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For a long time, the lecture dominated performatively presented scientific communication. Given academic traditions, it is possible to make a connection between the lecture and classical rhetoric, a highly differentiated instrument of analysis. The tradition of the lecture has been perpetuated in the presentation of research results, first in the use of transparencies and subsequently through computer-based projections. Yet the use of media technology has also allowed new practices to emerge, including mediation practices hitherto neglected in the theory of rhetoric.
Knowledge in textual form is always presented as visually and hierarchically structured units of text, which is particularly true in the case of academic texts. One research hypothesis of the ongoing project Knowledge ordering in texts - text structure and structure visualisations as sources of natural ontologies1 is that the textual structure of academic texts effectively mirrors essential parts of the knowledge structure that is built up in the text. The structuring of a modern dissertation thesis (e.g. in the form of an automatically generated table of contents - toes), for example, represents a compromise between requirements of the text type and the methodological and conceptual structure of its subject-matter. The aim of the project is to examine how visual-hierarchical structuring systems are constructed, how knowledge structures are encoded in them, and how they can be exploited to automatically derive ontological knowledge for navigation, archiving, or search tasks. The idea to extract domain concepts and semantic relations mainly from the structural and linguistic information gathered from tables of contents represents a novel approach to ontology learning.
This paper presents challenges and opportunities resulting from the application of geographical information systems (GIS) in the (digital) humanities. First, we provide an overview of the intersection and interaction between geography (and cartography), and the humanities. Second, the “GeoBib” project is used as a case study to exemplify challenges for such collaborative, interdisciplinary projects, both for the humanists and the geoscientists. Finally, we conclude with an outlook on further applications of GIS in the humanities, and the potential scientific benefit for both sides, humanities and geosciences.
In the project SemDok (Generic document structures in linearly organised texts) funded by the German Research Foundation DFG, a discourse parser for a complex type (scientific articles by example), is being developed. Discourse parsing (henceforth DP) according to the Rhetorical Structure Theory (RST) (Mann and Taboada, 2005; Marcu, 2000) deals with automatically assigning a text a tree structure in which discourse segments and rhetorical relations between them are marked, such as Concession. For identifying the combinable segments, declarative rules are employed, which describe linguistic and structural cues and constraints about possible combinations by referring to different XML annotation layers of the input text, and external knowledge bases such as a discourse marker lexicon, a lexico-semantic ontology (later to be combined with a domain ontology), and an ontology of rhetorical relations. In our text-technological environment, the obvious choice of formalism to represent such ontologies is OWL (Smith et al., 2004). In this paper, we describe two OWL ontologies and how they are consulted from the discourse parser to solve certain tasks within DP. The first ontology is a taxononomy of rhetorical relations which was developed in the project. The second one is an OWL version of GermaNet, the model of which we designed together with our project partners.
From Open Source to Open Information. Collaborative Methods in Creating XML-based Markup Languages
(2000)
Extending the possibilities for collaborative work with TEI/XML through the usage of a wiki system
(2013)
This paper presents and discusses an integrated project-specific working environment for editing TEI/XML-files and linking entities of interest to a dedicated wiki system. This working environment has been specifically tailored to the workflow in our interdisciplinary digital humanities project GeoBib. It addresses some challenges that arose while working with person-related data and geographical references in a growing collection of TEI/XML-files. While our current solution provides some essential benefits, we also discuss several critical issues and challenges that remain.
The administration of electronic publication in the Information Era congregates old and new problems, especially those related with Information Retrieval and Automatic Knowledge Extraction. This article presents an Information Retrieval System that uses Natural Language Processing and Ontology to index collection’s texts. We describe a system that constructs a domain specific ontology, starting from the syntactic and semantic analyses of the texts that compose the collection. First the texts are tokenized, then a robust syntactic analysis is made, subsequently the semantic analysis is accomplished in conformity with a metalanguage of knowledge representation, based on a basic ontology composed of 47 classes. The ontology, automatically extracted, generates richer domain specific knowledge. It propitiates, through its semantic net, the right conditions for the user to find with larger efficiency and agility the terms adapted for the consultation to the texts. A prototype of this system was built and used for the indexation of a collection of 221 electronic texts of Information Science written in Portuguese from Brazil. Instead of being based in statistical theories, we propose a robust Information Retrieval System that uses cognitive theories, allowing a larger efficiency in the answer to the users queries.
Uncertain about Uncertainty: Different ways of processing fuzziness in digital humanities data
(2014)
The GeoBib project is constructing a georeferenced online bibliography of early Holocaust and camp literature published between 1933 and 1949 (Entrup et al. 2013a). Our immediate objectives include identifying the texts of interest in the first place, composing abstracts for them, researching their history, and annotating relevant places and times. Relations between persons, texts, and places will be visualized using digital maps and GIS software as an integral part of the resulting GeoBib information portal. The combination of diverse data from varying sources not only enriches our knowledge of these otherwise mostly forgotten texts; it also confronts us with vague, uncertain or even conflicting information. This situation yields challenges for all researchers involved – historians, literary scholars, geographers and computer scientists alike. While the project operates at the intersection of historical and literary studies, the involved computer scientists are in charge of providing a working environment (Entrup et al. 2013b) and processing the collected information in a way that is formalized yet capable of dealing with inevitable vagueness, uncertainty and contradictions. In this paper we focus on the problems and opportunities of encoding and processing fuzzy data.
The present paper reports the first results of the compilation and annotation of a blog corpus for German. The main aim of the project is the representation of the blog discourse structure and relations between its elements (blog posts, comments) and participants (bloggers, commentators). The data included in the corpus were manually collected from the scientific blog portal SciLogs. The feature catalogue for the corpus annotation includes three types of information which is directly or indirectly provided in the blog or can be construed by means of statistical analysis or computational tools. At this point, only directly available information (e.g., title of the blog post, name of the blogger etc.) has been annotated. We believe, our blog corpus can be of interest for the general study of blog structure or related research questions as well as for the development of NLP methods and techniques (e.g. for authorship detection).