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Has Fulltext
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Institute
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The neuronal dynamics of auditory language comprehension : (Akademievorlesung am 12. November 1998)
(1999)
Introduction : how much is enough, but not too much ; (Ernst-Mayr-Lecture am 27. Oktober 1998)
(1999)
Research in Silicon Valley
(1998)
The computer has come to play a transformative role in the ways we model, store, process and study text. Nevertheless, we cannot yet claim to have realised the promises of the digital medium: the organisation and dissemination of scholarly knowledge through the exchange, reuse and enrichment of data sets. Despite the acclaimed interdisciplinary nature of digital humanities, current digital research takes place in a closed environment and rarely surpasses the traditional boundaries of a field. Furthermore, it is worthwhile to continue questioning the models we use and whether they are actually suitable for our scholarly needs. There’s a risk that the affordances and limitations of a prevailing model may blind us to aspects it doesn’t support.
In her talk, Elli Bleeker discusses different technologies to model data with respect to their expressive power and their potential to address the needs of the scholarly community. Within this framework, she introduces a new data model for text, Text-As-Graph (TAG), and it’s reference implementation Alexandria, a text repository system. The TAG model allows researchers to store, query, and analyse text that is encoded from different perspectives. Alexandria thus stimulates new ways of looking at textual objects, facilitates the exchange of information across disciplines, and secures textual knowledge for future endeavours. From a philosophical perspective, the TAG model and the workflow of Alexandria raise compelling questions about our notions of textuality, and prompt us to reconsider how we can best model the variety of textual dimensions.
When managing large quantities of data, it is a common solution to utilize a centralized data management software to forge a connection between metadata and the data objects themselves. In case of text-based objects without any attached metadata, it is easy for humans to contextualize these objects by recognizing patterns such as filenames, titles, authors etc. This task becomes a challenge when dealing with non-text-based objects like images in the cultural heritage domain. Without metadata or expert knowledge, it becomes difficult to estimate the creation date of a painting or tell the name of its painter. Thus, the ability to contextualize data depends on whether there is a working connection between the metadata store and the data object itself. This connection fails as soon as the file is moved on the file system without having these changes also applied in the corresponding
data base, or when the file is shared without a reference to its original location. This paper presents an approach to overcome that type of co-dependency by utilizing XMP to embed cultural heritage metadata directly into image files to ensure their location-independent long-term preservation. The “Corpus Vitrearum Medii Aevi” Germany (CVMA) project serves as an example use-case.