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.

A. Ciula, Ø. Eide, C. Marras, P. Sahle, "Modelling Between Digital and Humanities. Thinking in Practice", Open Book Publisher 2023. DOI: https://doi.org/10.11647/OBP.0369

F. Moretti, "Operationalizing": Or, the function of measurement in modern literary theory", Pamphlet 6, December 2013, available through Stanford Literary Lab: https://litlab.stanford.edu/pamphlets/
F. Moretti, "Network Theory, Plot Analysis", Pamphlet 2, May 2011, available through Stanford Literary Lab: https://litlab.stanford.edu/pamphlets/
F. Moretti, "Literature, Measured". Pamphlet 12. April 2016, available through Stanford Literary Lab: https://litlab.stanford.edu/pamphlets/

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

In order to obtain a mark between 27 and 30 cum laude, students are expected to analyse in depth the topics of the course following the methodological guidelines acquired; to possess and communicate an organic understanding of the topics addressed in class and/or studied in the manual and critical texts in the bibliography and on the course Moodle; to demonstrate an excellent capacity for expression and argumentation; and to use the technical language of the discipline competently.
An overall mark between 23 and 26 will be awarded to those who demonstrate a good knowledge of the course program; the ability to analyse the topics in a methodologically correct way, even if marked by some imperfections; and a good command of language, although with occasional uncertainties in exposition and/or minor imprecision.
An acceptable but limited knowledge of the course program, a superficial understanding of the topics addressed, a restricted analytical ability, and expression that is not always appropriate will lead to sufficient marks (18–22).
Poor knowledge of the course topics, inadequate analytical skills, and incorrect or inappropriate expression will result in an insufficient assessment.

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.