Informatica

Ontologies are used to semantically enrich different types of information systems (IS), ensure a reasoning on their content and integrate heterogeneous IS at the semantical level. On the other hand, fuzzy theory is employed in IS for handling the uncertainty and fuzziness of their attributes, resulting in a fully fuzzy IS. As such, ontology- and fuzzy-based IS (i.e. ontology and fuzzy IS) are being developed. So, in this paper, we present a bibliometric analysis of the ontology and fuzzy IS concept to grasp its main ideas, and to increase its body of knowledge by providing a concept map for ontology and fuzzy IS. The main results obtained show that by adding ontologies and fuzzy theory to traditional ISs, they evolve into intelligent ISs capable of managing fuzzy and semantically rich (ontological) information and ensuring knowledge recognition in various fields of application. This bibliometric analysis would enable practitioners and researchers gain a comprehensive understanding of the ontology and fuzzy IS concept that they can eventually adopt for development of intelligent IS in their work.

Data involving spatial and/or temporal attributes are often represented at different levels of granularity in different source schemata. In this work, a model of such multigranular data is developed, which supports not only the usual order structure on granules, but also lattice-like join and disjointness operators for relating such granules in much more complex ways. In addition, a model for multigranular thematic attributes, to which aggregation operators are applied, is provided. Finally, the notion of a thematic multigranular comparison dependency, generalizing ordinary functional and order dependencies but specifically designed to model the kinds of functional and order dependencies which arise in the multigranular context, and in particular incorporating aggregation into the definition of the constraint, is developed.

This paper presents a new approach for the business and information systems (IS) alignment consisting of a framework, metamodel, process, and tools for implementing it in practice. The purpose of the approach is to fill in the gap between the existing conceptual business and IS alignment frameworks and the empirical business and IS alignment methods. The suggested approach is based on the SOA, GRAAL, and enterprise modeling techniques such as TOGAF, DoDAF, and UPDM. The proposed approach is applied on four real world projects. Both the application results and the small example are provided to validate the suitability of the approach.

The quality of software engineering projects often suffers due to the large gap between the way stakeholders present their requirements and the way analysts capture and express those requirements. With this problem in mind the new method for business rules driven IS requirements specification has been developed. In this paper the architecture of the requirements repository, which is at the core of the proposed method, is presented. The repository model supports the storage and management of all components of the captured requirements, including functions, business decisions, data sources, conceptual data model elements, business rules and their templates. The important aspects of the specialised requirements specification tool implementation are also overviewed.

A new method for a creation of the information system for sequential identification of states of technological processes or other dynamic systems for their supervision and control is considered. The states of dynamic system can be unknown and can change themselves abruptly or slowly. The method is based on a sequential nonlinear mapping of many-dimensional vectors of parameters (collection of which describes the present state of dynamic systems) into two-dimensional vectors in order to reflect the states and their changes on the PC screen and to observe the situation by means of computer. The mapping error function is chosen and expressions for sequential nonlinear mapping are obtained. The mapping preserves the inner structure of distances among the vectors. Examples are given.