Category: English

Humanities Data Analysis: Case Studies with Python — Humanities Data Analysis: Case Studies with Python

Humanities Data Analysis: Case Studies with Python — Humanities Data Analysis: Case Studies with Python

Introduction: Folgert Karsdorp, Mike Kestemont and Allen Riddell ‘s  interactive book, Humanities Data Analysis: Case Studies with Python had been written with the aim in mind to equip humanities students and scholars working with textual and tabular resources with practical, hands-on knowledge to better understand the potentials of data-rich, computer-assisted approaches that the Python framework offers to them and eventually to apply and integrate them to their own research projects.

The first part introduces a “Data carpentry”, a collection of essential techniques for gathering, cleaning, representing, and transforming textual and tabular data. This sets the stage for the second part that consists of 5 case studies (Statistics Essentials: WhoReads Novels? ; Introduction to Probability ; Narrating with Maps ; Stylometry and the Voice of Hildegard ; A Topic Model of United States Supreme Court Opinions, 1900–2000 ) showcasing how to draw meaningful insights from data using quantitative methods. Each chapter contains executable Python codes and ends with exercises ranging from easier drills to more creative and complex possibilities to adapt the apply and adopt the newly acquired knowledge to their own research problems.

The book exhibits best practices in how to make digital scholarship available in an open, sustainable ad digital-native manner, coming in different layers that are firmly interlinked with each other. Published with Princeton University Press in 2021, hardcopies are also available, but more importantly, the digital version is an  Open Access Jupyter notebook that can be read in multiple environments and formats (.md and .pdf). The documentation, coda and data materials are available on Zenodo (https://zenodo.org/record/3560761#.Y3tCcn3MJD9). The authors also made sure to select and use packages which are mature and actively maintained.

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What is PixPlot? (DH Tools) – YouTube

What is PixPlot? (DH Tools) – YouTube

Introduction: This short video teaser summarizes the main characteristics of PixPlot, a Python-based tool for clustering images and analyzing them from a numerical perspective as well as its pedagogical relevance as far as
machine learning is concerned.

The paper “Visual Patterns Discovery in Large Databases of Paintings”, presented at the Digital Humanities 2016 Conference held in Poland,
can be considered the foundational text for the development of the PixPlot Project at Yale University.
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Navigating the centuries with the ‘Mapping of the Republic of Letters’ project.

Navigating the centuries with the ‘Mapping of the Republic of Letters’ project.

In this post, we reach back in time to showcase an older project and highlight its impact on data visualization in Digital Humanities as well as its good practices to make different layers of scholarship available for increased transparency and reusability.  

Developed at Stanford with other research partners (‘Cultures of Knowledge’ at Oxford, the Groupe d’Alembert at CNRS, the KKCC-Circulation of Knowledge and Learned Practices in the 17th-century Dutch Republic, the DensityDesign ResearchLab), the ‘Mapping of the Republic of Letters Project’ aimed at digitizing and visualizing the intellectual community throughout the XVI and XVIII centuries known as ‘Republic of Letters’ (an overview of the concept can be found in Bots and Waquet, 1997), to get a better sense of the shape, size and associated intellectual network, its inherent complexities and  boundaries.

Below we highlight the different, interrelated
layers of making project outputs available and reusable on the long term (way before FAIR data became a widespread policy imperative!): methodological reflections, interactive visualizations, the associated data and its data model schema. All of these layers are published in a trusted repository and are interlinked with each other via their Persistent Identifiers.

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OpenMethods Spotlights #4 Improving access to Asian cultural heritage and enabling new ways to connect and study them: a podcast with Alíz Horváth and Shih-Pei Chen

OpenMethods Spotlights #4 Improving access to Asian cultural heritage and enabling new ways to connect and study them: a podcast with Alíz Horváth and Shih-Pei Chen

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!

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Collaborative Digital Projects in the Undergraduate Humanities Classroom: Case Studies with Timeline JS

Collaborative Digital Projects in the Undergraduate Humanities Classroom: Case Studies with Timeline JS

https://openmethods.dariah.eu/2022/05/11/open-source-tool-allows-users-to-create-interactive-timelines-digital-humanities-at-a-state/ OpenMethods introduction to: Collaborative Digital Projects in the Undergraduate Humanities Classroom: Case Studies with Timeline JS 2022-05-11 07:28:36 Marinella Testori Blog post Creation Data Designing Digital Humanities English Methods…

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Annotation Guidelines For narrative levels, time features, and subjective narration styles in fiction (SANTA 2).

Annotation Guidelines For narrative levels, time features, and subjective narration styles in fiction (SANTA 2).

Introduction: If you are looking for solutions to translate narratological concepts to annotation guidelines to tag or mark-up your texts for both qualitative and quantitative analysis, then Edward Kearns’s paper “Annotation Guidelines for narrative levels, time features, and subjective narration styles in fiction” is for you! The tag set is designed to be used in XML, but they can be flexibly adopted to other working environments too, including for instance CATMA. The use of the tags is illustrated on a corpus of modernist fiction.
The guidelines have been published in a special issue of The Journal of Cultural Analytics (vol. 6, issue 4) entirely devoted to the illustration of the Systematic Analysis of Narrative levels Through Annotation (SANTA) project, serving as the broader intellectual context to the guidelines. All articles in the special issue are open peer reviewed , open access, and are available in both PDF and XML formats.
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GitHub – CateAgostini/IIIF

GitHub – CateAgostini/IIIF

Introduction: In this resource, Caterina Agostini, PhD in Italian from Rutgers University, Project Manager at The Center for Digital Humanities at Princeton shares two handouts of workshops she organized and co-taught on the International Image Interoperability Framework (IIIF). They provide a gentle introduction to IIIF and clear overview of features (displaying, editing, annotating, sharing and comparing images along universal standards), examples and resources. The handouts could be of interest to anyone interested in the design and teaching of Open Educational Resources on IIF.
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Find research data repositories for the humanities – the data deposit recommendation service

Find research data repositories for the humanities – the data deposit recommendation service

Introduction: Finding  suitable research data repositories that best match the technical or legal requirements of your research data is not always an easy task. This paper, authored by Stephan Buddenbohm, Maaikew de Jong, Jean-Luc Minel  and Yoann Moranville showcase the demonstrator instance of the Data Deposit Recommendation Service (DDRS), an application built on top of the re3data database specifically for scholars working in the Humanities domain. The paper  also highlights further directions of developing the tool, many of which implicitly bring sustainability issues to the table.

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BERT for Humanists: a deep learning language model meets DH

BERT for Humanists: a deep learning language model meets DH

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’).

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TAO IC Project: the charm of Chinese ceramics.

TAO IC Project: the charm of Chinese ceramics.

Introduction: Among the Nominees in the ‘Best DH Dataset’ of the DH Awards 2020, the TAO IC Project (http://www.dh.ketrc.com/index.html) leads us in a fascinating journey through the world of Chinese ceramics. The project, which is developed in a collaborative way at the Knowledge Engineering & Terminology Research Center of Liaocheng (http://ketrc.com/), exploits an onto-terminology-based approach to build an e-dictionary of Chinese vessels. Do you want to know every detail about a ‘Double-gourd Vase I’? If you consult ‘Class’ in the ‘Ontology’ section (http://www.dh.ketrc.com/class.html), you can discover the component, the function, from what such a vessel is made of, and what is the method to fire it. If you also wish to see how the vase appears, under ‘Individuals’ of the same section you can read a full description of it and, also, see a picture (http://www.dh.ketrc.com/class.html). All this information is collected in the e-dictionary for each beautiful item belonging to the Ming and Qing dynasties.

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