Module 6: Cultural Heritage and Artificial Intelligence
Ioannis Blatsos
- Introduce students to the notions of artificial intelligence and cultural heritage
- Introduce students to EU funding for artificial intelligence use in cultural heritage and museums.
- Knowledge of the interplay between cultural heritage and new technologies
- Provide students with opportunities to apply theoretical knowledge to practical case studies
- Develop students' critical thinking skills, both as individuals and as members of a group
- Discuss and elaborate the main new technologies related to cultural heritage.
- Analyze in depth the most used new technologies related to cultural heritage.
- Introduce students to the notions of artificial intelligence and cultural heritage
- Introduce students to EU funding for artificial intelligence use in cultural heritage and museums.
- Knowledge of the interplay between cultural heritage and new technologies
- Provide students with opportunities to apply theoretical knowledge to practical case studies
- Develop students' critical thinking skills, both as individuals and as members of a group
- Discuss and elaborate the main new technologies related to cultural heritage.
- Analyze in depth the most used new technologies related to cultural heritage.
- Introduce students to the notions of artificial intelligence and cultural heritage
- Introduce students to EU funding for artificial intelligence use in cultural heritage and museums.
- Knowledge of the interplay between cultural heritage and new technologies
- Provide students with opportunities to apply theoretical knowledge to practical case studies
- Develop students' critical thinking skills, both as individuals and as members of a group
- Discuss and elaborate the main new technologies related to cultural heritage.
- Analyze in depth the most used new technologies related to cultural heritage.
Syllabus
Course Objectives/Goals
Upon the successful completion of the module the students will be able:
CO1. Understand and interpret the notions of artificial intelligence and cultural heritage
CO2. Detect and estimate the challenges related to use of artificial intelligence and cultural heritage.
CO3. Recognize and analyze the ways in which artificial intelligence and other cutting-edge technologies have improved cultural heritage protection, usage, and preservation.
CO4. Demonstrate ability to synthesize various and new methodological and technological solutions to allow catalysing possible interactions and aggregations between the various subjects involved in developing new applications in the cultural heritage sector.
CO5. Reflect upon their own learning process and develop their soft skills which are of great importance when dealing with the notions of artificial intelligence and cultural heritage.
Instructional Methods
The course is designed to develop different parts of the learning process, including asynchronous video recorded lectures, discussions on the online platform for specific and topical topics, developing new ideas, presenting, and solving questions and problems, and self-assessment exercises at the end of each module.
The instructor may upload notes, interactive presentations, quizzes, announcements, as well as any other additional multi-media material (videos, news reports, images, interviews, a/v documentation) on the Course’s webpage, which can be found at the electronic used by Ionian University. Moreover, students are required to use the discussion forum in order to communicate and interact with each other. Please note that, other than written text, your responses can include: hyperlinks related to the topic of discussion, video or other audiovisual material, self-recorded audio or video responses, questionnaires and polls, or, any other interactive resource. Students are advised to visit the platform on a regular basis in order to gain access to any newly uploaded educational material, since the above comprise a virtual learning environment for the Course.
Assessment Methods
The overall academic performance of students is based on the assessment of a written assignment, on a formative assessment, their performance in the final exams and the final assignment. A passing mark in the mid-term assignment is not a prerequisite for his/her participation in the final exams. The final grade awarded to each student is the sum of the grades awarded for the assignment and the final exams. Both the assignments and the final exams are marked in the scale 0 (complete failure) to 100 (absolute success). In order to get a passing mark in the Course, a student must receive a passing mark in the final exams. In a nutshell:
- The grade awarded for the assignment represents the 20% of the Course’s final grade.
- The grade awarded for the formative assessment activities represents the 20% of the Course’s final grade
- The grade awarded for the final exams represents the 60% of the Course’s final grade.
- In order to get an overall passing mark, a student must be graded with at least 50/100 in the final exams.
- Final assignment.
Bibliography
- European Commission (2022) Study on Quality in 3D Digitisation of Tangible Cultural Heritage: Mapping Parameters, Formats, Standards, Benchmarks, Methodologies, and Guidelines; VIGIE 2020/654 Final Study Report; European Commission: Brussels, Belgium.
- Fiorucci, M.; Khoroshiltseva, M.; Pontil, M.; Traviglia, A.; Del Bue, A.; James, S. (2020) Machine Learning for Cultural Heritage: A Survey. Pattern Recognit. Lett., 133, 102–108.
- Münster S, Maiwald F, di Lenardo I, Henriksson J, Isaac A, Graf MM, Beck C, Oomen J. (2024) Artificial Intelligence for Digital Heritage Innovation: Setting up a R&D Agenda for Europe. Heritage; 7(2):794-816.
- Rei, L.; Mladenic, D.; Dorozynski, M.; Rottensteiner, F.; Schleider, T.; Troncy, R.; Lozano, J.S.; Salvatella, M.G. (2023) Multimodal metadata assignment for cultural heritage artifacts. Syst., 29, 847–869.
Upon the successful completion of the module the students will be able:
CO1. Understand and interpret the notions of artificial intelligence and cultural heritage
CO2. Detect and estimate the challenges related to use of artificial intelligence and cultural heritage.
CO3. Recognize and analyze the ways in which artificial intelligence and other cutting-edge technologies have improved cultural heritage protection, usage, and preservation.
CO4. Demonstrate ability to synthesize various and new methodological and technological solutions to allow catalysing possible interactions and aggregations between the various subjects involved in developing new applications in the cultural heritage sector.
CO5. Reflect upon their own learning process and develop their soft skills which are of great importance when dealing with the notions of artificial intelligence and cultural heritage.
The course is designed to develop different parts of the learning process, including asynchronous video recorded lectures, discussions on the online platform for specific and topical topics, developing new ideas, presenting, and solving questions and problems, and self-assessment exercises at the end of each module.
The instructor may upload notes, interactive presentations, quizzes, announcements, as well as any other additional multi-media material (videos, news reports, images, interviews, a/v documentation) on the Course’s webpage, which can be found at the electronic used by Ionian University. Moreover, students are required to use the discussion forum in order to communicate and interact with each other. Please note that, other than written text, your responses can include: hyperlinks related to the topic of discussion, video or other audiovisual material, self-recorded audio or video responses, questionnaires and polls, or, any other interactive resource. Students are advised to visit the platform on a regular basis in order to gain access to any newly uploaded educational material, since the above comprise a virtual learning environment for the Course.
The overall academic performance of students is based on the assessment of a written assignment, on a formative assessment, their performance in the final exams and the final assignment. A passing mark in the mid-term assignment is not a prerequisite for his/her participation in the final exams. The final grade awarded to each student is the sum of the grades awarded for the assignment and the final exams. Both the assignments and the final exams are marked in the scale 0 (complete failure) to 100 (absolute success). In order to get a passing mark in the Course, a student must receive a passing mark in the final exams. In a nutshell:
- The grade awarded for the assignment represents the 20% of the Course’s final grade.
- The grade awarded for the formative assessment activities represents the 20% of the Course’s final grade
- The grade awarded for the final exams represents the 60% of the Course’s final grade.
- In order to get an overall passing mark, a student must be graded with at least 50/100 in the final exams.
- Final assignment.
- European Commission (2022) Study on Quality in 3D Digitisation of Tangible Cultural Heritage: Mapping Parameters, Formats, Standards, Benchmarks, Methodologies, and Guidelines; VIGIE 2020/654 Final Study Report; European Commission: Brussels, Belgium.
- Fiorucci, M.; Khoroshiltseva, M.; Pontil, M.; Traviglia, A.; Del Bue, A.; James, S. (2020) Machine Learning for Cultural Heritage: A Survey. Pattern Recognit. Lett., 133, 102–108.
- Münster S, Maiwald F, di Lenardo I, Henriksson J, Isaac A, Graf MM, Beck C, Oomen J. (2024) Artificial Intelligence for Digital Heritage Innovation: Setting up a R&D Agenda for Europe. Heritage; 7(2):794-816.
- Rei, L.; Mladenic, D.; Dorozynski, M.; Rottensteiner, F.; Schleider, T.; Troncy, R.; Lozano, J.S.; Salvatella, M.G. (2023) Multimodal metadata assignment for cultural heritage artifacts. Syst., 29, 847–869.
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