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This White Paper sets out commonly agreed definitions on activities of consortia within NFDI. It aims to provide a common basis for reporting and reference regarding selected questions of cross-consortial relevance in DFG’s template for the Interim Reports. The questions were prioritised by an NFDI Task Force on Evaluation and Reporting (formerly Task Force Monitoring) as a result of discussing possible answers to the DFG template. In this process the need to agree on a generalizable meaning of terms commonly used in the context of NFDI, and reporting in particular, were identified from cross-consortial perspectives. Questions that showed the highest requirement on clarification are discussed in this White Paper. As NFDI evolves, the Task Force will likely propose further joint approaches for reporting in information infrastructures.
While each of broad relevance, the questions addressed relate to substantially different aspects of consortia’s work. They are thus also structured slightly different.
In der Bund-Länder-Vereinbarung (BLV) zu Aufbau und Förderung einer Nationalen Forschungsdateninfrastruktur (NFDI) (im Folgenden BLV-NFDI) wird in §1 festgehalten, dass mit der Förderung "eine Etablierung und Fortentwicklung eines übergreifenden Forschungsdatenmanagements" und damit eine "Steigerung der Effizienz des gesamten Wissenschaftssystems verfolgt" wird. In der BLV-NFDI werden dazu sieben Ziele vorgegeben, die eine Verfeinerung dieser Hauptziele darstellen. Dieses White Paper formuliert das gemeinsame Verständnis der beteiligten Konsortien für die sieben in der BLV-NFDI vorgegebenen Ziele. Auf der Grundlage dieses Verständnisses hat die Task Force Evaluation und Reporting Vorschläge gemacht, wie das Erreichen der Ziele erfasst, beschrieben und gemessen werden kann.
Collaborative work in NFDI
(2023)
The non-profit association National Research Data Infrastructure (NFDI) promotes science and research through a National Research Data Infrastructure. Its aim is to develop and establish an overarching research data management (RDM) for Germany and to increase the efficiency of the entire German science system. After a two-and-a-half year build up phase, the process of adding new consortia, each representing a different data domain, has ended in March 2023. NFDI now has 26 disciplinary consortia (and one additional basic service collaboration). Now the full extent of cross-consortial interaction is beginning to show.
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.
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 also 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 a questionnaire and automatic quality assurance for depositors of language resources, 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 consider three main data maturity levels in order to decide on a suitable level of strictness of the quality assurance. This division has been introduced to avoid that a set of ideal quality criteria prevent researchers from depositing or even assessing their (legacy) data. The tools described in the paper are work in progress and are expected to be released by the end of the QUEST project in 2022.
The CMDI Explorer
(2020)
We present the CMDI Explorer, a tool that empowers users to easily explore the contents of complex CMDI records and to process selected parts of them with little effort. The tool allows users, for instance, to analyse virtual collections represented by CMDI records, and to send collection items to other CLARIN services such as the Switchboard for subsequent processing. The CMDI Explorer hence adds functionality that many users felt was lacking from the CLARIN tool space.
CMDI Explorer
(2021)
We present CMDI Explorer, a tool that empowers users to easily explore the contents of complex CMDI records and to process selected parts of them with little effort. The tool allows users, for instance, to analyse virtual collections represented by CMDI records, and to send collection items to other CLARIN services such as the Switchboard for subsequent processing. CMDI Explorer hence adds functionality that many users felt was lacking from the CLARIN tool space.
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.
Signposts for CLARIN
(2021)
An implementation of CMDI-based signposts and its use is presented in this paper. Arnold, Fisseni et al. (2020) present signposts as a solution to challenges in long-term preservation of corpora. Though applicable to digital resources in general, we focus on corpora, especially those that are continuously extended or 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, notably virtual collections, and document the design for the CMDI profile.
In diesem Beitrag widmen wir uns der Frage, welche Schritte unternommen werden müssen, um Skripte, die bei der Aufbereitung und/oder Auswertung von Forschungsdaten Anwendung finden, so FAIR wie möglich zu gestalten. Dabei nehmen wir sowohl Reproduzierbarkeit, also den Weg von den (Roh)daten zu den Ergebnissen einer Studie, als auch Wiederverwertbarkeit, also die Möglichkeit, die Methoden einer Studie mittels des Skripts auf andere Daten anzuwenden, in den Fokus und beleuchten dabei die folgenden Aspekte: Arbeitsumgebung, Datenvalidierung, Modularisierung, Dokumentation und Lizenz.
Wenn man verschiedenartige Forschungsdaten über Metadaten inhaltlich beschreiben möchte, sind bibliografische Angaben allein nicht ausreichend. Vielmehr benötigt man zusätzliche Beschreibungsmittel, die der Natur und Komplexität gegebener Forschungsressourcen Rechnung tragen. Verschiedene Arten von Forschungsdaten bedürfen verschiedener Metadatenprofile, die über gemeinsame Komponenten definiert werden. Solche Forschungsdaten können gesammelt (z.B. über OAI-PMH-Harvesting) und mittels Facetten-basierter Suche über eine einheitliche Schnittstelle exploriert werden. Der beschriebene Anwendungskontext kann über sprachwissenschaftliche Daten hinaus verallgemeinert werden.
Linguistics is facing the challenge of many other sciences as it continues to grow into increasingly complex subfields, each with its own separate or overarching branches. While linguists are certainly aware of the overall structure of the research field, they cannot follow all developments other than those of their subfields. It is thus important to help specialists but also newcomers alike to bushwhack through evolved or unknown territory of linguistic data. A considerable amount of research data in linguistics is described with metadata. While studies described and published in archived journals and conference proceedings receive a quite homogeneous set of metadata tags — e.g., author, title, publisher —, this does not hold for the empirical data and analyses that underlie such studies. Moreover, lexicons, grammars, experimental data, and other types of resources come in different forms; and to make things worse, their description in terms of metadata is also not uniform, if existing at all. These problems are well-known and there are now a number of international initiatives — e.g., CLARIN, FlareNet, MetaNet, DARIAH — to build infrastructures for managing linguistic resources. The NaLiDa project, funded by the German Research Foundation, aims at facilitating the management and access to linguistic resources originating from German research institutions. In cooperation with the German SFB 833 research center, we are developing a combination of faceted and full-text search to give integrated access through heterogeneous metadata sets. Our approach is supported by a central registry for metadata field descriptors, and a component repository for structured groups of data categories as larger building blocks.
The proposed contribution will shed light on current and future challenges on legal and ethical questions in research data infrastructures. The authors of the proposal will present the work of NFDI’s section on Ethical, Legal and Social Aspects (hereinafter: ELSA), whose aim is to facilitate cross-disciplinary cooperation between the NFDI consortia in the relevant areas of management and re-use of research data.
Forschungsprojekte erschließen, erfassen und publizieren eine große Menge digitaler Daten. Bis zur Publikation entstehen häufig Vorarbeiten oder auch Nebenprodukte des beabsichtigten Ergebnisses (beispielsweise Transkriptionen einzelner Texte oder Textzeugen, die die Grundlage z.B. für eine Edition bilden). CLARIAH-DE bietet verschiedene Möglichkeiten zur Integration von Angeboten und Inhalten aus der Community, die deren längerfristige Sicht- und Nachnutzbarkeit sicherstellt. Die vorliegende Handreichung befasst sich mit den Fragen, welche Textangebote wo und auf welche Weise archiviert werden können, sowie welche Kriterien verschiedene Arten von Daten erfüllen müssen, um grundsätzlich für eine Übernahme in den CLARIAH-DE-, Forschungsdatenmanagement- oder NFDI-Kontext geeignet zu sein.
This paper presents the system architecture as well as the underlying workflow of the Extensible Repository System of Digital Objects (ERDO) which has been developed for the sustainable archiving of language resources within the Tübingen CLARIN-D project. In contrast to other approaches focusing on archiving experts, the described workflow can be used by researchers without required knowledge in the field of long-term storage for transferring data from their local file systems into a persistent repository.
Gerade wenn es um die Gewinnung und eine erste Bewertung von Forschungsdaten geht, ist derzeit oft vom Übergang zu citizen science die Rede. Nachdem dieses Konzept zunächst in den Lebenswissenschaften eine größere Rolle gespielt hat, findet es sich neuerdings auch in Teilen der Sprachwissenschaft. Viele einschlägige Initiativen schließen an die Tätigkeiten an, bei denen sich auch traditionell schon die professionalisierte Wissenschaft der Hilfe der ‚Laien‘ bediente, sie können allerdings jetzt die in ungeahntem Ausmaß gewachsenen Möglichkeiten elektronischer Kommunikation und elektronischen Daten-Managements nutzen. Das digitale Interagieren erweitert die Möglichkeiten der als beteiligte „Laien“ gesehenen Personen aber doch so sehr, dass sich auch qualitativ ein neues Verhältnis zwischen den am Forschungsprozess Beteiligten entwickelt. In diesem Beitrag wird diskutiert, welche Folgen diese Veränderung für die wissenschaftliche Praxis, aber auch für das Verständnis des Konzepts „Wissenschaft“ hat.
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.
In unserem Beitrag diskutieren wir Aspekte einer Forschungsdateninfrastruktur für den wissenschaftlichen Alltag auf Projektebene und argumentieren für eine Unterstützung von Projekten während der Erfassung und Bearbeitung von Daten, d. h. vor deren endgültiger Veröffentlichung. Dabei differenzieren wir zwischen Projekten, deren primäres Ziel es ist, eine Ressource aufzubauen (ressourcenschaffende Projekte, kurz RP) und solchen, die zur Beantwortung einer konkreten Forschungsfrage Daten sammeln und auswerten (Forschungsprojekte, kurz FP). Wir argumentieren dafür, dass bei den offenkundigen Unterschieden zwischen beiden Projektarten die grundsätzlichen Ansprüche an das alltägliche Forschungsdatenmanagement im Kern sehr ähnlich (wenn auch unterschiedlich akzentuiert und skaliert) sind. Diese Ähnlichkeit rührt nicht zuletzt daher, dass im Rahmen von FP gesammelte Daten in Bezug auf das Projektziel primär Mittel zum Zweck sein mögen, sie jedoch bereits im Arbeitsprozess in unterschiedlichem Maß von unterschiedlichen Beteiligten genutzt werden. Wir gehen konkret auf die Aspekte Datenorganisation und -verwaltung, Metadaten, Dokumentation und Dateiformate und deren Anforderungen in den verschiedenen Projekttypen ein. Schließlich diskutieren wir Lösungsansätze dafür, Aspekte des Forschungsdatenmanagements auch in (kleineren) Forschungsprojekten nicht post-hoc, sondern bereits in der Projektplanung als Teil der alltäglichen Arbeit zu berücksichtigen und entsprechende Unterstützung in der Forschungsinfrastruktur vorzusehen.
In unserem Beitrag diskutieren wir Aspekte einer Forschungsdateninfrastruktur für den wissenschaftlichen Alltag auf Projektebene und argumentieren für eine Unterstützung von Projekten während der Erfassung und Bearbeitung von Daten, d. h. vor deren endgültiger Veröffentlichung. Dabei differenzieren wir zwischen Projekten, deren primäres Ziel es ist, eine Ressource aufzubauen (ressourcenschaffende Projekte, kurz RP) und solchen, die zur Beantwortung einer konkreten Forschungsfrage Daten sammeln und auswerten (Forschungsprojekte, kurz FP). Wir argumentieren dafür, dass bei den offenkundigen Unterschieden zwischen beiden Projektarten die grundsätzlichen Ansprüche an das alltägliche Forschungsdatenmanagement im Kern sehr ähnlich (wenn auch unterschiedlich akzentuiert und skaliert) sind. Diese Ähnlichkeit rührt nicht zuletzt daher, dass im Rahmen von FP gesammelte Daten in Bezug auf das Projektziel primär Mittel zum Zweck sein mögen, sie jedoch bereits im Arbeitsprozess in unterschiedlichem Maß von unterschiedlichen Beteiligten genutzt werden. Wir gehen konkret auf die Aspekte Datenorganisation und -verwaltung, Metadaten, Dokumentation und Dateiformate und deren Anforderungen in den verschiedenen Projekttypen ein. Schließlich diskutieren wir Lösungsansätze dafür, Aspekte des Forschungsdatenmanagements auch in (kleineren) Forschungsprojekten nicht post-hoc, sondern bereits in der Projektplanung als Teil der alltäglichen Arbeit zu berücksichtigen und entsprechende Unterstützung in der Forschungsinfrastruktur vorzusehen.
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.
The theme of the AFinLA 2020 Yearbook Methodological turns in applied language studies is discussed in this introductory article from three interrelated perspectives, variously addressed in the three plenary presentations at the AFinLA Autumn Symposium 2019 as well as in the thirteen contributions to the yearbook. In the first set of articles presented, the authors examine the role and impact of technological development on the study of multimodal digital and non-digital contexts and discourses and ensuing new methods. The second set of studies in the yearbook revisits issues of language proficiency, critically discussing relevant concepts and approaches. The third set of articles explores participation and participatory research approaches, reflecting on the roles of the researcher and the researched community.
Making research data publicly available for evaluation or reuse is a fundamental part of good scientific practice. However, regulations such as copyright law can prevent this practice and thereby hamper scientific progress. In Germany, text-based research disciplines have for a long time been mostly unable to publish corpora made from material outside of the public domain, effectively excluding contemporary works. While there are approaches to obfuscate text material in a way that it is no longer covered by the original copyright, many use cases still require the raw textual context for evaluation or follow-up research. Recent changes in copyright now permit text and data mining on copyrighted works. However, questions regarding reusability and sharing of such corpora at a later time are still not answered to a satisfying degree. We propose a workflow that allows interested third parties to access customized excerpts of protected corpora in accordance with current German copyright law and the soon to be implemented guidelines of the Digital Single Market directive. Our prototype is a very lightweight web interface that builds on commonly used repository software and web standards.
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.
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.
Towards comprehensive definitions of data quality for audiovisual annotated language resources
(2021)
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 specific resource type and possibly for digital language resources in general.
This paper describes the TEI-based ISO standard 24624:2016 ‘Transcription of spoken language’ and other formats used within CLARIN for spoken language resources. It assesses the current state of support for the standard and the interoperability between these formats and with rele- vant tools and services. The main idea behind the paper is that a digital infrastructure providing language resources and services to researchers should also allow the combined use of resources and/or services from different contexts. This requires syntactic and semantic interoperability. We propose a solution based on the ISO/TEI format and describe the necessary steps for this format to work as an exchange format with basic semantic interoperability for spoken language resources across the CLARIN infrastructure and beyond.
N-grams are of utmost importance for modern linguistics and language theory. The legal status of n-grams, however, raises many practical questions. Traditionally, text snippets are considered copyrightable if they meet the originality criterion, but no clear indicators as to the minimum length of original snippets exist; moreover, the solutions adopted in some EU Member States (the paper cites German and French law as examples) are considerably different. Furthermore, recent developments in EU law (the CJEU's Pelham decision and the new right of newspaper publishers) also provide interesting arguments in this debate. The proposed paper presents the existing approaches to the legal protection of n-grams and tries to formulate some clear guidelines as to the length of n-grams that can be freely used and shared.
Twitter data is used in a wide variety of research disciplines in Social Sciences and Humanities. Although most Twitter data is publicly available, its re-use and sharing raise many legal questions related to intellectual property and personal data protection. Moreover, the use of Twitter and its content is subject to the Terms of Service, which also regulate re-use and sharing. This extended abstract provides a brief analysis of these issues and introduces the new Academic Research product track, which enables authorized researchers to access Twitter API on a preferential basis.
Open Science and language data: Expectations vs. reality. The role of research data infrastructures
(2023)
Language data are essential for any scientific endeavor. However, unlike numerical data, language data are often protected by copyright, as they easily meet the threshold of originality. The role of research infrastructures (such CLARIN, DARIAH, and Text+) is to bridge the gap between uses allowed by statutory exceptions and the requirements of Open Science. This is achieved on the one hand by sharing language data produced by research organisations with the widest possible circle of persons, and on the other by mutualizing efforts towards copyright clearance and appropriate licensing of datasets.
The General Data Protection Regulation (hereinafter: GDPR), EU Regulation 2016/679 of 27 April 2016, will become applicable on 25 May 2018 and repeal the Personal Data Directive of 24 October 1995.
Unlike a directive, which requires transposition into national laws (while leaving the choice of “forms and methods” to the Member States), a regulation is binding and directly applicable in all Member States. This means that when the GDPR becomes applicable, all the EU countries will have the same rules regarding the protection of personal data — at least in principle, since some details (including in the area of research — see below) are expressly left to the discretion of the Member States.
The GDPR is a particularly ambitious piece of legislation (consisting of 99 articles and 173 recitals) whose intended territorial scope extends beyond the borders of the European Union. Its main concepts and principles are essentially similar to those of the Personal Data Directive, but enriched with interpretation developed through the case law of the CJEU and the opinions of the Article 29 Data Protection Working Party (hereinafter: WP29).
This White Paper will discuss the main principles of data protection and their impact on language resources, as well as special rules regarding research under the GDPR and the standardisation mechanisms recognized by the Regulation.
Providing online repositories for language resources is one of the main activities of CLARIN centres. The legal framework regarding liability of Service Providers for content uploaded by their users has recently been modified by the new Directive on Copyright in the Digital Single Market. A new category of Service Providers, Online Content-Sharing Service Providers (OCSSPs), was added. It is subject to a complex and strict framework, including the requirement to obtain licenses from rightholders for the hosted content. This paper provides the background and effect of these changes to law and aims to initiate a debate on how CLARIN repositories should navigate this new legal landscape.
The debate on the use of personal data in language resources usually focuses — and rightfully so — on anonymisation. However, this very same debate usually ends quickly with the conclusion that proper anonymisation would necessarily cause loss of linguistically valuable information. This paper discusses an alternative approach — pseudonymisation. While pseudonymisation does not solve all the problems (inasmuch as pseudonymised data are still to be regarded as personal data and therefore their processing should still comply with the GDPR principles), it does provide a significant relief, especially — but not only — for those who process personal data for research purposes. This paper describes pseudonymisation as a measure to safeguard rights and interests of data subjects under the GDPR (with a special focus on the right to be informed). It also provides a concrete example of pseudonymisation carried out within a research project at the Institute of Information Technology and Communications of the Otto von Guericke University Magdeburg.
Sometimes legal scholars get relevant but baffling questions from laypersons like: “The reference to a work is personal data, so does the GDPR actually require me to anonymise it? Or, as my voice data is personal data, does the GDPR automatically give me access to a speech recognizer using my voice sample? Or, can I say anything about myself without the GDPR requiring the web host to anonymise or remove the post? What can I say about others like politicians? And, what can researchers say about patients in a research report?” Based on these questions, the authors address the interaction of intellectual property and data protection law in the context of data minimisation and attribution rights, access rights, trade secret protection, and freedom of expression.
CLARIN contractual framework for sharing language data: the perspective of personal data protection
(2020)
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.
In dem auf die Forschungsdaten sprach- und textbasierter Disziplinen ausgerichteten NFDI-Konsortium Text+ spielen Normdaten eine zentrale Rolle für die interoperable Beschreibung und semantische Verknüpfung von verteilten Datenquellen. Insbesondere die Gemeinsame Normdatei (GND) ist ein bedeutender Hub im Zentrum eines im Entstehen begriffenen, domänenübergreifenden Wissensgraphen. Diese Funktion soll im Rahmen von Text+ durch den Aufbau einer GND-Agentur für sprach- und textbasierte Forschungsdaten weiterentwickelt und ausgebaut werden. Ziel ist es, niedrigschwellige, qualitätsgesicherte Beteiligungsmöglichkeiten für Forschende zu schaffen und zugleich den Vernetzungsgrad der GND auch durch Terminologie-Mappings zu erweitern. Spezifische Anforderungen und Nutzungspraktiken werden hierbei anhand der Datendomänen von Text+ exemplifziert.
This contribution summarizes the lessons learned from the organization of a joint conference on text analytics research by the Business, Economic, and Related Data (BERD@NFDI) and Text+ consortia within the National Research Data Infrastructure (NFDI) in Germany. The collaboration aimed to identify common ground and foster interdisciplinary dialogue between scholars in the humanities and in the business domain. The lessons learned include the importance of presenting research questions using textual data to establish common ground, similarities in methodology for processing textual data between the consortia, similarities in research data management, and the need for regular interconsortial discussions on textual analysis methods and data. The collaboration proved valuable for interdisciplinary dialogue within the NFDI, and further collaboration between the consortia is planned.
This paper reports on recent developments within the European Reference Corpus EuReCo, an open initiative that aims at providing and using virtual and dynamically definable comparable corpora based on existing national, reference or other large corpora. Given the well-known shortcomings of other types of multilingual corpora such as parallel/translation corpora (shining-through effects, over-normalization, simplification, etc.) or web-based comparable corpora (covering only web material), EuReCo provides a unique linguistic resource offering new perspectives for fine-grained contrastive research on authentic cross-linguistic data, applications in translation studies and foreign language teaching and learning.
The landscape of digital lexical resources is often characterized by dedicated local portals and proprietary interfaces as primary access points for scholars and the interested public. In addition, legal and technical restrictions are potential issues that can make it difficult to efficiently query and use these valuable resources. As part of the research data consortium Text+, solutions for the storage and provision of digital language resources are being developed and provided in the context of the unified cross-domain German research data infrastructure NFDI. The specific topic of accessing lexical resources in a diverse and heterogenous landscape with a variety of participating institutions and established technical solutions is met with the development of the federated search and query framework LexFCS. The LexFCS extends the established CLARIN Federated Content Search that already allows accessing spatially distributed text corpora using a common specification of technical interfaces, data formats, and query languages. This paper describes the current state of development of the LexFCS, gives an insight into its technical details, and provides an outlook on its future development.
Als Teil der NFDI vernetzt Text+ ortsverteilt verschiedenste Daten und Dienste für die geisteswissenschaftliche Forschung und stellt sie der wissenschaftlichen Gemeinschaft FAIR zur Verfügung. In diesem Beitrag beschreiben wir die Umsetzung beispielhaft im Bereich der Text+ Datendomäne Sammlungen anhand von Korpora, die in verschiedenen Disziplinen Verwendung finden. Die Infrastruktur ist auf Erweiterbarkeit ausgelegt, so dass auch weitere Ressourcen über Text+ verfügbar gemacht werden können. Enthalten ist auch ein Ausblick auf weitere zu erwartende Entwicklungen. Ein Beitrag zur 9. Tagung des Verbands "Digital Humanities im deutschsprachigen Raum" - DHd 2023 Open Humanities Open Culture.
In diesem Panel geht es um die Förderung der geisteswissenschaftlichen Forschung durch eine planvolle Erhebung, Archivierung, Veröffentlichung und die dadurch ermöglichte Nachnutzung von Forschungsdaten, die sowohl zur Qualitätssicherung in der Forschung beitragen als auch nicht zuletzt neue Fragestellungen erlauben. Aus unterschiedlichen Perspektiven soll in dem Panel beleuchtet werden, welchen Mehrwert das Datenmanagement für die Forschung in den digitalen Geisteswissenschaften hat, wie man diesen Mehrwert erreicht und auch die Veröffentlichung der Forschungsdaten als ein selbstverständliches Element der Dissemination der Forschungsergebnisse etabliert und wie man gleichzeitig den Aufwand für die Forschung abschätzen kann.
In this article, we describe a user support solution for the digital humanities. As a case study, we show the development of the CLARIN-D Helpdesk from 2013 into the current support solution that has been extended for several other CLARIN-related software and projects and the DARIAH-ERIC. Furthermore, we describe a way towards a common support platform for CLARIAH-DE, which is currently in the final phase. We hope to further expand the help desk in the following years in order to act as a hub for user support and a central knowledge resource for the digital humanities not only in the German, but also in the European area and perhaps at some point worldwide.
Song lyrics can be considered as a text genre that has features of both written and spoken discourse, and potentially provides extensive linguistic and cultural information to scientists from various disciplines. However, pop songs play a rather subordinate role in empirical language research so far - most likely due to the absence of scientifically valid and sustainable resources. The present paper introduces a multiply annotated corpus of German lyrics as a publicly available basis for multidisciplinary research. The resource contains three types of data for the investigation and evaluation of quite distinct phenomena: TEI-compliant song lyrics as primary data, linguistically and literary motivated annotations, and extralinguistic metadata. It promotes empirically/statistically grounded analyses of genre-specific features, systemic-structural correlations and tendencies in the texts of contemporary pop music. The corpus has been stratified into thematic and author-specific archives; the paper presents some basic descriptive statistics, as well as the public online frontend with its built-in evaluation forms and live visualisations.
Digital research infrastructures can be divided into four categories: large equipment, IT infrastructure, social infrastructure, and information infrastructure. Modern research institutions often employ both IT infrastructure and information infrastructure, such as databases or large-scale research data. In addition, information infrastructure depends to some extent on IT infrastructure. In this paper, we discuss the IT, information, and legal infrastructure issues that research institutions face.
Datenmanagement wird durch die Forschungsföderungsorganisationen (etwa in Horizon 2020 der EU, die Allianz der deutschen Wissenschaftsorganisationen oder in DFG geförderten Projekten) mehr und mehr Teil der Forschungslandschaft. Für die Computerlinguistik ist das Forschungsdatenmanagement aber auch Teil des Forschungsgebietes: Datenmodellierung und Transformation für die nachhaltige Datenspeicherung gehören in den Bereich der Texttechnologie und Textlinguistik, ebenso die Modellierung der beschreibenden Daten zu Datensätzen.
"Reproducibility crisis" and "empirical turn" are only two keywords when it comes to providing reasons for research data management. Research data is omnipresent and with the more and more automatic data processing procedures, they become even more important. However, just because new methods require data and produce data, this does not mean that data are easily accessible, reusable or even make a difference in the CV of a researcher, even if a large portion of research goes into data creation, acquisition, preparation, and analysis. In this talk I will present where we find data in the research process, where we may find appropriate support for data management and advocate for a procedure for including it in research publications and resumes.
This presentation relies on work within the BMBF-funded project CLARIN-D. It also builds on work within the German National Research Data Infrastructure (NFDI) consortium Text+, DFG project number 460033370.