Descrizione
The third volume of the ’30 anni di informatica archeologica’ series focuses on the quantitative approach to archaeological data analysis and explores the fifty-year evolution of Analyse des Données, starting with Jean-Paul Benzécri’s seminal 1973 work. The volume, prefaced by Tito Orlandi, features contributions from scholars directly involved in this evolution, highlighting the role and influence of the French school of data analysis, the dissemination of exploratory data analysis techniques, and their legacy in contemporary Data Science tools.
Sommario
- Prefazione, Tito Orlandi
- 1. Introduction, François Djindjian, Paola Moscati
- 2. The French school of data analysis, François Djindjian
- 2.1 Introduction
- 2.2 Jean-Paul Benzécri and his community
- 2.3 The statistical methods of the French school of data analysis
- 2.4 Fields of application
- 2.5 The key phases of data analysis in France
- 2.6 Conclusions .
- 3. Correspondence analysis: a ‘neglected multivariate method’ in the international panorama?, Paola Moscati
- 3.1 The statistical roots
- 3.2 The archaeological approach
- 3.3 Theoretical and practical developments of data analysis techniques
- 3.4 A literature-based analysis: the case of «Archeologia e Calcolatori»
- 4. Data analysis and prehistoric archaeology, François Djindjian
- 4.1 The influence of data analysis on the evolution of archaeological methods
- 4.2 Data analysis as a cognitive process
- 4.3 Teaching data analysis in archaeology
- 4.4 The post-modern reaction in archaeology
- 5. Data analysis and ‘classical’ archaeology, Paola Moscati
- 5.1 The quantitative approach and the data encoding strategy
- 5.2 Quantitative archaeology, data analysis, and ancient pottery
- 5.3 ‘Automatization of Etruscan corpora’: a pioneering application of data analysis in the archaeology of pre-Roman Italy
- 6. Textual analysis in archaeology: proposals, methods, and applications, Alessandro Di Ludovico
- 6.1 Textual analysis: assumptions and needs of archaeological research
- 6.2 Textual analysis and archaeology: premises, beginnings and developments
- 6.3 Textual analysis and the French school of data analysis: the investigation of visual languages
- 6.4 Textual analysis for methodological and meta-archaeological research
- 6.5 Closing remarks
- 7. The legacy: the Data Science movement, Lorenzo Cardarelli
- 7.1 The leading actors: Data Science, Machine Learning and Deep Learning
- 7.2 Not only Deep Learning: the role of manifold learning and dimensionality reduction
- 7.3 A practical example: UMAP and archaeological ceramics
- 7.4 Conclusions and perspectives
- 8. References
In collaborazione con la SAMI, Società degli Archeologi Medievisti Italiani
