48693 - Computer Science for Cultural Heritage

Learning outcomes

The course provides students with an overall knowledge of technologies and IT tools to support the study of cultural heritage: digital transposition and analysis of objects and documents, organization of databases, ontologies and semantic web, three-dimensional acquisitions and virtual reconstructions by computer graphics. Through case studies in the various areas of cultural heritage (archaeological, historical-artistic and architectural, archival-library and music), the student acquires critical competence on the main digital technologies useful for the knowledge, conservation and enhancement of cultural heritage.

Course contents

First of all, some basic concepts of computer science will be presented and explained according to a humanistic approach to the subject: meaning and implications of the adjective digital, computers, computational thinking and data structures, algorithms and computability, programming languages. Then we will try to understand how computer science has been used for the protection and enhancement of cultural heritage by reviewing the main tools and methodologies starting from the first applications of computer science to cultural heritage (databases). Special attention will be paid to the relationship between disruptive technologies (digital breaking) and cultural heritage. Among these disruptive technologies, artificial intelligence (AI) and its applications (machine learning systems) in the field of cultural heritage will be studied. Subsequently, the concept of digital cultural heritage will be discussed and digital cultural resources (from their representation and dissemination on the web to their preservation) will be analysed. Talking about the evolution of the Internet, the metaverse as a mix of virtual, augmented, blockchain and other technologies will be analysed. Particular attention will be paid to technologies for the creation of digital originals of works of art (Digital Art Work) and certificates of ownership on digital originals registered on blockchain (Non Fungible Tken).

Readings/Bibliography

Reference texts for exam preparation:

F. Tomasi, Metodologie e discipline umanistiche (Carocci editore, Rome, 2008). Excluding chapters 7 and 5.
Anne Burdick - Johanna Drucker - Peter Lunenfeld - Todd Presner - Jeffrey Schapp, Digital Humanities, Oscar Mondadori, Milan, 2014.
For those with insufficient basic knowledge of computer science, the following texts are also recommended:

Curtin - Foley - Sen - Morin, Italian edition edited by A. Marengo Alessandro Pagano, Basic Computer Science. With online update. With e-book, 6th edition, McGraw-Hill Education, Milan, 2016.
Stefano Allegrezza, Basic Informatics. Conoscere e comprendere le risorse digitali nella società dell'informazione, Edizioni Simple, Macerata, 2009.

Teaching materials by the lecturer will be available on the virtual platform (https://virtuale.unibo.it ). To access the virtual platform it is necessary to include the course in your syllabus. All the material provided will be in Italian. Studying the material provided is not sufficient to pass the exam with flying colours.

Publications of particular guidance
For an introduction to computer science, telematics and their applications in the humanities, see Marco Lazzari, Informatica Umanistica, McGrawHill, Milan, 2014.On storage devices and preservation of digital documents, see Stefano Allegrezza, Le memorie per la conservazione a lungo termine dei documenti digitali, Edizioni Simple, Macerata, 2013. On standards for file formats, see Stefano Pigliapoco - Stefano Allegrezza, Digital Document Production and Preservation. Requisiti e standard per i formati informatici, Vol. 1, edited by Stefano Pigliapoco, Edizioni Simple, Macerata, 2008. On the representation and storage of information, publication and retrieval of information on the Web and the Web, see Silvana Castano - Alfio Ferrara - Stefano Montanelli, Informazione, conoscenza e web, Pearson, 2009.

Teaching methods

Classroom lessons and computer lab.

Assessment methods

The examination consists of an oral interview aimed at assessing the knowledge and the critical and methodological skills acquired by the student, who will be invited to discuss the texts, themes and methodological issues addressed during the course and during the exercises. Possible tests (with multiple-choice question, multiple answer, true or false statement, open answer, word association, customised question) may be administered on the EOL platform.
For non-attending students, in addition to the previous syllabus , there are additional questions on some essays, always related to the topics covered in the course. Links to the essays are available on the course webpage on the virtual.unibo.it platform.
In the assessment of the examination, particular account will be taken of the student's ability to know how to navigate within the sources, topics covered in class and the examination bibliography to illustrate themes and problems, and to be able to make connections between them.
The student's mastery of the contents and ability to synthesise and analyse themes and concepts and the ability to express himself/herself adequately and in language appropriate to the subject matter will be assessed.

The student's attainment of an organic view of the topics addressed in the lectures together with their critical utilisation, a good mastery of expression and specific language will be assessed with marks of excellence; formative gaps and/or inappropriate language - albeit in a context of minimal knowledge of the examination material - will lead to marks that do not exceed sufficiency.

Teaching tools

At the beginning of the course, a cognitive survey will be conducted on the training and basic IT knowledge/skills possessed by the students by means of a questionnaire with multiple choice, true/false, short answer and open answer type questions. This cognitive survey will allow the lecturer to calibrate the lessons in order to homogenise the students' skills and fully ensure the teaching effectiveness of the course.
Monitoring of learning at the end of each topic covered in class with questionnaires to direct, modify, make the learning process more effective.
Online collaborative teaching tools to supplement traditional classroom teaching activities: Moodle platform, forum, chat, web conference wiki.
Use of content (textual and multimedia teaching materials, videos, exercises) available on the delivery platform Online teaching to registered trainees.
Online teaching resources: Sitography.

Office hours

See the website of Stefano Russo