This thesis sets out to explore, describe, quantify, and visualise uncertainty in a
cultural informatics context, with a focus on archaeological reconstructions. For quite
some time, archaeologists and heritage experts have been criticising the often toorealistic
appearance of three-dimensional reconstructions. They have been highlighting
one of the unique features of archaeology: the information we have on our heritage
will always be incomplete. This incompleteness should be reflected in digitised
reconstructions of the past.
This criticism is the driving force behind this thesis. The research examines archaeological
theory and inferential process and provides insight into computer visualisation.
It describes how these two areas, of archaeology and computer graphics,
have formed a useful, but often tumultuous, relationship through the years.
By examining the uncertainty background of disciplines such as GIS, medicine,
and law, the thesis postulates that archaeological visualisation, in order to mature,
must move towards archaeological knowledge visualisation. Three sequential areas
are proposed through this thesis for the initial exploration of archaeological uncertainty:
identification, quantification and modelling. The main contributions of the
thesis lie in those three areas.
Firstly, through the innovative design, distribution, and analysis of a questionnaire,
the thesis identifies the importance of uncertainty in archaeological interpretation
and discovers potential preferences among different evidence types.
Secondly, the thesis uniquely analyses and evaluates, in relation to archaeological
uncertainty, three different belief quantification models. The varying ways that these
mathematical models work, are also evaluated through simulated experiments. Comparison
of results indicates significant convergence between the models.
Thirdly, a novel approach to archaeological uncertainty and evidence conflict visualisation
is presented, influenced by information visualisation schemes. Lastly, suggestions
for future semantic extensions to this research are presented through the
design and development of new plugins to a search engine
