Informatica

Knowledge graphs are commonly represented by ontology-based databases. Tracking the provenance of ontological changes and ensuring ontology consistency is important. In this work, we propose a transaction manager for ontology-based database manipulation that combines blockchain and Semantic Web technologies. The latter is used for the efficient querying and modification of data, whereas the blockchain is used for the secure storage and tracking of changes. The blockchain enables a decentralized setup and data restoration. We evaluate our solution by measuring cost and time. Our solution introduces some overhead for updates whereas querying works at the same speed as the underlying ontology database.

In this paper we propose facilitating ontology development by constant evaluation of steps in the process of ontology development. Existing methodologies for ontology development are complex and they require technical knowledge that business users and developers don't poses. By introducing ontology completeness indicator developer is guided throughout the development process and constantly aided by recommendations to progress to next step and improve the quality of ontology. In evaluating the ontology, several aspects are considered; from description, partition, consistency, redundancy and to anomaly. The applicability of the approach was demonstrated on Financial Instruments and Trading Strategies (FITS) ontology with comparison to other approaches.

The main scientific problems investigated in this paper deal with the problem of multiple criteria evaluation of the quality of the main components of e-learning systems, i.e., learning objects (LOs) and virtual learning environments (VLEs). The aim of the paper is to analyse the existing LO and VLE quality evaluation methods, and to create more comprehensive methods based on learning individualisation approach. LOs and VLEs quality evaluation criteria are further investigated as the optimisation parameters and several optimisation methods are explored to be applied. Application of the experts' additive utility function using evaluation criteria ratings and their weights is explored in more detail. These new elements make the given work distinct from all the other earlier works in the area.

The advance of the Web has significantly and rapidly changed the way of information organization, sharing and distribution. The next generation of the web, the semantic web, seeks to make information more usable by machines by introducing a more rigorous structure based on ontologies. In this context we try to propose a novel and integrated approach for a semi-automated extraction of ontology-based semantic web from data-intensive web application and thus, make the web content machine-understandable. Our approach is based on the idea that semantics can be extracted by applying a reverse engineering technique on the structures and the instances of HTML-forms which are the most convenient interface to communicate with relational databases on the current data-intensive web application. This semantics is exploited to produce over several steps, a personalised ontology.

In the present paper, the method of structure analysis for multivariate functions was applied to examine the global sensitivity of three complex models: the HIV/AIDS infection spread, radar search, and the multiple criteria decisions.