Data visualization

This course offers a general picture of managing speech corpora and of the methods that are available for the acoustic-phonetic study of speech. During the course, students use a speech analysis program called Praat and learn to apply the main features of the program in their own work with speech recordings. In addition, students will learn the basics of another program called ELAN that can be used for transcribing and annotating audio as well as video material.

Taken from: Teaching with CLARIN: https://www.clarin.eu/content/introduction-speech-analysis

The aim of the course is to introduce digital humanities and to describe various aspects of digital content processing. The practical aims consist of introducing current data sources, annotation, pre-processing methods, software tools for data analysis and visualisation, and evaluation methods.

Currently, we identified that students are somewhat aware of digital humanities but it is difficult for them to dive in and, mainly, to anticipate what they should learn for their future research. A more detailed goal of this course is to present some current projects, show the datasets and technologies behind, and encourage students to explore the datasets and use the technologies on data they already know. A high level goal is to set the knowledge of the technologies and available datasets into the research iteration loop (create hypotheses -> design instruments -> collect data -> analyze and evaluate).

Taken from: Teaching with CLARIN: https://www.clarin.eu/content/introduction-digital-humanities

The course demonstrates how HFST tools can be used for generating finite-state morphologies. Through practical exercises, students will learn how to use finite-state methods to develop a morphology for a language. This online course is suitable as a complement to a more theory or linguistics-oriented course on morphology.

After successfully completing the course:

- you can explain the basic theory on finite-state automata and transducers,

- you can design morphological lexica using finite-state technology,

- you know how to write morpho-phonological rules in a finite-state framework,

- you understand the diversity of morphological structure in different languages

 and you know how to take these differences into account when designing computational models of morphology.

Taken from Teaching with CLARIN: https://www.clarin.eu/content/computational-morphology-hfst 

Goals and objectives of the training materials:

• to improve textual criticism on ancient Greek fragmentary texts (research skills and data acquisition skills: research data management + text analytics)
• to improve competence on text annotation (research skills and data acquisition skills: analytical thinking + text annotation);
• to reach a reliable corpus for a digital scholarly edition of an ancient Greek poet (research skills and data handling: research methods + data repositories + data formats and standards).

Taken from Teaching with CLARIN: https://www.clarin.eu/content/archilochus-paros-elegiac-fragments-xml-archive

The original code plus some variants that contain extensions, especially a new function extracting relations between editors. Note that extended versions might include additional computational steps that can lead to higher runtimes than the original. 

Service based on Jupyter Notebook enables the creation and sharing of documents containing “live” code, equations, visualisations and texts. It allows to write simple programs, numerical simulations, statistical modeling, data visualization and much more.

A prototype "game" created for use on the British Library's crowd-sourcing arcade machine. Players have to flag up errors in the OCR transcriptions of content taken from the Qatar Digital Library.

A IIIF powered, Chrome extension that displays a random map from the David Rumsey Map Collection everytime you open a new tab in your browser. Built using Leaflet-IIIF and React.js.

The University of Glasgow has a range of resources to support researchers seeking to manage their research data. These resources include the Research Data Management Service, the Research Data Management Webpages and Enlighten: Research Data, the University's research data repository.

CORD (Cranfield Online Research Data) is an institutional data repository, where you should store any research data that must be preserved, if there is no appropriate funder or subject repository (e.g. NERC data centres). Fundamentally, remember that data must only be added to CORD with public access if you have the right to share it.