logolpt fri_logo

Semantic web and Ontologies

Current version of World Wide Web (WWW) is consisted of several mutually connected documents that are presented to human users by computers. These documents originated in interconnected systems where every user could contribute. This also results in a fact that information quality can’t always be guaranteed. Current World Wide Web consists of data, information and knowledge, but the role of computers at this stage is only to deliver and represent the content of the documents that describe knowledge. To integrate different information resources users have to manually interpret these data.

Rapid Ontology Development with constant evaluation

Semantic Web tends to improve current World Wide Web with computers processing, interpreting, integrating data on the web and with this approach aiding human users in discovering complex knowledge. Semantic Web is focused towards sharing and reusing of data and not documents. The research area emphasizes establishment of common framework to enable sharing and reusing data among applications and enterprises.

Ontologies are the mechanism that enables us achieving these functionalities. The research are of ontology development is concerned with presentation of data and knowledge and are commonly regarded as specialization of conceptualization – terms and their meaning that are used for description and presentation of selected problem domain.

Linking Open Data for integration of various online repositories


Rapid Ontology Development

The Semantic Web vision is the idea of having data on the Web defined and linked in a way that it can be used by machines not just for display purposes (e.g. user), but for automation, integration and reuse of data across various applications. Next generation of the Web is expected to provide automated services based on machine processable semantics of data, reasoning techniques and heuristics that make use of these data. The applications of ontologies are mainly restricted to academia while successful employment in business environments is rare.

The simplicity of using approaches for ontology construction and accompanying tool support is an important issue which needs a lot of attention and further work. Current approaches in ontology development are technically very demanding and require long learning curve and are therefore inappropriate for business users. In majority of existing approaches an additional role of knowledge engineer is required for mediation between actual knowledge that business users possess and ontology engineers who encode knowledge in one of selected formalisms. Introduction of several abstraction layers as suggested in systems for business rules manipulation and MDA approach has turned out to be very effective in development of ontologies and using it in business applications. Besides simplifying the process of ontology construction we also have to focus on very important aspect of ontology completeness. Several researches have discussed error free ontologies and identified frequent errors and anomalies in ontology development, which is advised to be included in the development process and therefore aiding users at prevention and elimination of repeated design errors.

Rapid Ontology Development with constant evaluation

The main purpose of our work was to define innovative model for rapid ontology development (ROD) that is suitable for users without extensive technical knowledge and knowledge of ontology design. The proposed process includes pre-development, development and post-development activities, from business vocabulary acquisition to employment of developed ontology as a functional component in information system. ROD process also includes constant evaluation of developed ontologies which is conducted at every step of the process and gives user recommendations on how to improve the quality of developing ontology. This functionality is implemented using ontology completeness indicator (OC) that is used for following the steps of ROD process in simplified manner. Constant evaluation of developing ontology is also performed with dynamic adaption of weights in calculation which in turn aids user with recommendations on how to improve ontology. Along with the development of ROD model several possibilities of using ontology as a functional component was investigated. Ontology can be used as whole or just partly by using only schematic part. To improve integration with existing data sources, interfaces for direct linking of semi-structured data in ontology were developed. This was accomplished with a generic approach of regular expressions that enables us to connect to any semi-structured source of data, e.g. document, web page, data base, CSV file etc. For the evaluation purposes of proposed approach FITS ontology for trading with financial instruments was developed. Its generic design enables users very straightforward reuse. In this experiment ROD approach turned out to be very effective. It took less iterations to develop a working version of ontology and the required confirmation level of ontology quality was also achieved earlier.

By this, our work represents integral model for rapid ontology development, that enables users without extensive technical knowledge development of ontology. By doing this they have an ability to employ the advantages of semantic web in building semantically enabled application that can very intuitively reuse data from several (also semi-structured) data sources.

For more information please consider:

Employment of Semantic Web technologies

FITS applicationFor more information please consider:

Mind map approach to data traversal

PanoramaThe increasing amount of information and the absence of an effective tool for assisting users with minimal technical knowledge lead us to use associative thinking paradigm for implementation of a software solution – Panorama. In this study, we present object recognition process, based on context + focus information visualization techniques, as a foundation for realization of Panorama. We show that user can easily define data vocabulary of selected domain that is furthermore used as the application framework. The purpose of Panorama approach is to facilitate software development of certain problem domains by shortening the Software Development Life Cycle with minimizing the impact of implementation, review and maintenance phase. Our approach is focused on using and updating data vocabulary by users without extensive programming skills. Panorama therefore facilitates traversing through data by following associations where user does not need to be familiar with the query language, the data structure and does not need to know the problem domain fully. Our approach has been verified by detailed comparison to existing approaches and in an experiment by implementing selected use cases. The results confirmed that Panorama fits problem domains with emphasis on data oriented rather than ones with process oriented aspects. In such cases the development of selected problem domains is shortened up to 25%, where emphasis is mainly on analysis, logical design and testing, while omitting physical design and programming, which is performed automatically by Panorama tool.
For more information please consider:


Semantic integration of people data

Data extraction and cleansing of semi-structured data