MODELLING AND VISUALIZING TEXTUAL DATA

The course Modelling and Visualizing Textual Data is part of the Master’s degree Programme in Digital and Public Humanities and is connected with the Venice Centre for Digital and Public Humanities (VeDPH) in the Department of Humanities. It aims to provide students with a methodological framework on the concepts of modelling and data visualization, with a specific focus on literary texts.

Students will consolidate their theoretical knowledge in the field of modelling, acquiring practical skills in the design, management, and implementation of a data model. They will learn to use computational techniques and tools to analyze features of a literary textual corpus. Students will be able to critically evaluate the results obtained, identifying both the potential and the limitations. The skills acquired will be applied to a specific textual corpus, thus providing hands-on experience with modelling and visualization processes.

The course includes a hands-on component in the classroom and requires basic knowledge of programming (Python), as well as familiarity with data aggregation methods (XML, JSON, CSV).

This course provides a theoretical introduction to the concept of model and the practice of modelling and visualizing data in the field of Digital Humanities, with a specific focus on the modelling and visualization of resources based on literary textual data.
The course will address the following key topics:
• Modelling spatial and temporal data.
• Data structures and ontologies.
• Data modelling
• Operationalizing
Students will actively engage in a project based on the literary corpus. Through this project, they will apply computational methods to analyze the characteristics of the corpus, gaining hands-on experience in modelling and visualization techniques.

The Shape of Data in Digital Humanities. Modeling Texts and Text-Based Resources, edited by Julia Flanders and Fotis Jannidis, Routledge 2019

The final exam is designed to assess the skills acquired during the course. The evaluation will focus on the students’ disciplinary knowledge, as well as their critical and methodological abilities developed through lectures and individual study. The questions will cover topics discussed in class, activities carried out during the course, and any optional projects that students may choose to present during the exam.

oral

Under 18: Fail - insufficient knowledge of and ability to understand the topics of the course - insufficient level of execution of class and home activities
Grades 18-21: - sufficient knowledge of and ability to understand the topics of the course - sufficient level of execution of class and home activities
Grades 22-24: - satisfactory knowledge of and ability to understand the topics of the course - satisfactory level of execution of class and home activities
Grades 25-27: - good knowledge of and ability to understand the topics of the course - good level of execution of class and home activities
Grades 28-30: - very good or excellent knowledge of and ability to understand the topics of the course - very good or excellent level of execution of class and home activities

In order to achieve the expected learning outcomes, the following activities are envisaged: 1) lectures, study and deepening of the bibliography; 2) guided exercises: 3) class discussion. Materials and resources will be madre available through the e-learning platform

Accessibility, Disability and Inclusion.
Accommodation and support services for students with disabilities and students with specific learning impairments:
Ca’ Foscari abides by Italian Law (Law 17/1999; Law 170/2010) regarding support services and accommodation available to students with disabilities. This includes students with mobility, visual, hearing and other disabilities (Law 17/1999), and specific learning impairments (Law 170/2010). If you have a disability or impairment that requires accommodations (i.e., alternate testing, readers, note takers or interpreters) please contact the Disability and Accessibility Offices in Student Services: disabilita@unive.it.