Corpora (HZSK) at the University of Hamburg in Germany, over the past ten years. The typical resource hosted in the HZSK Repository, the core component of the infrastructure, is a collection of recordings with time-aligned transcripts and additional contextual data, a spoken language corpus. Since the centre has a thematic focus on multilingualism and linguistic diversity and provides its service to researchers within linguistics and other disciplines, the development of the infrastructure was driven by diverse usage scenarios and user needs on the one hand, and by the common technical requirements for certified service centres of the CLARIN infrastructure on the other. Beyond the technical details, the article also aims to be a contribution to the discussion on responsibilities and services within emerging digital research data infrastructures and the fundamental issues in sustainability of research software engineering, concluding that in order to truly cater to user needs across the research data lifecycle, we still need to bridge the gap between discipline-specific research methods in the process of digitalisation and generic digital research data management approaches.
In order to satisfy the information needs of a wide range of researchers across a number of disciplines, large textual datasets require careful design, collection, cleaning, encoding, annotation, storage, retrieval, and curation. This daunting set of tasks has coalesced into a number of key themes and questions that are of interest to the contributing research communities: (a) what sampling techniques can we apply? (b) what quality issues should we be aware of? (c) what infrastructures and frameworks are being developed for the efficient storage, annotation, analysis and retrieval of large datasets? (d) what affordances do visualisation techniques offer for the exploratory analysis approaches of corpora? (e) what legal paths can be followed in dealing with IPR and data protection issues governing both the data sources and the query results? (f) how to guarantee that corpus data remain available and usable in a sustainable way?