SPARQL for music: when melodies meet ontology

SPARQL for music: when melodies meet ontology

Introduction: Developed in the context of the EU H2020 Polifonia project, the investigation deals with the potentialities of SPARQL Anything to
to extract musical features, both at metadata and symbolic levels, from MusicXML files. The paper captures the procedure that has applied by starting from an overview about the application of ontologies to music, as well as of the so- called ‘façade-based’ approach to knowledge graphs, which is at the core of the SPARQL Anything software. Then, it moves to an illustration of the passages involved (i.e., melody extraction, N-grams extraction, N-grams analysis and exploitation
of the Music Notation Ontology). Finally, it provides some considerations regarding the result of the experiment in terms of effectiveness of the queries’ performance. In conclusion, the authors highlight how further studies in the field may cast an increasingly brighter light on the application of semantic-oriented methods and techniques to computational musicology.
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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.

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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LoGaRT and RISE: Two multilingual tools from the Max Planck Institute for the History of Science

LoGaRT and RISE: Two multilingual tools from the Max Planck Institute for the History of Science

Introduction: This post introduces two tools developed by the Max Planck Institute for the History of Science, LoGaRT and RISE with a focus on Asia and Eurasia. […]The concept of LoGaRT – treating local gazetteers as “databases” by themselves – is an innovative and pertinent way to articulate the essence of the platform: providing opportunities for multi-level analysis from the close reading of the sources (using, for example, the carousel mode) to the large-scale, “bird’s eye view” of the materials across geographical and temporal boundaries. Local gazetteers are predominantly textual sources – this characteristic of the collection is reflected in the capabilities of LoGaRT as well, since some of its key capabilities include data search (using Chinese characters), collection and analysis, as well as tagging and dataset comparison. That said, LoGaRT also offers integrated visualization tools and supports the expansion of the collection and tagging features to the images used in a number of gazetteers. The opportunity to smoothly intertwine these visual and textual collections with Chinese historical maps (see CHMap) is an added, and much welcome, advantage of the tool, which helps to develop sophisticated and multifaceted analyses.
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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…

Getting started with OpenRefine – Digital Humanities 201

Getting started with OpenRefine – Digital Humanities 201

Introduction: Open Refine, the freely accessible successor to Google Refine, is an ideal tool for cleaning up data series and thus obtaining more sustainable results. Entries can be searched in alphabetical order or sorted by frequency, so that typing errors or slightly different variants can be easily found and adjusted. For example, with the help of the software, I discovered two such discrepancies in my Augustinian Correspondence Database, which I am now able to correct with one click in the programme. I was shown that I had noted “As a reference to Jerome’s letter it’s not counted” five times and “As a reference to Jerome’s letter, it’s not counted” three times. Consequently, if I searched the database for this expression, I would not see all the results. A second discrepancy was between the entry “continuing reference (marked by Nam)” and the entry “continuing reference (marked by nam)”. Thanks to Open Refine, such errors can be completely avoided in the future.

The tutorial by Miriam Posner is a useful introduction to come in touch with the software. However, the first step of the installation is already out of date. While version 3.1 was still the latest when the tutorial was published, it is now version 3.5.2. Under Windows, you can now distinguish between a version that requires Java and a version with embedded OpenJDK Java, which I found very pleasing.

If needed, there are links at the end of the tutorial to other introductions that go into more depth.

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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