Research activities are usually applied to one or several research objects. An article about modeling of manuscript properties would therefore be tagged with the tags “Modeling” and “Manuscript”. A plain text editor would be tagged with the tags “Writing” and “Code” and “Text”.
FactGrid is both a database as well as a wiki. This project operated by the Gotha Research Centre and the data lab of the University of Erfurt. It utilizes MediaWiki and a Wikidata’s “wikibase” extension to collect data from historic research. With FactGrid you can create a knowledge graph, giving information in triple statements. This knowledge graph can be asked with SPARQL. All data provided by FactGrid holds a CC0-license.
TEI editions are among the most used tool by scholarly editors to produce digital editions in various literary fields. LIFT is a Python-based tool that allows to programmatically extract information from digital texts annotated in TEI by modelling persons, places, events and relations annotated in the form of a Knowledge Graph which reuses ontologies and controlled vocabularies from the Digital Humanities domain.
Every scholar in digital humanities and/or social sciences has probably already faced the challenge posed by consulting large digital newspaper archives in order to extract detailed information about a topic. It is beyond any doubt that computational-oriented methods and tools currently available may provide a great contribution; however, applying such methods and tools could pose several difficulties, especially in dealing with large ensembles of items.
Based on the ancient name for the gate of the Athenian Acropolis, the PROPYLÄEN open up a variety of approaches to Johann Wolfgang von Goethe’s life, work, communication and actions.
The Spanish Paleography (http://spanishpaleographytool.org) tool helps to bridge this gap for those interested in learning paleography of the early modern Spanish period, covering the late 15th to the 18th centuries. The tool is intended to allow users to learn how to decipher and read handwriting from documents of this era. Full transcriptions of the documents can be viewed in a facing-page format, or users can highlight individual words. This tool could be used as a teaching tool to introduce students to paleography.
Mediate is a collaborative time-based media annotation tool for the web that can be used both individually and collaboratively for synchronous and asynchronous digital annotation. One of its highlighting features is accessibility and customization, i.e. the ability to customize the schema that forms the basis of the analysis or the purpose of the project.
The Chinese Text Project is a well-established resource in Sinology, providing open access to a large number of ancient Chinese texts. As a digital medium, it utilizes crowdsourcing, linked data, knowledge graph and other computational technologies to provide an interactive interface for users who are interested in ancient Chinese texts. Beyond its main aim of providing open access to Chinese literature and philosophy texts, the project features an integrated Chinese character dictionary tool, images of scanned source texts, a search function for parallel passages, and much more. In terms of structured data, the project’s data wiki contains a wealth of records on entities such as persons, locations, and works.
The Closing the Gap in non-Latin script data aims at mapping the field of digital humanities projects outside and beyond the anglosphere with a particular focus on non-Latin scripts such as Arabic or Chinese in both machine-actionable and human readable form. The urgency and value of such a survey has been highlighted in recent discussions around global, decolonial, and multilingual digital humanities.
Everyone of us is accustomed to reading academic contributions using the Latin alphabet, for which we have already standard characters and formats. But what about texts written in languages featuring different, ideographic-based alphabets (for example, Chinese and Japanese)? What kind of recognition techniques and metadata are necessary to adopt in order to represent them in a digital context?
Following our last post focusing on Critical Discourse Analysis, today we highlight an automated document enrichment pipeline for automated interview coding, proposed by Ajda Pretnar Žagar, Nikola Ðukic´, Rajko Muršic in their paper presented at the Conference on Language Technologies & Digital Humanities, Ljubljana 2022. As described in the “Essential Guide to Coding Qualitative Data” (https://delvetool.com/guide), one of the main field of application of such a procedure is Ethnography, but not only.
Thanks to qualitative data coding it is possible to enrich texts through adding labels and descriptions to specific passages, that are generally pinpointed by means of computer-assisted qualitative data analysis softwares (CAQDAS). This can be valid for several fields of applications, from the humanities to biology, from sociology to medicine.
In their paper, Pretnar Žagar, Ðukic´ and Muršicˇ illustrate how relying on a couple of taxonomies (or onthologies) already known in anthropological studies may represent an asset to automatize and hasten the process of data labelling. These taxonomies are the Outline of Cultural Materials (OCM) and the ETSEO (acronym for Ethnological Topography of Slovenian Ethnic Territory) systematics. In both cases we deal with taxonomies elaborated and applied in ethnographic research in order to organize and better analyze concepts and categories related to human cultures and traditions.
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