Module CLAS20E1: Digital Humanities and the Ancient World

Department: Classics and Ancient History

CLAS20E1: Digital Humanities and the Ancient World

Prerequisites

• None

Corequisites

• None

Excluded Combination of Modules

• None

Aims

• To provide an overview into fundamental Digital Humanities methods and theories applied to the study of the ancient world, from the digitisation of ancient artifacts to their analysis with computational techniques.
• To investigate the complex relationship between quantitative methods and qualitative inquiry, and observe how historical research may at the same time challenge and enrich our understanding of technology.
• To help students problematize traditional scholarly concepts through the constraints of structured analysis, through a more nuanced understanding of key ideas like "place", "relation", "document", or "event".
• To support the building of basic digital and data literacy skills, including but not limited to methods for data gathering, design of structured datasets, spatial and visual literacy, evaluation of quantitative outputs, etc.

Content

• The course will present a survey into the use of digital humanities methods for the study of the ancient world. Topics might include, but are not limited to: digitisation of ancient inscribed objects; digital editing; understanding ancient texts as structured data; Named Entity annotation and disambiguation; fundamentals of network analysis; mapping and GIS; machine learning and generative AI; analysis of ancient texts with distant reading.
• Students will be introduced to the theoretical framework and key definitions of digital methods. In the practicals, they will have the opportunity to work with each method through hands-on supervised activities. This will help them to the challenging relationship between quantitative methods and qualitative/historical analysis, emphasizing the ambiguity, uncertainty and fragility of ancient world ‘data’.
• This module uses a ‘Minimal Computing’ approach: no experience in coding and programming is required. For students who already have some knowledge of programming, this module will offer a different point of view into computer science, examining the application of quantitative methods to historical documents.
• The summative assessment will consist of a research project that will apply one or more of the methods presented during the course to an ancient corpus (texts, artifacts, sites, collections). The students will create structured datasets to collect the evidence, manipulate them for visualization and/or analysis, and interpret them through the theoretical framework provided to them during the lectures. They will submit the dataset and a 2,500 word project report, discussing the corpus, the method, the constitution of the dataset, and the results of the analysis.

Learning Outcomes

• Theoretical and practical knowledge of the most important processes of digitization, visualization, and computational analysis of ancient corpora, including objects, sites, and texts.
• Critical understanding of what it means to apply quantitative methods to qualitative or unstructured evidence, and the (ethical, practical and scientific) implications of this process.
• Knowledge of the most important standards and data formats used for the digital analysis of ancient sources.
• Engagement with current scholarship in Digital Humanities, particularly the emerging field of Digital Classics.

• Ability to choose, utilize, and understand fundamental digital and computational methods to explore different facets of the ancient world.
• Ability to evaluate computer-generated outputs (visual, numerical, cartographic) for the purposes of historical analysis.
• Ability to conceive, plan, motivate, and carry to completion an academic research project with an emphasis on digital methods.

• Essential visual, spatial, and data literacy skills.
• Fundamentals of Spatial Information Analysis and GIS.
• Fundamentals of Network Analysis.
• Fundamentals of text analysis: Named Entity Recognition and Classification, Distant Reading, Linguistic analysis, Data visualization, etc.
• Fundamentals of Semantic Annotation and Linked Open Data.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• This course leverages on an integrated notion of training and education. In Digital Humanities, the development of a practical skillset is structurally integrated with discursive interpretation and critical thinking. Lectures will provide the essential theoretical framework to better understand the background and implications of specific digital methods and tools. Laboratory hours will emphasize the practical use of these methods on documents and artifacts from antiquity, to empower and problematize their study and their interpretation.
• Assessments will test the ability of the students to conceive, plan, motivate, and complete a research project that analyses an ancient corpus using one or more of the digital methods studied during the course. The students will be required to submit the data produced in a structured format, alongside a Project Report where they will discuss the broader theoretical framework of the method/s used, how they supported their analysis, the challenges and potential pitfalls, and the results.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University