Conceptual Modeling of Prosopographic Databases Integrating Quality Dimensions

International audienceProsopographic databases, which allow the study of social groups through their bibliography, are used today by a significant number of historians. Computerization has allowed intensive and large-scale exploitation of these databases. The modeling of these proposopographic databases has given rise to several data models. An important problem is to ensure a level of quality of the stored information. In this article , we propose a generic data model allowing to describe most of the existing prosopographic databases and to enrich them by integrating several quality concepts such as uncertainty, reliability, accuracy or completeness

Quantification of the Uncertainties for the Space Launch System Liftoff/Transition and Ascent Databases

A detailed description of the uncertainty quantification process for the Space Launch System Block 1 vehicle configuration liftoff/transition and ascent 6-Degree-of-Freedom (DOF) aerodynamic databases is presented. These databases were constructed from wind tunnel test data acquired in the NASA Langley Research Center 14- by 22-Foot Subsonic Wind Tunnel and the Boeing Polysonic Wind Tunnel in St. Louis, MO, respectively. The major sources of error for these databases were experimental error and database modeling errors

Data modeling dealing with uncertainty in fuzzy logic

This paper shows models of data description that incorporate uncertainty like models of data extension EER, IFO among others. These database modeling tools are compared with the pattern FuzzyEER proposed by us, which is an extension of the EER model in order to manage uncertainty with fuzzy logic in fuzzy databases. Finally, a table shows the components of EER tool with the representation of all the revised models.The past and the future of information systems: 1976-2006 and beyondRed de Universidades con Carreras en Informática (RedUNCI

Implementing imperfect information in fuzzy databases

Information in real-world applications is often vague, imprecise and uncertain. Ignoring the inherent imperfect nature of real-world will undoubtedly introduce some deformation of human perception of real-world and may eliminate several substantial information, which may be very useful in several data-intensive applications. In database context, several fuzzy database models have been proposed. In these works, fuzziness is introduced at different levels. Common to all these proposals is the support of fuzziness at the attribute level. This paper proposes first a rich set of data types devoted to model the different kinds of imperfect information. The paper then proposes a formal approach to implement these data types. The proposed approach was implemented within a relational object database model but it is generic enough to be incorporated into other database models.ou