Refine
Document Type
- Part of a Book (5)
- Article (4)
- Conference Proceeding (3)
Has Fulltext
- yes (12)
Keywords
- Annotation (4)
- Digital Humanities (4)
- Computerlinguistik (3)
- Sprachdaten (3)
- Automatische Sprachanalyse (2)
- Datenstruktur (2)
- Korpus <Linguistik> (2)
- XML (Extensible Markup Language) (2)
- Annotations (1)
- Argumentstruktur (1)
Publicationstate
- Postprint (12) (remove)
Reviewstate
- (Verlags)-Lektorat (10)
- Peer-Review (2)
Was darf die sprachwissenschaftliche Forschung? Juristische Fragen bei der Arbeit mit Sprachdaten
(2022)
Sich in der Linguistik mit rechtlichen Themen beschäftigen zu müssen, ist auf den ersten Blick überraschend. Da jedoch in den Sprachwissenschaften empirisch gearbeitet wird und Sprachdaten, insbesondere Texte und Ton- und Videoaufnahmen sowie Transkripte gesprochener Sprache, in den letzten Jahren auch verstärkt Sprachdaten internetbasierter Kommunikation, als Basis für die linguistische Forschung dienen, müssen rechtliche Rahmenbedingungen für jede Art von Datennutzung beachtet werden. Natürlich arbeiten auch andere Wissenschaften, wie z. B. die Astronomie oder die Meteorologie, empirisch. Jedoch gibt es einen grundsätzlichen Unterschied der empirischen Basis: Im Gegensatz zu Temperaturen, die gemessen, oder Konstellationen von Himmelskörpern, die beobachtet werden, basieren Sprachdaten auf schriftlichen, mündlichen oder gebärdeten Äußerungen von Menschen, wodurch sich juristisch begründete Beschränkungen ihrer Nutzung ergeben.
An approach to the unification of XML (Extensible Markup Language) documents with identical textual content and concurrent markup in the framework of XML-based multi-layer annotation is introduced. A Prolog program allows the possible relationships between element instances on two annotation layers that share PCDATA to be explored and also the computing of a target node hierarchy for a well-formed, merged XML document. Special attention is paid to identity conflicts between element instances, for which a default solution that takes into account metarelations that hold between element types on the different annotation layers is provided. In addition, rules can be specified by a user to prescribe how identity conflicts should be solved for certain element types.
The Leibniz-Institute for the German Language (IDS) was established in Mannheim in 1964. Since then, it has been at the forefront of innovation in German linguistics as a hub for digital language data. This chapter presents various lessons learnt from over five decades of work by the IDS, ranging from the importance of sustainability, through its strong technical base and FAIR principles, to the IDS’ role in national and international cooperation projects and its expertise on legal and ethical issues related to language resources and language technology.
This article shows that the TEI tag set for feature structures can be adopted to represent a heterogeneous set of linguistic corpora. The majority of corpora is annotated using markup languages that are based on the Annotation Graph framework, the upcoming Linguistic Annotation Format ISO standard, or according to tag sets defined by or based upon the TEI guidelines. A unified representation comprises the separation of conceptually different annotation layers contained in the original corpus data (e.g. syntax, phonology, and semantics) into multiple XML files. These annotation layers are linked to each other implicitly by the identical textual content of all files. A suitable data structure for the representation of these annotations is a multi-rooted tree that again can be represented by the TEI and ISO tag set for feature structures. The mapping process and representational issues are discussed as well as the advantages and drawbacks associated with the use of the TEI tag set for feature structures as a storage and exchange format for linguistically annotated data.
We report on finished work in a project that is concerned with providing methods, tools, best practice guidelines, and solutions for sustainable linguistic resources. The article discusses several general aspects of sustainability and introduces an approach to normalizing corpus data and metadata records. Moreover, the architecture of the sustainability platform implemented by the authors is described.
This article introduces the topic of ‘‘Multilingual language resources and interoperability’’. We start with a taxonomy and parameters for classifying language resources. Later we provide examples and issues of interoperatability, and resource architectures to solve such issues. Finally we discuss aspects of linguistic formalisms and interoperability.
Researchers in many disciplines, sometimes working in close cooperation, have been concerned with modeling textual data in order to account for texts as the prime information unit of written communication. The list of disciplines includes computer science and linguistics as well as more specialized disciplines like computational linguistics and text technology. What many of these efforts have in common is the aim to model textual data by means of abstract data types or data structures that support at least the semi-automatic processing of texts in any area of written communication.