3 research outputs found

    A conceptual modeling methodology based on niches and granularity

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    This paper presents a methodology for conceptual modeling which is based on a new modeling primitive, the niche, and associated constructs granularity and reconciliation. A niche is an environment where entities interact for a specific purpose, playing specific roles, and according to the norms and constraints of that environment. Granularity refers to the relative level of power or influence of an entity within a niche. Reconciliation is a relationship from N entities onto one reconciled entity, and represents explicitly a situation where two or more different perspectives of the same entity have been reconciled, by negotiation, into a single consensus view. The methodology we propose provides a systematic method of designing conceptual models along with a process for normalising inappropriate relationships. Normalising is a prescriptive process for identifying and remedying inconsistencies within a model based on granularities. Drawing on a number of case studies, we show how niches and granularity make complexity easier to manage, highlight inaccuracies in a model, identify opportunities for achieving project goals, and reduce semantic heterogeneity

    Migration of the Individuals

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    AbstractThe individuals are modeled by the elements of variable domains. The primitive frame to detect the individual migration from domain to domain is proposed. The supporting computational model is based on a separation of individuals into actual, possible and virtual ones. As was shown, this leads to an adoption of the stage-by-stage cognition model with a pair of evolvents to capture dynamics of the domains – the 2-dimensions model. The first evolvent reflects the generation of the individuals in a domain, the beginning of and canceling out their existence in a domain. The second evolvent reflects the shifts in properties of the individuals. As awaited this unified data model will have the applications to a wide range of models in computer science and Information Technologies
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