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R 4 aRchaeologists


In Humanities, the exponential increase in digital documentation requires us to question its management, its use, its availability to the scientific community and its sustainability. In archaeology, these issues are even more crucial because they relate to non-reproducible primary data. In order to effectively retrieve, store, manage, prepare for analysis, and communicate the information and the scientific range of such amount of data, modern archaeologists should be able to deal with concepts and tools related to new technologies. Such digital competencies are not present in a standard archaeology background, though they are fundamental to effectively interact with ICT experts.

The “R 4 aRchaeologists” Winter School aims for a fruitful combination of archaeology and statistics through the teaching of Data analysis, Data mining, and Data visualization techniques. It is conducted through R, programming language and free software environment for statistical computing and graphics. The large amount of data that are produced through archaeological work show a wide degree of heterogeneity, complexity, and interconnection, making the use of algorithmic methods unavoidable. R is one of the main programming languages of Data Science and includes a wide variety of statistical and graphical techniques: linear and nonlinear modelling, statistical tests, spatial statistics, time-series analysis, classiffication, clustering, and others.

The Winter School will last 60 hours and will take place from January 22th to February 2nd, 2024, at the Department of Civilisations and Forms of Knowledge of the University of Pisa, Italy.


  • David R. Carlson, Quantitative methods in archaeology using R, Cambridge University Press (June 26, 2017)
  • Nakoinz O. & Knitter D., Modelling Human Behaviour in Landscapes, Springer (2016)

The program will be activated also in distance learning mode (TEAMS platform).


The Winter School “R 4 aRcheologists” will enable participants to conduct statistical analysis and visualization of Archaeological data.
It is built around a new paradigm, which takes into consideration archaeologists as both producers and users of digital archaeological data.
Attendees will learn the concepts and methods of univariate and multivariate analysis, spatial analysis, and data visualisation through an integrated use of R ecosystem software packages, statistical and practical principles.

Who can apply

Students, graduates, PhD candidates, and post-docs in archaeology or related to Cultural Heritage.



Program Intensity



Admission Requirements

Specific computer science or technology skills are not required.
For an effective learning environment, the number of participants will be limited to 20.
Personal laptops are needed for attending the winter school.
Some introductory tutorials will be delivered to attendees before the School starts.

Required documents

  • Identity Document (*PASSPORT in case you are a foreign student*)
  • Enrolment Form
  • Curriculum Vitae

All the documents must be in pdf format, in order to upload them on the portal when required.

Application has to be submitted via Alice portal following the instructions of the "How to apply" page.




500 euro

Pay fees by Debit/Credit Card or PayPal online using the following form filling it with all the required data:

Payment Form 


  • International students without Italian Tax Code: please tick the box 'Anonymous' in order to disable the field 'Italian personal ID/VAT number'.
  • Please type your NAME and SURNAME next to the pre-filled text of the field 'Reason'
  • Please pay only after receiving the admission letter


Please write to the coordinator for further details.


22 January - 2 February 2024


22 December 2023


Prof. Gabriele Gattiglia Questo indirizzo email è protetto dagli spambots. È necessario abilitare JavaScript per vederlo. 
Dott. Nevio Dubbini Questo indirizzo email è protetto dagli spambots. È necessario abilitare JavaScript per vederlo. 


Summer/Winter School Office Questo indirizzo email è protetto dagli spambots. È necessario abilitare JavaScript per vederlo.

Ultima modifica: Mer 12 Giu 2024 - 09:43

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