Computational archaeology
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2008-07-10T16:36:12Z
Hoopes
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'''Computational archaeology''' describes computer-based analytical methods for the study of long-term human behaviour and behavioural evolution. As with other sub-disciplines that have prefixed 'computational' to their name (e.g. [[computational biology]], [[computational physics]] and [[computational sociology]]), the term is reserved for (generally mathematical) methods that could not realistically be performed without the aid of a computer.
Computational archaeology may include the use of [[Geographic information system|geographical information system]]s (GIS), especially when applied to [[spatial analyses]] such as [[viewshed]] analysis and [[least-cost path]] analysis as these approaches are sufficiently computationally complex that they are extremely difficult if not impossible to implement without the processing power of a computer. Likewise, some forms of [[statistical]] and [[mathematical]] [[mathematical model|modelling]], and the [[computer simulation]] of [[human behaviour]] and [[behavioural evolution]] using software tools such as [[Swarm (simulation)|Swarm]] or [[Repast (Modelling toolkit)|Repast]] would also be impossible to calculate without computational aid. The application of a variety of other forms of complex and bespoke software to solve archaeological problems, such as human perception and movement within built environments using software such as [[University College London|University College London's]] [[Space Syntax]] program, also falls under the term 'computational archaeology'.
'''Computational archaeology''' is also known as '''archaeological informatics ''' (Burenhult 2002, Huggett and Ross 2004) or '''archaeoinformatics''' (sometimes abbreviated as "AI", but not to be confused with [[artificial intelligence]].
== Origins and objectives ==
In recent years, it has become clear that [[archaeologists]] will only be able to harvest the full potential of [[quantitative]] methods and computer technology if they become aware of the specific pitfalls and potentials inherent in the archaeological data and research process. AI science is an emerging discipline that attempts to uncover, quantitatively represent and explore specific properties and patterns of archaeological information. Fundamental research on data and methods for a self-sufficient archaeological approach to [[information processing]] produces quantitative methods and computer [[software]] specifically geared towards archaeological problem solving and understanding.
AI science is capable of complementing and enhancing almost any area of [[scientific]] archaeological research. It incorporates a large part of the methods and theories developed in [[Processual archaeology|quantitative archaeology]] since the 1960s but goes beyond former attempts at quantifying archaeology by exploring ways to represent general archaeological information and problem structures as computer [[algorithms]] and [[data structures]]. This opens archaeological analysis to a wide range of computer-based information processing methods fit to solve problems of great complexity. It also promotes a formalized understanding of the discipline's research objects and creates links between archaeology and other quantitatice disciplines, both in methods and software technology. Its agenda can be split up in two major research themes that complement each other:
#Fundamental research (theoretical AI science) on the structure, properties and possibilities of archaeological data, [[inference]] and knowledge building. This includes modeling and managing [[Fuzzy measure theory|fuzziness]] and [[uncertainty]] in archaeological data, scale effects, optimal [[Sampling (statistics)|sampling]] strategies and spatio-temporal effects.
#Development of computer algorithms and software (applied AI science) that make this theoretical knowledge available to the user.
There is already a large body of literature on the use of quantitative methods and computer-based analysis in archaeology. The development of methods and applications is best reflected in the annual publications of the CAA conference (see weblinks at bottom). At least two journals, the Italian ''Archeologia e Calcolator'' and the British ''Archaeological Computing Newsletter'', are dedicated to archaeological computing methods. AI Science contributes to many fundamental research topics, including but not limited to:
* advanced [[statistics]] in archaeology, spatial and temporal archaeological data analysis
* [[bayesian]] analysis and advanced [[probability]] models, [[Fuzzy measure theory|fuzziness]] and [[uncertainty]] in archaeological data
* scale-related phenomena and scale transgressions
* [[GIS in archaeology|intrasite analysis]] (representations of [[Stratification|stratigraphy,]] 3D analysis, [[Artifact (archaeology)|artefact]] distributions)
* landscape analysis (territorial modeling, [[visibility analysis]])
* optimal [[archaeological field survey|survey]] and sampling strategies
* [[Process (science)|process-based]] modeling and [[simulation]] models
* archaeological [[predictive modeling]] and [[heritage management]] applications
* supervised and unsupervised [[Scientific classification|classification]] and typology, [[artificial intelligence]] applications
* digital [[excavations]] and [[virtual reality]]
* archaeologcial software development, electronic data sharing and publishing
AI science advocates a formalized approach to archaeological inference and knowledge building. It is [[interdisciplinary]] in nature, borrowing, adapting and enhancing method and theory from numerous other disciplines such as [[computer science]] (e.g. algorithm and software design, [[database]] design and theory), [[geoinformation]] science ([[Geostatistics|spatial statistics]] and modeling, [[geographic information systems]]), [[artificial intelligence]] research (supervised classification, [[fuzzy logic]]), [[ecology]] (point pattern analysis), [[applied mathematics]] ([[graph theory]], [[probability theory]]) and [[statistics]].
== Training and research ==
Scientific progress in archaeology, as in any other discipline, requires building abstract, generalized and transferable knowledge about the processes that underlie past human actions and their manifestations. [[Quantification]] provides the ultimate known way of abstracting and extending our scientific abilities past the limits of [[intuitive]] cognition. Quantitative approaches to archaeological information handling and inference constitute a critical body of scientific methods in archaeological research. They provide the tools, [[algebra]], [[statistics]] and computer [[algorithms]], to process information too voluminous or complex for purely [[cognitive]], informal [[inference]]. They also build a bridge between archaeology and numerous quantitative sciences such as [[geophysics]], [[geoinformation]] sciences and applied [[statistics]]. And they allow archaeological scientists to design and carry out research in a formal, transparent and comprehensible way.
Being an emerging field of research, AI science is currently a rather dispersed discipline in need of stronger, well-funded and institutionalized embedding, especially in academic teaching. Despite its evident progress and usefulness, today's quantitative archaeology is often inadequately represented in archaeological training and education. Part of this problem may be misconceptions about the seeming conflict between mathematics and [[humanistic]] archaeology.
Nevertheless, digital [[excavation]] technology, modern [[heritage management]] and complex research issues require skilled students and researchers to develop new, efficient and reliable means of processing an ever-growing mass of untackled archaeological data and research problems. Thus, providing students of archaeology with a solid background in quantitative sciences such as mathematics, statistics and computer sciences seems today more important than ever.
Currently, universities based in the UK provide the largest share of study programmes for prospective quantitative archaeologists, with many institutes in Italy developing a strong profile quickly (see links at the bottom). In Germany, the country's first lecturer's position in AI science ("Archäoinformatik") was established in 2005 at the University of Kiel.
The most important platform for students and researchers in quantitative archaeology and AI science is the international conference on Computer Applications and Quantitative Methods in Archaeology (CAA) which has been in existence for more than 30 years now and is held in a different city of Europe each year. Vienna's city archaeology unit also hosts an annual event that is quickly growing in international importance (see links at bottom).
== Employment opportunities ==
As a general rule, the archaeological job market has insufficient capacities to offer employment for all of the subject's graduates. Training in AI science will provide students with knowledge and skills related to a number of key qualifications and technologies that are sought for in many sectors of today's job market. In archaeology itself, prospective fields of work include heritage management, archaeological IT consulting and software development, digital excavation management, digital archives and museums, digital publishing (e.g. ''[[Internet Archaeology]]''), and teaching and training quantitative archaeologists.
== See also ==
*Burenhult 2002: Burenhult, G. (ed.): ''Archaeological Informatics: Pushing The Envelope''. CAA2001. Computer Applications and Quantitative Methods in Archaeology. BAR International Series 1016, Archaeopress, Oxford.
*Huggett and Ross 2004: J. Hugget, S. Ross (eds.): ''Archaeological Informatics. Beyond Technology''. ''[[Internet Archaeology]]'' 15. http://intarch.ac.uk/journal/issue15/
*Schlapke 2000: Schlapke, M. ''Die "Archäoinformatik" am Thüringischen Landesamt für Archäologische Denkmalpflege'', Ausgrabungen und Funde im Freistaat Thüringen, 5, 2000, S. 1-5.
*Zemanek 2004: Zemanek, H.: ''Archaeological Information - An information scientist looks on archaeology.'' In: Ausserer, K.F., Börner, w., Goriany, M. & Karlhuber-Vöckl, L. (eds) 2004. Enter the Past. The E-way into the four Dimensions of Cultural Heritage. CAA 2003, Computer Applications and Quantitative Methods in Archaeology. BAR International Series 1227, Archaeopress, Oxford, 16-26.
*[http://www.gla.ac.uk/Acad/Archaeology/acn/index.html ''Archaeological Computing Newsletter'' journal homepage]
*[http://soi.cnr.it/archcalc/ Archeologia e Calcolatori journal homepage]
*[[Computational archaeology]]
== External links ==
===Studying AI science===
*[http://www.ucl.ac.uk/archaeology/masters/summary/MSc-gis.htm University College London: M.Sc. GIS and Spatial Analysis in Archaeology]
*[http://www.york.ac.uk/depts/arch/gsp/publicity/archinfodet.htm University of York: Archaeological Information Systems]
*[http://www.iaa.bham.ac.uk/arch/pgeomatics.htm University of Birmingham: Landscape Archaeology and Geomatics]
*[http://www.humanities.soton.ac.uk/courses.asp?type=1&sbj=33 University of Southampton: MSc in Archaeological Computing (Spatial Technologies) and MSc in Archaeological Computing (Virtual Pasts)]
*[http://www.archeogr.unisi.it/ Archaeoinformatics at Siena University (Italian page)]
*[http://www.uni-kiel.de/ufg/ufg_BerAI.htm Archaeoinformation science at CAU Kiel (German page)]
*[http://www.aegean.gr/culturaltec/msc University of the Aegean M.Sc. in Cultural Informatics]
===Research groups and institutions ===
*[http://www.ucl.ac.uk/archaeology/research/research-groups/matcult.htm University College London: Material Culture and Data Science Research Group]
*[http://www.arch.soton.ac.uk/default.asp?Division=3&SubDivision=10&Page=0 University of Southampton: Archaeological Computing Research Group]
*[http://www.iaa.bham.ac.uk/Computing/HP_VISTA/HPindex.htm University of Birmingham: HP Visual and Spatial Technology Centre Archaeological Computing Division]
*[http://www.ics.forth.gr/isl/cci.html Foundation for Research and Technology Hellas (FORTH), Center for Cultural Informatics]
*[http://www.alexandriaarchive.org Alexandria Archive Institute (AAI)]
*[http://www.iosa.it Internet and Open Source for Archaeology] is a portal dedicated to the collection and creation of resources to help archaeologists eveluate open source alternatives to proprietary software.
===Important conferences===
*[http://www.caaconference.org Computer Applications and quantitative methods in Archaeology (CAA)]
*[http://www.stadtarchaeologie.at/ "Workshop Computer und Archäologie" at Vienna]
===Archaeological IT service providers===
*[http://ads.ahds.ac.uk Archaeology Data Service]
*[http://www.oxarchdigital.com Oxford ArchDigital]
*[http://www.intrasis.com/engelska/index_eng.htm Intrasis GIS]
*[http://www.arctron.de ArcTron (in German)]
*[http://www.opencontext.org Open Context: experimental system for archaeological data-sharing]
[[Category:Archaeological sub-disciplines]]
[[de:Archäoinformatik]]