Monitoring of human-data interactions towards understanding the interpretation process of geoscientific data

Yathunanthan Sivarajah

    Research output: ThesisDoctoral Thesis

    234 Downloads (Pure)


    [Truncated] Qualitative data interpretation forms the basis of important decisions with significant social, financial, and environmental implications across diverse sectors of our society including the medical, legal, astronomy, and resource sectors. These interpretations typically involve the recognition of anomalies or specific features of interest within data. In this process, interpreters' intuition and biases play an important role, resulting in outcomes that are highly subjective and uncertain. This thesis presents a study that aims to understand and address uncertainties in geoscientific data interpretation, specifically focusing on geological target spotting within magnetic geophysical data.

    Previous studies on geological interpretation uncertainties have mainly focused on analysing the interpretation outcomes and identifying factors that influenced these outcomes. This thesis on the other hand aims to understand and address uncertainties in human-data interactions, that is, the process by which the interpretation outcomes are reached. This is achieved by monitoring and quantifying physiological and neurological responses of interpreters during target spotting exercises through an eye tracker system (ETS) and electroencephalography (EEG) techniques. These technologies are widely used in various elds, such as humancomputer interaction (HCI), brain-computer interface (BCI), clinical studies, and web marketing, but their use in geoscience is in its infancy. Various experiments were carried out to capture ETS and EEG data during target spotting exercises involving the identification of prescribed geological 'targets', specifically porphyrystyle intrusive systems within magnetic data. Interpreters with varying levels of expertise and experience participated in the experiments, and their data observation patterns were profiled using an ETS and their brain responses were monitored using EEG techniques.

    Original languageEnglish
    QualificationDoctor of Philosophy
    Publication statusUnpublished - 2015


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