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Twenty-two historical encyclopedias encoded in TEI: a new resource for the Digital Humanities
(2020)
This paper accompanies the corpus publication of EncycNet, a novel XML/TEI annotated corpus of 22 historical German encyclopedias from the early 18th to early 20th century. We describe the creation and annotation of the corpus, including the rationale for its development, suggested methodology for TEI annotation, possible use cases and future work. While many well-developed annotation standards for lexical resources exist, none can adequately model the encyclopedias at hand, and we therefore suggest how the TEI Lex-0 standard may be modified with additional guidelines for the annotation of historical encyclopedias. As the digitization and annotation of historical encyclopedias are settling on TEI as the de facto standard, our methodology may inform similar projects.
Privacy by Design (also referred to as Data Protection by Design) is an approach in which solutions and mechanisms addressing privacy and data protection are embedded through the entire project lifecycle, from the early design stage, rather than just added as an additional layer to the final product. Formulated in the 1990 by the Privacy Commissionner of Ontario, the principle of Privacy by Design has been discussed by institutions and policymakers on both sides of the Atlantic, and mentioned already in the 1995 EU Data Protection Directive (95/46/EC). More recently, Privacy by Design was introduced as one of the requirements of the General Data Protection Regulation (GDPR), obliging data controllers to define and adopt, already at the conception phase, appropriate measures and safeguards to implement data protection principles and protect the rights of the data subject. Failing to meet this obligation may result in a hefty fine, as it was the case in the Uniontrad decision by the French Data Protection Authority (CNIL). The ambition of the proposed paper is to analyse the practical meaning of Privacy by Design in the context of Language Resources, and propose measures and safeguards that can be implemented by the community to ensure respect of this principle.
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.
Beyond Citations: Corpus-based Methods for Detecting the Impact of Research Outcomes on Society
(2020)
This paper proposes, implements and evaluates a novel, corpus-based approach for identifying categories indicative of the impact of research via a deductive (top-down, from theory to data) and an inductive (bottom-up, from data to theory) approach. The resulting categorization schemes differ in substance. Research outcomes are typically assessed by using bibliometric methods, such as citation counts and patterns, or alternative metrics, such as references to research in the media. Shortcomings with these methods are their inability to identify impact of research beyond academia (bibliometrics) and considering text-based impact indicators beyond those that capture attention (altmetrics). We address these limitations by leveraging a mixed-methods approach for eliciting impact categories from experts, project personnel (deductive) and texts (inductive). Using these categories, we label a corpus of project reports per category schema, and apply supervised machine learning to infer these categories from project reports. The classification results show that we can predict deductively and inductively derived impact categories with 76.39% and 78.81% accuracy (F1-score), respectively. Our approach can complement solutions from bibliometrics and scientometrics for assessing the impact of research and studying the scope and types of advancements transferred from academia to society.
Interoperability in an Infrastructure Enabling Multidisciplinary Research: The case of CLARIN
(2020)
CLARIN is a European Research Infrastructure providing access to language resources and technologies for researchers in the humanities and social sciences. It supports the use and study of language data in general and aims to increase the potential for comparative research of cultural and societal phenomena across the boundaries of languages and disciplines, all in line with the European agenda for Open Science. Data infrastructures such as CLARIN have recently embarked on the emerging frameworks for the federation of infrastructural services, such as the European Open Science Cloud and the integration of services resulting from multidisciplinary collaboration in federated services for the wider domain of the social sciences and humanities (SSH). In this paper we describe the interoperability requirements that arise through the existing ambitions and the emerging frameworks. The interoperability theme will be addressed at several levels, including organisation and ecosystem, design of workflow services, data curation, performance measurement and collaboration. For each level, some concrete outcomes are described.
Die zentrale Aufgabenstellung des Verbundprojektes TextTransfer (Pilot) war eine Machbarkeitsprüfung für die Entwicklung eines Text-Mining-Verfahrens, mit dem Forschungsergebnisse automatisiert auf Hinweise zu Transfer- und Impactpotenzialen untersucht werden können. Das vom Projektkoordinator IDS verantwortete Teilprojekt konzentrierte sich dabei auf die Entwicklung der methodischen Grundlagen, während der Projektpartner TIB vornehmlich für die Bereitstellung eines geeigneten Datensatzes verantwortlich war. Solchen automatisierten Verfahren liegen zumeist textbasierte Daten als physisches Manifest wissenschaftlicher Erkenntnisse zugrunde, die im Falle von TextTransfer (Pilot) als empirische Grundlage herangezogen wurden. Das im Verbund zur Anwendung gebrachte maschinelle Lernverfahren stützte sich ausschließlich auf deutschsprachige Projektendberichte öffentlich geförderter Forschung. Diese Textgattung eignet sich insbesondere hinsichtlich ihrer öffentlichen Verfügbarkeit bei zuständigen Gedächtnisorganisationen und aufgrund ihrer im Vergleich zu anderen Formaten wissenschaftlicher Publikation relativen strukturellen wie sprachlichen Homogenität. TextTransfer (Pilot) ging daher grundsätzlich von der Annahme struktureller bzw. sprachlicher Ähnlichkeit in Berichtstexten aus, bei denen der Nachweis tatsächlich erfolgten Transfers zu erbringen war. Im Folgenden wird in diesen Fällen von Texten bzw. textgebundenen Forschungsergebnissen mit Transfer- und Impactpotenzial gesprochen werden. Es wurde ferner postuliert, dass sich diese Indizien von sprachlichen Eigenschaften in Texten zu Projekten ohne nachzuweisenden bzw. ggf. auch niemals erfolgtem, aber potenziell möglichem Transfer oder Impact unterscheiden lassen. Mit einer Verifizierung dieser Annahmen war es möglich, Transfer- oder Impactwahrscheinlichkeiten in großen Mengen von Berichtsdaten ohne eingehende Lektüre zu prognostizieren.