Exploring the ontological links between Human Ecodynamics and field archaeology through the integration of archaeological reports into DataARC’s landscape ontology

Barruezo Vaquero, Pablo (2021) Exploring the ontological links between Human Ecodynamics and field archaeology through the integration of archaeological reports into DataARC’s landscape ontology. MPhil(R) thesis, University of Glasgow.

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Abstract

This research focuses on the processes of knowledge creation within a framework of Big Data. Concretely, my project focus on grey archaeological data and their underlying ontologies, and how to interlink such type of data with other data in a Computational Ontology. This research was carried out within the dataARC Project, which tries to represent Human Ecodynamics for the North Atlantic context using data generated over 25 years by NABO (North Atlantic Biocultural Organisation). The project has been developing a cyberinfrastructure whose main tool is a computational ontology. We try to include in this ontology diverse conceptual models (from archaeological and historical, to ecological or geological data) from different grey sources.
In my case, the main issue is the creation of knowledge using multiple datasets that comes from grey literature sources. Said another way, my thesis explores how to create a dataset by extracting data and their underlying ontologies from grey-archaeological reports with the final aim of interlinking them with other datasets. For so doing, these reports are transformed into a dataset, which in turn is mapped to the interdisciplinary ontology. This thesis, therefore, presents a prototype dataset and the process of conceptual mappings. In so doing, I explore how to decompose archaeological reports that are in Open Access to make their data FAIRer and (inter)linked.
Human Ecodynamics are of special importance for NABO and, consequently, for the DataARC project. Our computational ontology, therefore, had to be developed for representing Human Ecodynamics in a rigorous and efficient way, yet capable of engaging a broad audience. This, along the use multiple, interconnected, datasets in a concrete relational manner, forces us to develop an ontology capable of representing very abstract themes while representing small details that affect these ecodynamics. This led me to try to develop a theoretical framework which could allow me to contextualise DataARC's ontology and my own method. The theoretical framework blends Latourian Actor-Network-Theory and some basic ontological principles (in the theoretical-philosophical sense) drawn from Human Ecodynamics. This might arguably open new avenues for developing powerful ontologies capable of representing complex knowledge. Problems such as overlappings or identifying the right number of hierarchical levels will be discussed, as well as some procedures that might help in rethinking computational ontologies.
Digital Archaeology's ethical challenges is a final interesting point touched by this thesis. Here it is argued that Digital Archaeology, specifically if we convey inter/transdisciplinary knowledge such as Human Ecodynamics or Local and Traditional Knowledge, carries quite an important ethical responsibility. This leads me to offer new possible pathways by openly engaging theoretical critical schools of thought such as Social Ecology -which, in turn, might shed light on problems related to Climate Change and similar current issues.

Item Type: Thesis (MPhil(R))
Qualification Level: Masters
Keywords: Digital archaeology, landscape archaeology, theory, computational ontologies, DataARC, North Atlantic, Vikings, Iceland.
Subjects: B Philosophy. Psychology. Religion > B Philosophy (General)
C Auxiliary Sciences of History > CC Archaeology
D History General and Old World > DL Northern Europe. Scandinavia
G Geography. Anthropology. Recreation > GF Human ecology. Anthropogeography
Colleges/Schools: College of Arts > School of Humanities > Archaeology
Supervisor's Name: Opitz, Dr. Rachel
Date of Award: 2021
Depositing User: Pablo Barruezo Vaquero
Unique ID: glathesis:2021-82111
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 08 Apr 2021 08:43
Last Modified: 21 Apr 2021 09:00
URI: http://theses.gla.ac.uk/id/eprint/82111

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