The FOLE Database

This paper continues the discussion of the representation and interpretation of ontologies in the first-order logical environment {\ttfamily FOLE} (Kent). Ontologies are represented and interpreted in (many-sorted) first-order logic. Five papers provide a rigorous mathematical representation for the {\ttfamily ERA} (entity-relationship-attribute) data model (Chen) in particular, and ontologies in general, within the first-order logical environment {\ttfamily FOLE}. Two papers (Kent and another paper) represent the formalism and semantics of (many-sorted) first-order logic in a \emph{classification form} corresponding to ideas discussed in the Information Flow Framework (IFF). Two papers (Kent and the current paper) represent (many-sorted) first-order logic in an \emph{interpretation form} expanding on material found in the paper (Kent). A fifth paper (Kent) demonstrates that the classification form of {\ttfamily FOLE} is "informationally equivalent" to the interpretation form of {\ttfamily FOLE}, thereby defining the formalism and semantics of first-order logical/relational database systems. Although the classification form follows the entity-relationship-attribute data model of Chen, the interpretation form incorporates the relational data model of Codd. Two further papers discuss the "relational algebra" (Kent) and the "relational calculus". In general, the {\ttfamily FOLE} representation uses a conceptual structures approach, that is completely compatible with the theory of institutions (Goguen and Burstall), formal concept analysis (Ganter and Wille), and information flow (Barwise and Seligman).Comment: 42 pages, 17 figures, 9 table

Application of predicate logic for failure detection in SCADA systems

We consider the task of failure detection and localization. It is based on the analysis of the information flow state change in the system. We suggest a structural and logical model to describe SCADA of any topology. It is possible to form diagnostic features of independent failure detection. They are based on the characteristic functions of three-valued logic. We determine the predicate system of knowledge representation to implement the method of SCADA diagnostics in the event of incomplete data.Розглядається задача виявлення та локалізації відмов у SCADA на основі аналізу зміни стану інформаційних потоків у системі. Пропонується структурно-логічна модель опису SCADA будь-якої топології. На основі характеристичних функцій тризначної логіки формуються діагностичні ознаки виявлення незалежної відмови. Визначається предикатна система подання знань для реалізації методу діагностики працездатності SCADA в умовах неповних даних / недостовірних даних