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Data Integration in the Service of Synthetic Research

Published online by Cambridge University Press:  28 December 2017

Keith W. Kintigh*
Affiliation:
School of Human Evolution and Social Change, Arizona State University, Tempe, AZ 85287-2402, USA
Katherine A. Spielmann
Affiliation:
School of Human Evolution and Social Change, Arizona State University, Tempe, AZ 85287-2402, USA (kate.spielmann@asu.edu)
Adam Brin
Affiliation:
Center for Digital Antiquity, Arizona State University, Tempe, AZ 85287-2402, USA (abrin@digitalantiquity.org)
K. Selçuk Candan
Affiliation:
School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, AZ 85287–8809, USA (candan@asu.edu)
Tiffany C. Clark
Affiliation:
Applied EarthWorks, Inc., Pasadena, CA 91107–3414, USA (tclark@appliedearthworks.com)
Matthew Peeples
Affiliation:
School of Human Evolution and Social Change, Arizona State University, Tempe, AZ 85287-2402, USA (matthew.peeples@asu.edu)
*
(kintigh@asu.edu, corresponding author)

Abstract

Addressing archaeology's most compelling substantive challenges requires synthetic research that exploits the large and rapidly expanding corpus of systematically collected archaeological data. That, in turn, requires a means of combining datasets that employ different systematics in their recording while at the same time preserving the semantics of the data. To that end, we have developed a general procedure that we call query-driven, on-the-fly data integration that is deployed within the Digital Archaeological Record digital repository. The integration procedure employs ontologies that are mapped to the original datasets. Integration of the ontology-based dataset representations is done at the time the query is executed, based on the specific content of the query. In this way, the original data are preserved, and data are aggregated only to the extent necessary to obtain semantic comparability. Our presentation draws examples from the largest application to date: an effort by a research community of Southwest US faunal analysts. Using 24 ontologies developed to cover a broad range of observed faunal variables, we integrate faunal data from 33 sites across the late prehistoric northern Southwest, including about 300,000 individually recorded faunal specimens.

Abordar los retos sustantivos más convincentes de la arqueología requiere una investigación sintética que explote el corpus grande y rápidamente en expansión de datos arqueológicos recopilados sistemáticamente. Esto, a su vez, requiere un medio de combinar conjuntos de datos que empleen sistemática diferente en su grabación mientras que al mismo tiempo preserva la semántica de los datos. Para ello, hemos desarrollado un procedimiento general que denominamos integración de datos en tiempo real basada en consultas, que se despliega dentro del repositorio digital el Digital Archaeological Record. El procedimiento de integración emplea ontologías que se asignan a los conjuntos de datos originales. La integración de las representaciones de conjuntos de datos basados en ontología se realiza en el momento en que se ejecuta la consulta, en función del contenido específico de la consulta. De esta manera, los datos originales se conservan y los datos se agregan sólo en la medida necesaria para obtener comparabilidad semántica. Nuestra presentación dibuja ejemplos de la aplicación más grande hasta la fecha: un esfuerzo de una comunidad de investigadores de analistas faunísticos del suroeste de Estados Unidos. Utilizando 24 ontologías desarrolladas para cubrir una amplia gama de variables faunísticas observadas, integramos datos faunísticos de 33 conjuntos de datos que investigan el suroeste septentrional prehistórico tardío, incluyendo más de 300.000 muestras de fauna registradas individualmente.

Type
Articles
Copyright
Copyright 2017 © Society for American Archaeology 

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