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Poster des Text+ Partners Leibniz-Institut für Deutsche Sprache Mannheim präsentiert beim Workshop "Wohin damit? Storing and reusing my language data" am 22. Juni 2023 in Mannheim. Das Poster wurde im Kontext der Arbeit des Vereins Nationale Forschungsdateninfrastruktur (NFDI) e.V. verfasst. NFDI wird von der Bundesrepublik Deutschland und den 16 Bundesländern finanziert, und das Konsortium Text+ wird gefördert durch die Deutsche Forschungsgemeinschaft (DFG) – Projektnummer 460033370. Die Autor:innen bedanken sich für die Förderung sowie Unterstützung. Ein Dank geht außerdem an alle Einrichtungen und Akteur:innen, die sich für den Verein und dessen Ziele engagieren.
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.
"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.
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.
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.
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.
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.
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.
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 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.
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 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 12th Web as Corpus workshop (WAC-XII) looks at the past, present, and future of web corpora given the fact that large web corpora are nowadays provided mostly by a few major initiatives and companies, and the diversity of the early years appears to have faded slightly. Also, we acknowledge the fact that alternative sources of data (such as data from Twitter and similar platforms) have emerged, some of them only available to large companies and their affiliates, such as linguistic data from social media and other forms of the deep web. At the same time, gathering interesting and relevant web data (web crawling) is becoming an ever more intricate task as the nature of the data offered on the web changes (for example the death of forums in favour of more closed platforms).
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.
Um eine bessere Erreichbarkeit und Zugänglichkeit zu bestehenden sowie neuen Angeboten von Lehr- und Schulungsmaterialien im Bereich der Digital Humanities zu ermöglichen, sollten diese in einem zentralen Verzeichnis zur Verfügung gestellt werden. Im Rahmen des CLARIAH-DE Projekts wurde – zunächst für die Umsetzung eines Projektmeilensteins – eine Lösung gesucht, die eine übergreifende Suche in frei zugänglichen und nachnutzbaren Lehr- und Schulungsmaterialien zu Forschungsmethoden, Verfahren sowie Werkzeugen im Bereich der Digital Humanities in unterschiedlichen Plattformen und Repositorien bietet.
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.
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.
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.
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.
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.
To optimize the sharing and reuse of existing data, many funding organizations now require researchers to specify a management plan for research data. In such a plan, researchers are supposed to describe the entire life cycle of the research data they are going to produce, from data creation to formatting, interpretation, documentation, short-term storage, long-term archiving and data re-use. To support researchers with this task, we built DMPTY, a wizard that guides researchers through the essential aspects of managing data, elicits information from them, and finally, generates a document that can be further edited and linked to the original research proposal.
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.
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.
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.
The Component Metadata Infrastructure (CMDI) in a project on sustainable linguistic resources
(2012)
The sustainable archiving of research data for predefined time spans has become increasingly important to researchers and is stipulated by funding organizations with the obligatory task of being observed by researchers. An important aspect in view of such a sustainable archiving of language resources is the creation of metadata, which can be used for describing, finding and citing resources. In the present paper, these aspects are dealt with from the perspectives of two projects: the German project for Sustainability of Linguistic Data at the University of Tubingen (NaLiDa, cf. http://www.sfs.uni-tuebingen.de/nalida) and the Dutch-Flemish HLT Agency hosted at the Institute for Dutch Lexicology (TST-Centrale, cf.http://www.inl.nl/tst-centrale). Both projects unfold their approaches to the creation of components and profiles using the Component Metadata Infrastructure (CMDI) as underlying metadata schema for resource descriptions, highlighting their experiences as well as advantages and disadvantages in using CMDI.
Data Management is one of the core activities of all CLARIN centres providing data and services for the academia. In PARTHENOS, European initiatives and projects in the area of the humanities and social sciences assembled to compare policies and procedures. One of the areas of interest is data management. The data management landscape shows a lot of proliferation, for which an abstraction level is introduced to help centres, such as CLARIN centres, in the process of providing the best possible services to users with data management needs.
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.
The transfer of research data management from one institution to another infrastructural partner is all but trivial, but can be required,for instance, when an institution faces reorganisation or closure. In a case study, we describe the migration of all research data, identify the challenges we encountered, and discuss how we addressed them. It shows that the moving of research data management to another institution is a feasible, but potentially costly enterprise. Being able to demonstrate the feasibility of research data migration supports the stance of data archives that users can expect high levels of trust and reliability when it comes to data safety and sustainability.
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.
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.
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.
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.
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.
Die Gemeinsame Wissenschaftskonferenz hat den Verbund „Text+“ bewilligt. „Text+“ hat sich zum Ziel gesetzt, text- und sprachbasierte Forschungsdaten langfristig zu erhalten und ihre breite Nutzung in der Wissenschaft zu ermöglichen. Die Initiative startet somit nach mehrjähriger Vorbereitungszeit und wird zunächst für fünf Jahre durch die Deutsche Forschungsgemeinschaft gefördert.
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.
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.
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.
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.
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.
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.
Contents:
1. Julien Abadji, Pedro Javier Ortiz Suárez, Laurent Romary and Benoît Sagot: "Ungoliant: An Optimized Pipeline for the Generation of a Very Large-Scale Multilingual Web Corpus", S.1-9.
2. Markus Gärtner, Felicitas Kleinkopf, Melanie Andresen and Sibylle Hermann: "Corpus Reusability and Copyright - Challenges and Opportunities", S.10-19.
3. Nils Diewald, Eliza Margaretha and Marc Kupietz: "Lessons learned in Quality Management for Online Research Software Tools in Linguistics", S.20-26.
Implicitly abusive language – What does it actually look like and why are we not getting there?
(2021)
Abusive language detection is an emerging field in natural language processing which has received a large amount of attention recently. Still the success of automatic detection is limited. Particularly, the detection of implicitly abusive language, i.e. abusive language that is not conveyed by abusive words (e.g. dumbass or scum), is not working well. In this position paper, we explain why existing datasets make learning implicit abuse difficult and what needs to be changed in the design of such datasets. Arguing for a divide-and-conquer strategy, we present a list of subtypes of implicitly abusive language and formulate research tasks and questions for future research.
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.
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.
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.
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.
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.