Search results

The purpose of this study is to reduce the semantic distance by proposing a model for integrating indexes of textual and visual features via a multi-modality ontology and the use of DBpedia to improve the comprehensiveness of the ontology to enhance semantic retrieval.

A multi-modality ontology-based approach was developed to integrate high-level concepts and low-level features, as well as integrate the ontology base with DBpedia to enrich the knowledge resource. A complete ontology model was also developed to represent the domain of sport news, with image caption keywords and image features. Precision and recall were used as metrics to evaluate the effectiveness of the multi-modality approach, and the outputs were compared with those obtained using a single-modality approach (i.e. textual ontology and visual ontology).

The results based on ten queries show a superior performance of the multi-modality ontology-based IMR system integrated with DBpedia in retrieving correct images in accordance with user queries. The system achieved 100 per cent precision for six of the queries and greater than 80 per cent precision for the other four queries. The text-based system only achieved 100 per cent precision for one query; all other queries yielded precision rates less than 0.500.

This study only focused on BBC Sport News collection in the year 2009.

The paper includes implications for the development of ontology-based retrieval on image collection.

This study demonstrates the strength of using a multi-modality ontology integrated with DBpedia for image retrieval to overcome the deficiencies of text-based and ontology-based systems. The result validates semantic text-based with multi-modality ontology and DBpedia as a useful model to reduce the semantic distance.

This study aims to examine the current status and different characteristic features of research data repositories established by BRICS nations in order to understand the research data infrastructure within BRICS countries.

The data were collected from the re3data repository (http://www.re3data.org/), focusing specifically on BRICS nations. The data were analyzed to grasp the current status of research data repositories in BRICS countries. The dataset was retrieved on March 2, 2024. A total of 195 Research Data Repositories (RDRs) originating from BRICS countries were identified and selected for comprehensive analysis.

As of March 2, 2024, re3data.org indexes a total of 3,192 Research Data Repositories (RDRs) worldwide, with BRICS nations contributing 195. China leads among BRICS nations, followed by India, Russia, and Brazil. Scientific and Statistical Formats are the most shared content categories, followed closely by Standard Office Documents. There is notable diversity in the subjects covered by RDRs across BRICS nations. English is the primary interface language, followed by Chinese and Portuguese. “House, tailor-made” software is widely used for creating RDRs, followed by Dataverse and DSpace. Fourteen metadata standards are found, with Dublin Core metadata being the most prevalent, followed by the DataCite Metadata Scheme. Most repositories are disciplinary, followed by institutional ones. Most repositories specify data upload types, with “restricted” being the most common, followed by closed types. Open access is predominant in data access, followed by restricted access and embargo periods, while a small number restrict access entirely.

The present study will help gauge the strengths and weaknesses of the RDRs of BRICS nations and also learn how open these RDRs are for data access and upload provisions. The study contributes to a broader comprehension of the accessibility and usability of research data within the BRICS community, ultimately fostering greater transparency, collaboration, and knowledge dissemination within the scientific community, thus fostering greater innovation and advancement in research endeavors. The study provides a nuanced understanding of the research data infrastructure within BRICS nations, highlighting key trends, strengths, and areas for potential improvement.