Content (Syllabus outline):

• an overview of the digital methods in archaeology and cultural heritage
• selected methods of digital archaeology; the student chooses one or more methods, including but not limited to airborne LiDAR and remote sensing, artificial intelligence/machine learning/deep learning, data science, 3D models, GIS.

Readings:

• Bahn P. G., Renfrew C. (2018). Archaeology essentials, theories, methods, practice, Thames & Hudson College, London. (Chapters 1 and 3).
• Chapman, H., (2006) Landscape archaeology and GIS. The History Press Limited, Stroud.
• Conolloy J., Lake M. (2006). Geographical Information Systems in Archaeology, Cambridge: Cambridge University Press.
• Dell’Unto N., Landeschi G. (2022). Archaeological 3D GIS. London: Routledge.
• Garstki, K. (2020). Digital innovations in European archaeology. Cambridge University Press, Cambridge.
• Garstki, K. (ed.) (2022). Critical Archaeology in the Digital Age. 12th IEMA Visiting Scholar Conference. Cotsen Insititute of Archaeology Press, Los Angeles, CA.
• Lock G. (2003). Using Computers in Archaeology, Towards Virtual Pasts. Routledge, London.
• Lock, G.R., Hacıgüzeller, P., Gillings, M. (eds.) (2019). Re-mapping archaeology: critical perspectives, alternative mappings. Routledge, Abingdon, Oxon ; New York, NY.
• Lozić, E. (2021). Application of Airborne LiDAR Data to the Archaeology of Agrarian Land Use: The Case Study of the Early Medieval Microregion of Bled (Slovenia). Remote Sensing 13(16), 3228.
• Lozić, E., Štular, B. (2021). Documentation of Archaeology-Specific Workflow for Airborne LiDAR Data Processing. Geosciences 11(1), 26.
• Forte M., Campana S., eds., (2016). Digital Methods and Remote Sensing in Archaeology. Archaeology in the Age of Sensing. Springer.
• Parcak, S.H., (2009). Satellite Remote Sensing for Archaeology. Routledge, London ; New York.

Objectives and competences:

Digital archaeology is concerned with digital data for archaeological research as well as the computational methods and tools necessary to collect, analyse, and manage them.

The use of computers in archaeology dates back to the 1960s, and archaeology is currently one of the most digitised fields in humanities. Computer tools such as spatial analysis, three-dimensional modelling, simulations, and the analysis of archaeological plans have opened up new avenues for archaeological research and significantly increased our knowledge of the past. Our proficiency in surveying, remote sensing, spatial analysis, and data management encompasses the total workflow of archaeological research.

The objectives of the course are to train students for independent research work in the field of archaeology using relevant digital tools.

The competences that students will acquire are: the use of general digital tools, such as digital databases, and the use of other selected digital tools, such as the use of LiDAR data, the use of GIS.

Intended learning outcomes:

Students of Digital Archaeology will learn how to collect digital data in the field using our cutting-edge surveying equipment, as well as how to process, visualise, analyse, interpret, manage, and present digital data in our computer laboratory. Our network of national and international partners offers numerous opportunities for hands-on training and exchange, as well as access to specialised equipment.

The majority of digital tools are bringing positive changes to archaeology, but the introduction of new methods requires a critical approach. Do 3D models actually provide answers to research questions? Are sophisticated computational methods always required for data organisation? Students will acquire the skills necessary to independently apply and evaluate the incorporation of contemporary technological tools in archaeology. Students will be able to independently complete projects utilising GIS tools, as well as use hardware and software for data digitisation and collection, data analysis, modelling and visualisation, and computerisation of cartographic material.

Learning and teaching methods:

Types of learning/teaching:

• Work in smaller groups or pair work
• Independent students work
• e-learning

Teaching methods:

• Explanation
• Conversation/discussion/debate
• Case studies
• Field work (e.g. company visits)

Assessment

• 70 % Long written assignments
• 20 % Presentations
• 10 % Final examination (written/oral)