Refine
Document Type
- Conference Proceeding (7)
- Article (4)
- Other (2)
Has Fulltext
- yes (13)
Keywords
- Forschung (13) (remove)
Publicationstate
Reviewstate
- Peer-Review (12)
- (Verlags)-Lektorat (1)
Publisher
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.
The CLARIN Concept Registry (CCR) is the common semantic ground for most CMDI-based profiles to describe language-related resources in the CLARIN universe. While the CCR supports semantic interoperability within this universe, it does not extend beyond it. The flexibility of CMDI, however, allows users to use other term or concept registries when defining their metadata components. In this paper, we describe our use of schema.org, a light ontology used by many parties across disciplines.
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.
The CLARIN infrastructure as an interoperable language technology platform for SSH and beyond
(2023)
CLARIN is a European Research Infrastructure Consortium developing and providing a federated and interoperable platform to support scientists in the field of the Social Sciences and Humanities in carrying-out language-related research. This contribution provides an overview of the entire infrastructure with a particular focus on tool interoperability, ease of access to research data, tools and services, the importance of sharing knowledge within and across (national) communities, and community building. By taking into account FAIR principles from the very beginning, CLARIN succeeded in becoming a successful example of a research infrastructure that is actively used by its members. The benefits CLARIN members reap from their infrastructure secure a future for their common good that is both sustainable and attractive to partners beyond the original target groups.
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.
Für die sprachbasierte Forschung in den Geistes- und Sozialwissenschaften stellt CLARIN eine Forschungsinfrastruktur bereit, die auf die hochgradig heterogenen Forschungsdaten in diesen Wissenschaftsbereichen angepasst ist. Mit Werkzeugen zum Auffinden, zur standardkonformen Aufbereitung und zur nachhaltigen Aufbewahrung von Daten sowie mit der Bereitstellung von virtuellen Forschungsumgebungen zur kollaborativen Erstellung und Auswertung von Forschungsdaten unterstützt CLARIN alle wesentlichen Aspekte des Datenmanagements und der Datenarchivierung. Diese CLARIN-Angebote werden durch Beratungs- und Schulungsmaßnahmen begleitet.
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.
This paper uses a devil’s advocate position to highlight the benefits of metadata creation for linguistic resources. It provides an overview of the required metadata infrastructure and shows that this infrastructure is in the meantime developed by various projects and hence can be deployed by those working with linguistic resources and archiving. Possible caveats of metadata creation are mentioned starting with user requirements and backgrounds, contribution to academic merits of researchers and standardisation. These are answered with existing technologies and procedures, referring to the Component Metadata Infrastructure (CMDI). CMDI provides an infrastructure and methods for adapting metadata to the requirements of specific classes of resources, using central registries for data categories, and metadata schemas. These registries allow for the definition of metadata schemas per resource type while reusing groups of data categories also used by other schemas. In summary, rules of best practice for the creation of metadata are given.