Interest in Medieval accounts: examples from England, 1272-1340

The charging of interest for borrowing money, and the level at which it is charged, is of fundamental importance to the economy. Unfortunately, the study of the interest rates charged in the middle ages has been hampered by the diversity of terms and methods used by historians. This article seeks to establish a standardized methodology to calculate interest rates from historical sources and thereby provide a firmer foundation for comparisons between regions and periods. It should also contribute towards the current historical reassessment of medieval economic and financial development. The article is illustrated with case studies drawn from the credit arrangements of the English kings between 1272 and c.1340, and argues that changes in interest rates reflect, in part, contemporary perceptions of the creditworthiness of the English crown.

Special issue of Reading medieval studies: first crusade historiography

Collected papers of the University of Reading Stenton Symposium, 2008.

Ontology supported comparison in vague domains

It is problematic to use standard ontology tools when describing vague domains. Standard ontologies are designed to formally define one view of a domain, and although it is possible to define disagreeing statements, it is not advisable, as the resulting inferences could be incorrect. Two different solutions to the above problem in two different vague domains have been developed and are presented. The first domain is the knowledge base of conversational agents (chatbots). An ontological scripting language has been designed to access ontology data from within chatbot code. The solution developed is based on reifications of user statements. It enables a new layer of logics based on the different views of the users, enabling the body of knowledge to grow automatically. The second domain is competencies and competency frameworks. An ontological framework has been developed to model different competencies using the emergent standards. It enables comparison of competencies using a mix of linguistic logics and descriptive logics. The comparison results are non-binary, therefore not simple yes and no answers, highlighting the vague nature of the comparisons. The solution has been developed with small ontologies which can be added to and modified in order for the competency user to build a total picture that fits the user’s purpose. Finally these two approaches are viewed in the light of how they could aid future work in vague domains, further work in both domains is described and also in other domains such as the semantic web. This demonstrates two different approaches to achieve inferences using standard ontology tools in vague domains.