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Erschienen in: Quality & Quantity 4/2020

11.03.2020

Bringing archaeology into the information age: entropy, noise, channel capacity, and information potential in archaeological significance assessments

verfasst von: Kevin C. Nolan

Erschienen in: Quality & Quantity | Ausgabe 4/2020

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Abstract

Most archaeology today is conducted by private cultural resources management (CRM) firms in compliance with preservation legislation. Industry archaeologists make decisions that affect the expenditure of public and private development funds, and determine what resources, data, and information are available for the future. Decisions about what is archaeologically significant impact public value purchased by governments and firms, and impact cumulative ability to know the archaeological record. While there are many concepts of archaeological significance, many justify significance in terms of the information yield. Few define information. Discussions are confused by vague or absent definitions of information, and the conflation of data volume with information resulting in bias in the types of resources preserved. Perpetuating modern theoretical interests into the preserved data hobbles future archaeology. In the interest of representative preservation of archaeological information, we need an operational definition of “information” and which resources have information potential. To unify and organize discussions of information and representative samples, I turn to information theory. Claude E. Shannon provides a formal definition of “information”. Applying Shannon’s concepts of entropy and equivocation provides formal tools to objectively assess relative and absolute information potential, and can force CRM practitioners to more explicitly justify their recommendations for expenditure of public and private development funds and preserve a more representative sample of the archaeological record for future inquiry. Bringing archaeology into the information age is a practical solution to many problems with CRM significance evaluations, and will better justify the value CRM provides in return for public investment in archaeology.

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Fußnoten
1
There are exceptions, significance is messy and there is no one-to-one match with the NRHP criteria.
 
2
There is debate in the information, statistical mechanics, and physics literature as to whether Shannon’s entropy is thermodynamic entropy. Everyone acknowledges similarities in properties, but not everyone admits identity. Henceforth, my use of “entropy” refers to “Shannon entropy” or Shannon’s definition of “information”, unless otherwise specified.
 
3
Quantitative assessment of equivocation would require a defined symbol set for discrete observations and the occupations we are reconstructing. The symbol set of discrete observations would entail an explicit artifact classification and some type of classification of the spatial arrangement(s). Traditional units of artifact types, phases, site types, etc. are not sufficient to the task, though they can be used in an informal way in initial applications of the proposed model. Rafferty (2012) and Rafferty et al. (2011) provide an example of a way to create such an alphabet for occupations from observational units. Only after defining the number of possible classes in the channel and for the receiver can we begin to calculate conditional entropy. However, we can use the proposed model to frame the relative conditional entropies of different patterns of survey results.
 
4
An anonymous reviewer noted that there are many methods of investigation into formation processes that can account for and mitigate the increase in entropy and that my characterization of the increase in equivocation as “irretrievable” was perhaps too strong. I acknowledge the reviewer’s point. Indeed there are well tested methods and theories for assessing formation processes, in effect filtering the noise from the signal. However, any information lost is irretrievable, and there is always some that is irretrievable. The reviewer’s comment speaks to the discussion of error correction, noise reduction, and sampling decisions given a specified set of noise for a specific period (Nj). I did not mean to imply there is no way to filter noise and correct errors in the archaeological record. The ability of established methods to mitigate formation processes is factored into discussions of assessing channel capacity, and the methods referenced by the reviewer are what I had in mind in that discussion.
 
5
This would also include a version of intersymbol interference (Hartley 1928: 544). In archaeology, there is also intersource interference which is the Nj introduced by a different Xi occurring in the same place at a different time i. Being recipients, we cannot take Hartley’s design solution guidance; however, we can be aware of this as a practical limit in the approximation of HYs(Δj) to H(Δj).
 
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Metadaten
Titel
Bringing archaeology into the information age: entropy, noise, channel capacity, and information potential in archaeological significance assessments
verfasst von
Kevin C. Nolan
Publikationsdatum
11.03.2020
Verlag
Springer Netherlands
Erschienen in
Quality & Quantity / Ausgabe 4/2020
Print ISSN: 0033-5177
Elektronische ISSN: 1573-7845
DOI
https://doi.org/10.1007/s11135-020-00980-0

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