engleski

MINEONT: A proposal for a core ontology in the aerial non-technical survey domain

Logical representation of knowledge enables reasoning based on formal logic, integration of heterogeneous data sources, augmentation of existing knowledge, and discovery of hidden knowledge that is hidden or unknown even to experienced professionals. Moreover, many high- performance software tools and services for logical reasoning are readily available in the academic community. Computational ontologies, or ontologies for short, are a comprehensive, formal, scalable, and adaptable methods for knowledge representation and automated reasoning. They have been successfully used in many diverse application domains, from medicine and natural sciences to engineering and applied sciences. However, the use of ontologies in the context of demining is novel and has not been exploited to the full advantage. In this context, a new core ontology called MINEONT (an acronym for "MINE-action ONTology") has been proposed. The MINEONT is written in the OWL-DL 2 formalism and allows an expressive and formal representation of concepts in mine action, high- level semantics, geospatial metadata, and information obtained through method of remote sensing, non-technical surveys, and other mine action survey types. The vocabulary of this ontology supports, among others, the following corpora: multisensory aerial and satellite imagery, derived indicators of mine presence and absence, contextual data, terrain analysis information, formalized knowledge of the humanitarian demining specialists in the form of declarations and procedures. The designed ontology has many advantages in describing data for non- technical surveys. However, it is also relevant for building a specialized recommender artificial intelligence (AI) expert system. Such an ontology- based decision support system (DSS) would integrate a large amount of collected data and facilitate interpretation and decision-making processes. In the paper, details about the Web Ontology Language (OWL) are given and its advantages for application in the aerial non- technical survey for humanitarian demining are explained. The MINEONT model is introduced and described in detail. The advantages of MINEONT compared to other existing methods in the aerial non-technical survey system are planned to be tested and demonstrated as part of scientific projects in which domestic and foreign partners, including CROMAC, will participate.

aerial non-technical survey ; ontology ; knowledge database ; machine learning ; recommender system ; secondary mine indicators ; DSS ; CROMAC

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