We use ontology to capture the knowledge about domains. There are considerable number of ontologies which have been developed. To develop a new ontology, we use the existing concepts of the ontologies according to the domain needs. The reusability of the concept maintains shareability of knowledge across the domains and prevents multiple interpretation of the defined concept. An Internationalized Resource Identifier (IRI) of the concept is used to connect the various concepts with each other. This work aims to provide an IRI-Debug tool that enables the ontologist to validate their crafted ontology against the standard ontologies using IRI and gauging to what extent their ontology’s concepts or properties, if reused, compliant to the standard ontologies. This tool allows user to select a desired appropriate ontology from the available ontologies and validate the developed ontology with respect to standard ontologies.

To present the biodiversity information, a semantic model is required that connects all kinds of data about living creatures and their habitats. The model must be able to encode human knowledge for machines to be understood. Ontology offers the richest machine-interpretable (rather than just machine-processable) and explicit semantics that are being extensively used in the biodiversity domain. Various ontologies are developed for the biodiversity domain however a review of the current landscape shows that these ontologies are not capable to define the Indian biodiversity information though India is one of the megadiverse countries. To semantically analyze the Indian biodiversity information, it is crucial to build an ontology that describes all the essential terms of this domain from the unstructured format of the data available on the web. Since, the curation of the ontologies heavily depends on the domain where these are implemented hence there is no ideal methodology is defined yet to be ready for universal use. The aim of this article is to develop an ontology that semantically encodes all the terms of Indian biodiversity information in all its dimensions based on the proposed methodology. The comprehensive evaluation of the proposed ontology depicts that ontology is well built in the specified domain.

To present the biodiversity information, a semantic model is required that connects all kinds of data about living creatures and their habitats. The model must be able to encode human knowledge for machines to be understood. Ontology offers the richest machine-interpretable semantics that are being extensively used in the biodiversity domain. Various ontologies are developed for the biodiversity domain; however, these ontologies are not capable to define the Indian biodiversity information though India is one of the megadiverse countries. To semantically analyze the Indian biodiversity information, it is crucial to build an ontology that describes all the terms of this domain. Since the curation of the ontology depends on the domain where these are used, there is no ideal methodology defined yet. The aim of this article is to develop an ontology that semantically encodes all the terms of Indian biodiversity information in all its dimensions based on the proposed methodology. The evaluation of the proposed ontology depicts that ontology is well built in the specified domain.

In the era of World Wide Web, dependency has been increasing on real-time response, communication, disaster preparedness, and analysis by our society, experts from different areas including paramedics, risk management team, police, and firefighters. To ensure real-time response, appropriate information retrieval, expediting undertaking and response preparation and handling communiqué with all involved parties, there is a requirement of digitizing the resources, concepts semantically along with exploiting the information embedded in multimedia content. We also know that ontology has been proven the excellent mean of digitization. So through this paper, we propose a multimedia-driven disaster management ontology, featuring a different representation scheme integrating the multimedia content. This will offer semantic analysis and interoperability across heterogeneous multimedia data sources, hence facilitating in real-time disaster management.