TY - JOUR
T1 - Data Integration in the Service of Synthetic Research
AU - Spielmann, Katherine A.
AU - Brin, Adam
AU - Candan, Kasim
AU - Clark, Tiffany C.
AU - Peeples, Matthew
N1 - Funding Information: This material is based upon work supported by the National Science Foundation under grant numbers 0433959, 0624341, 1016921, and 1153115 awarded to Arizona State University and grant number 1353727 awarded to Indiana University of Pennsylvania. It is also based on work supported by a joint award, PX-50022-09, from the National Endowment for the Humanities and the Joint Information Systems Committee (UK). Permits were not required for this work. Publisher Copyright: © Copyright 2017 Society for American Archaeology.
PY - 2018/2/1
Y1 - 2018/2/1
N2 - 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.
AB - 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.
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U2 - 10.1017/aap.2017.33
DO - 10.1017/aap.2017.33
M3 - Article
SN - 2326-3768
VL - 6
SP - 30
EP - 41
JO - Advances in Archaeological Practice
JF - Advances in Archaeological Practice
IS - 1
ER -