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|Title:||Contemporary Digital Humanities|
|Publisher:||Teaching Hub, Nipissing University|
|Series/Report no.:||https://openlibrary.ecampusontario.ca/item-details/#/750bf7f8-e98d-469b-b51f-504091c555ef | https://openlibrary.ecampusontario.ca/item-details/#/78cc529e-9545-475f-a9c0-6d23ab2ab0ba | https://openlibrary.ecampusontario.ca/item-details/#/6e9c6e74-2646-4f37-bba7-868b573c6279 | https://openlibrary.ecampusontario.ca/item-details/#/3d2c9f12-58bd-4e64-b11d-0ab072f20426 | https://openlibrary.ecampusontario.ca/item-details/#/787a7042-7607-478a-b9ee-bd4f98c88185|
|Abstract:||Defining the digital humanities (DH) is an elusive task. It is an emerging interdisciplinary field that encompasses humanities scholarship, computation, analysis, and applications. DH is a vast field with many sub-areas of scholarship. Consequently, the six courses in this certificate are limited to a small number of timely and relevant topics.|
The first course is a contemporary introduction to the digital humanities covering: current and emerging sub-areas; major digital humanities projects; the importance of the Internet; an introduction to basic computational terminology and methods; the basic concepts of text processing; the relationship between tools and methods; criticisms of the digital humanities; and possible futures of the digital humanities.
The second course introduces the fundamental concepts of tool-building techniques in the digital humanities. It includes the principles of data science; Big Data; visualization (an increasingly important component in digital humanities scholarship); and the basics of Python and R, the two most widely used programming languages for tool-building in humanities scholarship; implementations of basic text processing methods, and other applications. Python and R code is provided for the examples in this course. In addition, most of the figures were generated with Python or R code, and this code is also provided.
The third course focuses on intermediate and advanced text processing techniques and visualization methods in the digital humanities. Python and R code are again provided for all examples. Digital tools and techniques are presented for different application areas. In addition to interactive tutorials, advanced techniques that are increasingly used in humanities scholarship, including machine learning, are introduced in a non-mathematical manner.
The fourth course examines the application of open access digital technology, such as machine actionable lexicographical tools, digital text repositories, and digitized collections of ancient material culture, to otherwise traditional methods and techniques of Classical Studies research.
The fifth course examines how the reception of Ancient Greece and Rome in the modern world has taken new directions through digital technology, including the storage and dissemination of pre-digital receptions in digital form. It explores the reception of the Classical World in digital cinema and TV, digital gaming, and in the performance of Greek tragedy both in digital environments and in virtual reality.
The sixth course focuses on the emerging area of the spatial humanities, with emphasis given to digital history and digital storytelling. Learners are introduced to GIS tools. They also learn how to access, interpret, and synthesize spatial and archival data and create their own digital maps, using historical GIS to communicate place-based narratives.
|Appears in Collections:||Ontario OER Collection|
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|Python R Jupyter Data Files.zip||%%dl%% Zip File (Python, R, and Jupyter files)||252.4 kB||zip||View/Open|
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