Problem
This dissertation examines the evolving role of digital technologies in archaeological research, focusing on the management and interpretation of extensive digital datasets generated by modern excavations. Drawing on six years of comprehensive fieldwork at San Miceli, Sicily, this study critically evaluates and updates the established four-field methodology proposed by Levy et al. (2012), encompassing acquisition, analysis, dissemination, and curation. While traditional archaeological documentation methods rely heavily on analog techniques, these approaches increasingly fall short due to the rapid expansion and complexity of digital data.
Method
To address this gap, the dissertation refines and expands the current methodological framework by incorporating contemporary innovations, including iterative workflows, artificial intelligence, and collaborative digital platforms. A detailed examination of practical applications at San Miceli demonstrates that the enhanced model substantially improves the efficiency, accuracy, and accessibility of data, while also supporting effective long-term preservation. Furthermore, the inclusion of iterative and collaborative practices within the refined framework promotes greater adaptability and responsiveness to emerging discoveries and methodological advancements.
Results and Conclusions
Ultimately, this research contributes an updated and scalable methodological model designed to meet the practical demands and theoretical challenges posed by digital archaeological data. By integrating cutting-edge digital tools and practices into traditional archaeological workflows, the dissertation establishes a robust foundation for managing big data in archaeology, ensuring meaningful preservation and interpretation for future research.
","abstract_html":"<p>Problem</p> <p>This dissertation examines the evolving role of digital technologies in archaeological research, focusing on the management and interpretation of extensive digital datasets generated by modern excavations. Drawing on six years of comprehensive fieldwork at San Miceli, Sicily, this study critically evaluates and updates the established four-field methodology proposed by Levy et al. (2012), encompassing acquisition, analysis, dissemination, and curation. While traditional archaeological documentation methods rely heavily on analog techniques, these approaches increasingly fall short due to the rapid expansion and complexity of digital data.</p> <p>Method</p> <p>To address this gap, the dissertation refines and expands the current methodological framework by incorporating contemporary innovations, including iterative workflows, artificial intelligence, and collaborative digital platforms. A detailed examination of practical applications at San Miceli demonstrates that the enhanced model substantially improves the efficiency, accuracy, and accessibility of data, while also supporting effective long-term preservation. Furthermore, the inclusion of iterative and collaborative practices within the refined framework promotes greater adaptability and responsiveness to emerging discoveries and methodological advancements.</p> <p>Results and Conclusions</p> <p>Ultimately, this research contributes an updated and scalable methodological model designed to meet the practical demands and theoretical challenges posed by digital archaeological data. By integrating cutting-edge digital tools and practices into traditional archaeological workflows, the dissertation establishes a robust foundation for managing big data in archaeology, ensuring meaningful preservation and interpretation for future research.</p>","abstract_has_math":false,"creators":["Wilson, Jared"],"institution":null,"degree_name":"Doctor of Philosophy","degree_level":"Dissertation","degree_discipline":"Biblical and/or Ancient Near Eastern Archaeology, PhD","degree_department":null,"school":null,"contributors":["Randall W. Younker","Paul Z. Gregor","Paul J. Ray"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-01-01T08:00:00Z","date_published":"2025-01-01T08:00:00Z","updated_at":"2026-07-24T00:54:19Z","subjects":["Archaeology; San Miceli; Sicily; Cyber; Digital Data;","Computer Engineering","Near Eastern Languages and Societies","Other Languages, Societies, and Cultures","Religion"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.andrews.edu/dissertations/1852","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Randall W. Younker","Paul Z. Gregor","Paul J. Ray"]},{"key":"dc:creator","label":"Author","values":["Wilson, Jared"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2025-11-19T08:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Biblical and/or Ancient Near Eastern Archaeology, PhD"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Archaeology; San Miceli; Sicily; Cyber; Digital Data;","Computer Engineering","Near Eastern Languages and Societies","Other Languages, Societies, and Cultures","Religion"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.andrews.edu/dissertations/1852"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Problem
This dissertation examines the evolving role of digital technologies in archaeological research, focusing on the management and interpretation of extensive digital datasets generated by modern excavations. Drawing on six years of comprehensive fieldwork at San Miceli, Sicily, this study critically evaluates and updates the established four-field methodology proposed by Levy et al. (2012), encompassing acquisition, analysis, dissemination, and curation. While traditional archaeological documentation methods rely heavily on analog techniques, these approaches increasingly fall short due to the rapid expansion and complexity of digital data.
Method
To address this gap, the dissertation refines and expands the current methodological framework by incorporating contemporary innovations, including iterative workflows, artificial intelligence, and collaborative digital platforms. A detailed examination of practical applications at San Miceli demonstrates that the enhanced model substantially improves the efficiency, accuracy, and accessibility of data, while also supporting effective long-term preservation. Furthermore, the inclusion of iterative and collaborative practices within the refined framework promotes greater adaptability and responsiveness to emerging discoveries and methodological advancements.
Results and Conclusions
Ultimately, this research contributes an updated and scalable methodological model designed to meet the practical demands and theoretical challenges posed by digital archaeological data. By integrating cutting-edge digital tools and practices into traditional archaeological workflows, the dissertation establishes a robust foundation for managing big data in archaeology, ensuring meaningful preservation and interpretation for future research.
"]},{"key":"dc:title","label":"Title","values":["Navigating Big Data in Cyber Archaeology: an Updated Four-Field Approach Applied to San Miceli"]}]}],"canonical_facts":{"dc:contributor":["Randall W. Younker","Paul Z. Gregor","Paul J. Ray"],"dc:creator":["Wilson, Jared"],"dc:date.available":["2025-11-19T08:00:00Z"],"dc:description.abstract":["Problem
This dissertation examines the evolving role of digital technologies in archaeological research, focusing on the management and interpretation of extensive digital datasets generated by modern excavations. Drawing on six years of comprehensive fieldwork at San Miceli, Sicily, this study critically evaluates and updates the established four-field methodology proposed by Levy et al. (2012), encompassing acquisition, analysis, dissemination, and curation. While traditional archaeological documentation methods rely heavily on analog techniques, these approaches increasingly fall short due to the rapid expansion and complexity of digital data.
Method
To address this gap, the dissertation refines and expands the current methodological framework by incorporating contemporary innovations, including iterative workflows, artificial intelligence, and collaborative digital platforms. A detailed examination of practical applications at San Miceli demonstrates that the enhanced model substantially improves the efficiency, accuracy, and accessibility of data, while also supporting effective long-term preservation. Furthermore, the inclusion of iterative and collaborative practices within the refined framework promotes greater adaptability and responsiveness to emerging discoveries and methodological advancements.
Results and Conclusions
Ultimately, this research contributes an updated and scalable methodological model designed to meet the practical demands and theoretical challenges posed by digital archaeological data. By integrating cutting-edge digital tools and practices into traditional archaeological workflows, the dissertation establishes a robust foundation for managing big data in archaeology, ensuring meaningful preservation and interpretation for future research.
"],"dc:identifier":["https://digitalcommons.andrews.edu/dissertations/1852"],"dc:subject":["Archaeology; San Miceli; Sicily; Cyber; Digital Data;","Computer Engineering","Near Eastern Languages and Societies","Other Languages, Societies, and Cultures","Religion"],"dc:title":["Navigating Big Data in Cyber Archaeology: an Updated Four-Field Approach Applied to San Miceli"],"thesis:degree_discipline":["Biblical and/or Ancient Near Eastern Archaeology, PhD"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy"]},"updated_at":"2026-07-24T00:54:19Z"}