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.
Category: Programming
Creation of code executable by a computer, that is creation of scripts or software. (This includes “Prototyping”, the creation of such code for testing or modeling purposes.) It is also closely related to the more broader activity of tool development. Programming is separate from Encoding (enriching a document by making structural, layout-related, semantic, or other information about a specific part of a document explicit by adding markup to its transcription).
The conversation below is a special, summer episode of our Spotlight series. It is a collaboration between OpenMethods and the Humanista podcast and this it comes as a podcast, in which Alíz Horváth, owner of the Humanista podcast series and proud Editorial Team member of OpenMethods, is asking Shih-Pei Chen, scholar and Digital Content Curator at the Max Plank Institute for the History of Science about the text analysis tools LoGaRT, RISE and SHINE; non-Latin scripted Digital Humanities, why local gazetteers are goldmines to Asian Studies, how digitization changes, broadens the kinds research questions one can study, where are the challenges in the access to cultural heritage and liaising with proprietary infrastructure providers… and many more! Enjoy!
Introduction: Awarded as Best Long Paper at the 2019 NACCL (North American Chapter of the Association for Computational Linguistics) Conference, the contribution by Jacob Devlin et al. provides an illustration of “BERT: Pre-training of Deep Biredictional Transformers for Language Understanding” (https://aclanthology.org/N19-1423/).
As highlighted by the authors in the abstract, BERT is a “new language representation model” and, in the past few years, it has become widespread in various NLP applications; for example, a project exploiting it is CamemBERT (https://camembert-model.fr/), regarding French.
In June 2021, a workshop organized by David Mimno, Melanie Walsh and Maria Antoniak (https://melaniewalsh.github.io/BERT-for-Humanists/workshop/) pointed out how to use BERT in projects related to digital humanities, in order to deal with word similarity and classification classification while relying on Phyton-based HuggingFace transformers library. (https://melaniewalsh.github.io/BERT-for-Humanists/tutorials/ ). A further advantage of this training resource is that it has been written with sensitivity towards the target audience in mind: in a way that it provides a gentle introduction to complexities of language models to scholars with education and background other than Computer Science.
Along with the Tutorials, the same blog includes Introductions about BERT in general and in its specific usage in a Google Colab notebook, as well as a constantly-updated bibliography and a glossary of the main terms (‘attention’, ‘Fine-Tune’, ‘GPU’, ‘Label’, ‘Task’, ‘Transformers’, ‘Token’, ‘Type’, ‘Vector’).
Introduction: This white paper is an outcome of a DH2019 workshop dedicated to foster closer collaboration among technology-oriented DH researchers and developers of tools to support Digital Humanities research. The paper briefly outlines the most pressing issues in their collaboration and addresses topics such as: good practices to ease mutual understanding between scholars and researchers; software development and academic career and recognition; or sustainability and funding.
Introduction: The world of R consists of innumerous packages. Most of them have very little download rates because they are limited to certain functions as part of a larger argument. Based on a surprising experience with the small package clipr Matthew Lincoln shares his thoughts about this reception phenomenon especially in the digital humanities.
Introduction: The Research Software Directory of the Netherlands eScience Institute provides easy access to software, source code and its documentation. More importantly, it makes it easy to cite software, which is highly advisable when using software to derive research results. The Research Software Directory positions itself as a platform that eases scientific referencing and reproducibility of software based research—good peer praxis that is still underdeveloped in the humanities.
Introduction: This lesson by Marten Düring from the “Programming Historian-Website” gently introduces novices to the topic to Network Visualisation of Historical Sources. As a case study it covers not only the general advantages of network visualisation for humanists but also a step-by-step explanation of the process from extraction of the data until the visualization (using the Palladio-tool). This lesson has also been translated into Spanish and includes many useful references for further reading.
Introduction: This blog post not only presents a technique of measuring poetic meter and using it to plot distances between poets, but it also provides an insight into the theoretical and empirical process leading to those results.
Introduction: This very complete tutorial by Patrick Smyth will help digital humanists or any interested person on digital technologies applied to projects how to make data more accessible to users through APIs (Application Programming Interfaces). After explaining the basics about APIs and databases, an API is built and put into practice. Python 3 and the Flask are the web frameworks used for developing this API.
Introduction: Concepts are described differently in different times, and the way people talk about them reveals much about how people perceive these concepts. Researchers of the eScience Center in Amsterdam together with scholars from Utrecht University developed a visual tool to gain insight into such concept shift.