Representing Imprecise and Uncertain Knowledge in Digital Humanities: A Theoretical Framework and ConML Implementation with a Real Case Study

TítuloRepresenting Imprecise and Uncertain Knowledge in Digital Humanities: A Theoretical Framework and ConML Implementation with a Real Case Study
AutoresPatricia Martin-Rodilla, Cesar Gonzalez-Perez
TipoComunicación para congreso
Fonte Sixth Edition IEEE International Conference of Technological Ecosystems for Enhancing Multiculturality, Salamanca (España), 2018.
AbstractWhen working in digital humanities, we are often required to manage knowledge that is highly vague, either because it refers to things in the world lacking clear-cut boundaries, or because it is incomplete or approximate. The usual approaches to knowledge representation and information modelling, often taken from engineering or natural science disciplines, lack the ability to express these concerns. Also, software systems for digital humanities should acknowledge that imprecise and uncertain information exists, but current software development technologies fall short of providing satisfactory approaches to implementing such “soft” issues. In this paper we propose a theoretical framework to define, characterise and express information imprecision and uncertainty in digital humanities, and describe a semi-formal implementation on top of the ConML conceptual modelling language. The proposal has been applied to a real project in digital humanities. Using this approach, imprecise and uncertain knowledge can be represented, so that models and simulations in digital humanities provide a better account of the reality being modelled. Also, software systems (including databases, search engines or analytical algorithms) can exploit these aspects to yield more faithful results.
Palabras chaveImprecision, Uncertainty, Vagueness, Knowledge representation, Conceptual modelling, Digital Humanities, ConML.

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