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2020/2021

Digital Archaeology

Code: 44063 ECTS Credits: 6
Degree Type Year Semester
4313137 Prehistory, Antiquity and the Middle Ages OT 0 1
The proposed teaching and assessment methodology that appear in the guide may be subject to changes as a result of the restrictions to face-to-face class attendance imposed by the health authorities.

Contact

Name:
Juan Antonio Barceló Álvarez
Email:
JuanAntonio.Barcelo@uab.cat

Use of Languages

Principal working language:
catalan (cat)

Other comments on languages

Language can be adapted to the special needs of students

Teachers

Ermengol Gassiot Ballbé

Prerequisites

Knowledge characteristic of a university degree (Bachelor level) in Archaeology, History, Humanities or Anthropology. It can be also acceptable a degree in any Human or Social Sciences. The course is also appropriated to students with a degree in computer science and wishing to apply digital technology in archaeological or historical fields. Some degree of familiarity with computers and basic office software. Although it is not compulsory, it  is recommended some knowledge, at a very basic level, in databases, computer assisted cartography, digital photography and statistics.

Knowledge of  English at a specialized reading level is also necessary.

Objectives and Contextualisation

The course pretends to introduce students to the use of advanced information technologies for archaeological research. Throughout the course  different techniques and information technologies for data analysis are presented. Topics such as advanced database design, data mining and automatic learning techniques (neural networks, induction), and various computer simulation approaches (agent-based models) are discussed. Emphasis is also put on advanced spatial analusis (Topography, GIS, geostatistics) and temporal series analysis of radiometric dates. Various aspects of 3D computer graphics are discussed, such as the use of 3D scanners and computer visualization and virtual reality techniques.

Competences

  • Analyse and summarise information from a critical perspective.
  • Correctly present historical research results orally or in writing.
  • Critically analyse the theoretical and methodological standpoints that have guided research in prehistory, ancient history and medieval history.
  • Define, design, plan and draw up an original unpublished research project on history or archaeology, following the established academic and scientific parameters.
  • Integrate knowledge and use it to make judgements in complex situations, with incomplete information, while keeping in mind social and ethical responsibilities.
  • Solve problems in new or little-known situations within broader (or multidisciplinary) contexts related to the field of study.
  • Use acquired knowledge as a basis for originality in the application of ideas, often in a research context.
  • Work in interdisciplinary teams.

Learning Outcomes

  1. Analyse and summarise information from a critical perspective.
  2. Carry out a research project on a particular topic, addressing the state of historical and/or archaeological theory in that area.
  3. Critically analyse the relation between historico-archaeological sources and their interpretation.
  4. Integrate knowledge and use it to make judgements in complex situations, with incomplete information, while keeping in mind social and ethical responsibilities.
  5. Present archaeological research results and conclusions clearly, orally or in writing, to both specialists and non-specialists.
  6. Solve problems in new or little-known situations within broader (or multidisciplinary) contexts related to the field of study.
  7. Use acquired knowledge as a basis for originality in the application of ideas, often in a research context.
  8. Work in interdisciplinary teams.

Content

  1. Introduction. Digital or Quantitative Archaeology? Debating the need of formalize reasoning and discourse in the human and social sciences, and the objective need of quantifying data about past social behavior.
  2. Data Acquisition in Archaeology. Image Analysis: From computer assisted microscopy to 3D scanning. Photogrammetry. Shape analysis and Geometry
  3. Image Analysis Practical Session. Quantitative Archaeology Lab and Digital Humanities Lab at the UAB. 3D scanning presentation from Faro Gmbh, CreaForm and Leica.
  4. Spatial Analysis. Data Acquisition. Topography and Teledetection
  5. Optional field trip for practicing with topographic equipment at an archaeological site
  6. Data Processing (i): Databases in Archaeology
  7. Data Processing (ii) Advanced uses of databases in archaeology
  8. Data Processing (III): Geographical Information Systems
  9. Data Processing (iv): Radiocarbon data and Temporal databases
  10. Practical session using Radiocarbon calibration software: OxCal, Chronomodel and R.
  11. Data Analysis (i): statistical hypothesis testing
  12. Data Analysis (ii): Classification, Typology and Artificial Intelligence
  13. Spatial Analysis at the intra-site scale. Geostatistics
  14. Spatial Analysis at the regional level. Landscape and territory.
  15. Practical session on: Spatial Analysis at the regional level. Landscape and territory.
  16. Virtual Reality in Archaeology. Reconstructing the Past
  17. Virtual Reality in Archaeology. Artificial Societies and Simulating the Past.

Methodology

Directed activities: standard class and explanation of digital technologies and its theoretical and methodological background. Discussion seminars about specialized texts (37.5 hours)

Supervised activities: Presentationh of digital equipment. Practical sessions with technology. Tutor work and attendance for preparing the writing essay to bge presented at the end of this module. (37.5 hours)

Autonomous activity: search for documentation, creation and operation of databases, technical exercises, text reading, essay writing. (75 hours)

Activities

Title Hours ECTS Learning Outcomes
Type: Directed      
Explanation of digital technologies 30 1.2 7
discusssion seminars 7.5 0.3 3, 4, 6
Type: Supervised      
Practical sessions 30 1.2 6, 8
Tutorial work 7.5 0.3 6, 2, 5
Type: Autonomous      
text reading 35 1.4 3, 1, 4, 7

Assessment

A written essay about any of the subjects presented and studied during the course. It can be a prospective essay about the need to apply a particular technique to a particular database at a particular case, or a bibliographic essay where the student discuss in a critical and innovative way the advantages and negative aspects of a particular kind of techniques and technologies. It is also acceptable the analysis of the student own data. (40 % of final result).

Written comments of practical sessions, indicating in a critical way, advantages and disadvantages. (35% final result)

Text commentaries about specialized readings. (25% final result).

At the time of completion/delivery of each assessment activity, the teacher will inform (Moodle, SIA) of the procedure and date of revision of the grades.

The student will be classified as Non-evaluable when he has not delivered the main written essay or more than 50 % of practical work and specialized texts comments.

In the event of a student committing any irregularity that may lead to a significant variation in the grade awarded to an assessment activity, the student will be given a zero for this activity, regardless of any disciplinary process that may take place. In the event of several irregularities in assessment activities of the same subject, the student will be given a zero as the final grade for this subject.

Assessment Activities

Title Weighting Hours ECTS Learning Outcomes
Practical Exercises 35 5 0.2 6, 8
Written Essay 40 30 1.2 1, 4, 6, 2, 7, 5
text comentaries 25 5 0.2 3, 1

Bibliography

Main literature

Banning, E.B. 2000. The Archaeologist’s Laboratory: The Analysis of Archaeological Data. Springer, New York (Interdisciplinary Contributions to Archaeology).

Barceló, J.A. 2009. Computational Intelligence in Archaeology. The IGI Group, Hershey (NY).

Barceló, J.A., Del Castillo Bernal, F., I., 2015, Simulating Prehistoric and Ancient Worlds. New York/Berlin, Springer Verlag

Barceló, J.A., Bogdanovic, I., 2014, Mathematics and Archaeology. CRC Press.

Barceló. J.A., Morell, B., 2020, Métodos Cronométricos en Arqueología, Historia y Paleontología. Madrid. Editorial Dextra

Bevan, A. and M. Lake (eds.). 2013. Computational Approaches to Archaeological Spaces. Left Coast Press, Walnut Creek.

Buck, C.E. and A. Millard (eds.). 2004. Tools for constructing chronologies: crossing disciplinary boundaries (Vol. 177). Springer, Berlin.

Cioffi -Rivilla, C. 2014. Introduction to Computational Social Science: Principles and Applications. Springer, Berlin-New York (Texts in Computer Science).

Conolly, J. and M. Lake. 2006. Geographical Information Systems in Archaeology. Cambridge University Press.

Cotterell, B. and J. Kamminga. 1992. Mechanics of Pre-Industrial Technology. An introduction to the mechanics of ancient and traditional material culture. Cambridge University Press.

Jiménez-Badillo, D., 2017, Arqueología Computacional. Mexico: Instituto Nacional de Antropología e Historia

Remondino, F. and S. Campana (eds.). 3D Recording and Modelling in Archaeology and Cultural Heritage—Theory and Best Practices. Archaeopress BAR Publication Series 2598, Oxford.

 

 

Specialized references

 

Aitchison, J. 1986. The Statistical Analysis of Compositional Data. Chapman and Hall, London.

Armit, I., G.T. Swindles and K. Becker. 2013. From dates to demography in later prehistoric Ireland? Experimental approaches to the meta-analysis of large 14C data-sets. Journal of Archaeological Science 40: 433–438.

Atkins, T. 2009. The Science and Engineering of Cutting: The Mechanics and Processes of Separating, Scratching and Puncturing Biomaterials, Metals and Non-Metals. Butterworth, Oxford.

Bailey, G.N. 2005. Concepts of time. pp. 268–273. In: C. Renfrew and P. Bahn (eds.). Archaeology: The Key Concepts. Thames and Hudson, London.

Bailey, G.N. 2007. Time perspectives, palimpsests and the archaeology of time. Journal of Anthropological Archaeology 26: 198–223.

Banning, E.B. 2000. The Archaeologist’s Laboratory: The Analysis of Archaeological Data. Springer, New York (Interdisciplinary Contributions to Archaeology).

Barceló, J.A. 2008. La incertesa de les cronologies absolutes en Arqueologia. Probabilitat i Estadística. Cypsela 17: 23–34.

Barceló, J.A. 2009. Computational Intelligence in Archaeology. The IGI Group, Hershey (NY).

Barceló, J.A. 2010a. Visual analysis in archaeology. An artifi cial intelligence Approach. In: A.M.T. Elewa (ed.). Morphometrics for Nonmorphometricians. Springer Verlag, Berlin. Lecture Notes in Earth Sciences 124: 51–101.

Frischer, J. Webb and D. Koller (eds.). Making History Interactive. ArcheoPress (BAR Int. Series, S2079), Oxford.

Barceló, J.A. and V. Moitinho de Almeida. 2012. Functional Analysis from Visual and Non-visual Data. An Artificial Intelligence Approach. Mediterranean Archaeology & Archaeometry 12(2): 273–321.

Baxter, M.J. 1994. Exploratory Multivariate Analysis in Archaeology. Edinburgh University Press.

Baxter, M.J. 2003. Statistics in Archaeology. Wiley, London.

Beekman, C.S. and W.W. Baden (eds.). 2005. Nonlinear models for archaeology and anthropology: continuing the revolution. Ashgate Publishing, Hampshire.

Bevan, A. and M. Lake (eds.). 2013. Computational Approaches to Archaeological Spaces. Left Coast Press, Walnut Creek.

Blankholm, H. 1991. Intrasite spatial analysis in theory and practice.Aarhus University Press. Aarhus.

Buck, C.E., W.C. Cavanaghwg and R. Litton. 1996. Bayesian Approach to Interpreting Archaeological Data. Wiley, Chichester (UK).

Bunge, M. 1959. Causality. The Place of Causal Principle in Modern Science. Harvard University Press, Cambridge.

Bunge, M. 2006. Chasing Reality: Strife over Realism. University of Toronto Press.

Buxó, R. and R. Piqué. 2009. Arqueobotánica: Los usos de las plantas en la Peninsula Ibérica. Editorial Ariel, Barcelona.

Cartwright, N. 2004. Causation: One word, many things. Philosophy of Science 71(5): 805–820.

Chamberlain, A. 2009. Archaeological Demography. Human Biology 81(2–3): 275–86.

Cioffi -Rivilla, C. 2014. Introduction to Computational Social Science: Principles and Applications. Springer, Berlin-New York (Texts in Computer Science).

Conolly, J. and M. Lake. 2006. Geographical Information Systems in Archaeology. Cambridge University Press.

Costa, L.F. and R.M. Cesar. 2001. Shape Analysis and Classifi cation: Theory and Practice. CRC Press, Boca Raton (FL).

Costopoulos, A. and M.W. Lake (eds.). 2010. Simulating Change: Archaeology into the Twenty-First Century. University of Utah Press, Salt Lake City.

Cotterell, B. and J. Kamminga. 1992. Mechanics of Pre-Industrial Technology. An introduction to the mechanics of ancient and traditional material culture. Cambridge University Press.

Desachy, B. 2008. De la formalisation du traitement des données stratigraphiques en archéologie de terrain. PhD Dissertation. Université Panthéon-Sorbonne-Paris I.

Drennan, R. 2010. Statistics for Archaeologists. 2nd Edition: A Common Sense Approach, Springer, Berlin-New York.

Elewa, E.M.T. (ed.). 2010. Morphometrics for Non-Morphometricians. Lecture Notes in Earth Sciences 124. Springer, Berlin.

Epstein, J.M. 2006. Generative social science: Studies in agent-based computational modeling. Princeton University Press.

Hastie, T., R. Tibshirani and J. Fiedman. 2011. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Second Edition. Springer, Berlin.

Kamermans, H., M. van Leusen and Ph Verhagen (eds.). 2009. Archaeological Prediction and Risk Management. Alternatives to current practice. Leiden University Press.

Kohler, T.A. and S.E. van der Leeuw. 2007. The Model-Based Archaeology of Socionatural Systems. SAR Press, Santa Fe (NM).

Kohler, T.A., D. Cockburn, P.L. Hooper, R.K. Bocinsky and Z. Kobti. 2012. The coevolution of group size and leadership: an agent-based public goods model for prehispanic Pueblo societies. Advances in Complex Systems 15(1&2). DOI 1150007–1–1150007–29.

Lindsey, J.K. 1995. Modelling Frequency and Count Data. Clarendon Press, Oxford.

Lyman, R.L. 2008. Quantitative Paleozoology. Cambridge University Press.

Moitinho de Almeida, V. 2013. Towards Functional Analysis of Archaeological Objects through Reverse Engineering Processes. PhD. Dissertation. Universitat Autònoma de Barcelona.

Murray, T. (ed.). 2004. Time and archaeology. Routledge, London.

Pawlowsky-Glahn, V. and A. Buccianti (eds.). 2011. Compositional data analysis: Theory and applications. John Wiley & Sons, London.

Railsback, S. and V. Grimm. 2011. Agent-Based and Individual-Based Modeling: A Practical Introduction. Princeton University Press.

Rivadulla, A. 1993. Probabilidad e inferencia estadística. Anthropos, Barcelona.

Small, C.G. 1996. The Statistical Theory of Shape. Springer, Berlin.

Squazzoni, F. 2012. Agent-Based Computational Sociology. Wiley, London.

Thornton, C. 2000. Truth from Trash. How Learning Makes Sense. The MITPress. Cambridge (MA).

VanPool, T.L. and R.D. Leonard. 2010. Quantitative Analysis in Archaeology. Wiley-Blackwell, London/Oxford.

Williams, A.N. 2012. The use of summed radiocarbon probability distributions in archaeology: a review of methods. Journal of Archaeological Science 39(3): 578–589.

Wurzer, G., K. Kowarik and H. Reschreiter (eds.). 2013. Agent-based Modeling and Simulation in Archaeology. Berlin, Springer.