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Einleitung
(2019)
This chapter will present lessons learned from CLARIN-D, the German CLARIN national consortium. Members of the CLARIN-D communities and of the CLARIN-D consortium have been engaged in innovative, data-driven, and community-based research, using language resources and tools in the humanities and neigh-bouring disciplines. We will present different use cases and users’ stories that demonstrate the innovative research potential of large digital corpora and lexical resources for the study of language change and variation, for language documentation, for literary studies, and for the social sciences. We will emphasize the added value of making language resources and tools available in the CLARIN distributed research infrastructure and will discuss legal and ethical issues that need to be addressed in the use of such an infrastructure. Innovative technical solutions for accessing digital materials still under copyright and for data mining such materials will be presented. We will outline the need for close interaction with communities of interest in the areas of curriculum development, data management, and training the next generation of digital humanities scholars. The importance of community-supported standards for encoding language resources and the practice of community-based quality control for digital research data will be presented as a crucial step toward the provisioning of high quality research data. The chapter will conclude with a discussion of impor-tant directions for innovative research and for supporting infrastructure development over the next decade and beyond.
Preface
(2022)
KonsortSWD ist das NFDI Konsortium für die Sozial-, Verhaltens-, Bildungs- und Wirtschaftswissenschaften. Für die äußerst vielfältigen Datentypen und Forschungsmethoden bauen die Beteiligten im Rahmen der NFDI eine bereits bestehende Forschungsdateninfrastruktur aus und ergänzen neue integrierende Dienste. Basis sind die heute 41 vom Rat für Sozial- und Wirtschaftsdaten akkreditierten Forschungsdatenzentren (FDZ). FDZ sind Spezialsammlungen zu jeweils spezifischen Forschungsdaten, z.B. aus der qualitativen Sozialforschung, und können so Forschende auf Basis einer ausführlichen Expertise zu diesen Daten beraten. Neben der Unterstützung der FDZ baut KonsortSWD auch neue Dienste in den Bereichen Datenproduktion, Datenzugang und Technische Lösungen auf.
This paper describes the ongoing work to integrate WebLicht into the CLARIN infrastructure. It introduces the CLARIN infrastructure for scholars in the humanities and social sciences as well as WebLicht - an orchestration and execution environment that is built upon Service Oriented Architecture principles. The integration of WebLicht into the CLARIN infrastructure involves adapting it to the standards and practices used within CLARIN, including distributed repositories, CMDI metadata, and persistent identifiers.
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.
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.
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.