Are you interested in working with digital tools that you could use in your field? Do you want to know the latest trends in digital research? See what courses in Digital Humanities you can enroll in at the Faculty of Arts! Do you want to know how to digitize, process and visualize textual, spatial or image data? See what Digital Humanities courses you can enrol in at the Faculty of Arts in the academic year 2022/23!
ONLINE COURSE
An online course that guides you through the entire process of working with data in the humanities, from its acquisition through digitization or directly from digital sources, through cleaning, processing and analysis of different types of data, to presentation in the form of visualization or publication and final archiving. You will learn, among other things, how the digitization of old prints and books is done in practice, how neural networks help computers "see" visual materials, how to read hundreds of books with a computer, why network analysis is of interest to epidemiologists, historians and sociologists, or how to fight disease or crime with data visualizations.
In this course, you will learn how to use simple tools for text analysis, spatial data analysis, mapping, and network analysis, all without any prior knowledge of these tools. The course is delivered in the form of online lectures, where you will learn how research projects in the Digital Humanities are created and, through mini-tasks, you will try your hand at working with some simple tools for text analysis, mapping, or data visualization.
01 // The digital turn in the humanities
In this lecture, you will learn about the history of Digital Humanities, the key projects that have determined the direction of this field and the institutions that enable its development and functioning in the Czech Republic and worldwide. The lecture will also present what the so-called "digital turn" has meant for the humanities and how it has affected research methods and practices.
02 // Digitization and digital data sources
DIgital and digitized data are key materials for research in the Digital Humanities. Much of it comes from digitized text, images, or other materials. This session will offer insight into the digitization process.
03 // Acquiring and cleaning digital data
In this lecture, you will learn both how to extract (scrape) data from digital sources - i.e. mainly websites, databases and social networks - and how to clean it afterwards using some basic techniques.
04 // Metadata
The content and main topic of this lecture is metadata, which is a key element for the proper functioning of databases and subsequent work with data not only in digital form.
05 // Text data
The content of this lecture is quantitative text processing. By the end of it, you should have an understanding of the distant reading method, natural language processing and its applications, corpus linguistics, sources of textual data and corpora, methods of text data mining, tools available for working with corpora, and basic text analysis. It would be beneficial to become familiar with the basic Voyant tools environment prior to the lecture.
06 // Image data
The subject of this lecture is image data. You will learn how computer processing of image data works, its use in cultural heritage, and the research opportunities presented by Cultural Analytics.
07 // Spatial data
This lesson introduces students to the basics of cartography and geoinformatics. It will also include a small hands-on demonstration of working with maps in QGIS software.
08 // Sound data
This lecture covers audio signal processing with a focus on music. You will learn what can be detected in a music signal and how mathematics and programming can be combined with music and end users. The lecture will cover, among others, the following topics:
09// Network Analysis
The main topic of this lecture is network analysis. In this lecture you will learn what the basic elements of networks are, where networks can be found everywhere, and how data for network analysis is created. In a hands-on workshop, you will try your hand at visualizing networks using GraphCommons.
10 // Data visualization
Data visualization is one of the most important areas of data processing. It can be used not only for data presentation, but also in the actual data analysis. This lesson will introduce the main principles of data visualization and the tools that enable it.
11 // Publishing data
In this lecture, you will learn why this is important at all and how it fits into the modern trends of contemporary science. We'll discuss where publication stands in the so-called data lifecycle and why it's important to think about it from the beginning of the creation of specific data.
12 // Data archiving
This talk will introduce the basic principles of data archiving and storage and some of the tools that are used in long-term data protection.
For those who are mainly interested in textual data and its processing, and are not afraid of a bit of coding, there is a course Introduction to Digital Humanities, taught by RNDr. Zuzana Nevěřilová, Ph.D. In this hands-on course, you will learn the basic commands for text analysis in a Python environment. By the end, you will be able to use Python to perform basic operations on text in corpora such as word counting, determining the most commonly used terms, or lemmatization.
The course, which this time focuses on digital approaches in various auxiliary historical sciences and archives, concentrates on five main topics (Digitization in Memory Institutions, Metadata and Metadata Standards, Working with Image Data, Text Analysis and Markup in XML, Spatial Data and Networking and Data Visualization). The course presents examples of good practice in these areas, and also introduces students to a few selected tools in the final project.
This course aims to introduce students to research on book culture in the context of digital humanities. The course focuses on the presentation of older book culture in the digital environment, both of particular types of old media (manuscripts, incunabula, old prints) and new directions in old media research.
The aim of this course is to teach students new strategies for conducting research on collections in libraries, archives, museums and other cultural heritage institutions; to understand how to research cultural heritage collections and collect information related to these collections and make it available for presentation, research and education.
In addition to the courses mentioned above, which represent different areas of Digital Humanities, there are also a number of courses at MUNI that focus on specific methods such as Geographic Information Systems and Mapping, Network Analysis, or Natural Language Processing. Many of these courses are also open to students outside of their parent disciplines. All courses can be found in the Course Catalog by entering an appropriate keyword in the search box.
This introductory course into Digital Humanities will teach you how to analyse textual, spatial and image data using digital tools. Now under the code ISKB83.
Maps give us information not only about specific places, but also about the relationships between space, time and human activity. We can study space and its meaning in literary science, history or linguistics. In the context of the humanities, spatial data offer insights into historical, cultural and social phenomena.
