MODELLING AND VISUALIZING TEXTUAL DATA

Academic year
2020/2021 Syllabus of previous years
Official course title
MODELLING AND VISUALIZING TEXTUAL DATA
Course code
FM0486 (AF:335468 AR:175892)
Modality
On campus classes
ECTS credits
6
Degree level
Master's Degree Programme (DM270)
Educational sector code
L-FIL-LET/08
Period
3rd Term
Course year
2
Moodle
Go to Moodle page
This course aims at providing the methodological and practical knowledge to develop a digital (scholarly) project from a theoretical assumption. Starting from the definition of a project's scope it will be made a critical strategic planning step of the development project. Students will know some principles to model information and create practically a project that can gather different kinds of resources from the Web.
In this course, students will learn how to plan, analyze risks and factors in which projects can be successfully published. In addition, the students will be able to understand the importance of data modeling and metadata in order to access, interchange data, and to publish on the Web.
Pre-requirements are knowledge of XML/TEI and HTML/CSS. Some knowledge of programming languages and GitHub are preferable.
Project management: description of the aims and goals of a possible project and how to achieve it

Selecting materials and planning strategies for the workflow to create a digital object
Data modeling and introduction of LOD and Semantic Web
IIIF (International Image Interoperability Framework)
Extracting and Data visualization strategies


Arianna Ciula, Øyvind Eide, Cristina Marras, Patrick Sahle, Models and Modelling Between Digital and Humanities: A Multidisciplinary Perspective, GESIS - Leibniz Institute for the Social Sciences, 2018

Julia Flanders, Fotis Jannidis, The Shape of Data in the Digital Humanities: Modeling Texts and Text-based Resources, Taylor & Francis, 2018

USEFUL LINK:

IIIF (International Image Interoperability Framework) - https://iiif.io/
Linking Open Data cloud diagram <http://lod-cloud.net/> ;
Linked Open Vocabularies (LOV) <http://lov.okfn.org/dataset/lov/> ;
W3C, Linked data <https://www.w3.org/standards/semanticweb/data> ;;
The assessment will be based on the following components:
1. Final oral exam.
2. Participation to class discussions.
3. Assignments and course activities.

Attendance is strongly recommended. Non-attending students are strongly invited to contact the teacher to get some explanations and avoid any misunderstanding about the course contents and reading materials.
Classes with activities in and outside the class, and interaction between professors and students.
Attendance is strongly recommended.
Materials and resources will be made available through the Moodle e-learning platform.
English
oral
Definitive programme.
Last update of the programme: 01/10/2020