Ontology-Based Data Observatory for Formal Knowledge Representation of UXO Using Advanced Semantic Web Technologies

Author:

Horvat Marko1ORCID,Krtalić Andrija2ORCID,Akagić Amila3ORCID,Mekterović Igor1ORCID

Affiliation:

1. Department of Applied Computing, Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, HR-10000 Zagreb, Croatia

2. Institute of Cartography and Photogrammetry, Faculty of Geodesy, University of Zagreb, Kačićeva 26, HR-10000 Zagreb, Croatia

3. Faculty of Electrical Engineering, University of Sarajevo, Zmaja od Bosne 8, BH-71000 Sarajevo, Bosnia and Herzegovina

Abstract

As landmines and other unexploded ordnances (UXOs) present a great risk to civilians and infrastructure, humanitarian demining is an essential component of any post-conflict reconstruction. This paper introduces the Minefield Observatory, a novel web-based datastore service that semantically integrates diverse data in humanitarian demining to comprehensively and formally describe suspected minefields. Because of the high heterogeneity and isolation of the available minefield datasets, extracting relevant information to determine the optimal course of demining efforts is time-consuming, labor-intensive and requires highly specialized knowledge. Data consolidation and artificial intelligence techniques are used to convert unstructured data sources and store them in an ontology-based knowledge database that can be efficiently accessed through a Semantic Web application serving as the Minefield Observatory user interface. The MINEONT+ ontology was developed to integrate diverse mine scene information obtained through non-technical surveys and remote sensing, such as aerial and hyperspectral satellite imagery, indicators of mine presence and absence, contextual data, terrain analysis information, and battlefield reports. The Minefield Observatory uses the Microdata API to embed this dataset into dynamic HTML5 content, allowing seamless usage in a user-centric web tool. A use-case example was provided demonstrating the viability of the proposed approach.

Publisher

MDPI AG

Reference74 articles.

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2. Remote Sensing Based Detection of Minefields;Maathuis;Geocarto Int.,2003

3. Bajić, M., Matić, C., Krtalić, A., Candjar, Z., and Vuletic, D. (2011). Research of the Mine Suspected Area, HCR Centre for Testing, Development and Training Ltd.. Available online: https://www.ctro.hr/publications.

4. Matić, Č., Laura, D., Turšić, R., and Krtalić, A. (2014). Analytical Assessment for the Process of Collecting Additional Data on a Suspected Hazardous Area in Humanitarian Demining, CROMAC-CTDT Ltd.. Available online: https://www.ctro.hr/publications.

5. Geneva International Centre for Humanitarian Demining (2024, February 04). A Guide to the International Mine Action Standards. Available online: https://www.files.ethz.ch/isn/26813/Guide_IMAS_2006.pdf.

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