ForestQB: An adaptive query builder to support wildlife research

Mussa, Omar, Rana, Omer ORCID: https://orcid.org/0000-0003-3597-2646, Benoît, Goossens, Orozco-terWengel, Pablo and Perera, Charith ORCID: https://orcid.org/0000-0002-0190-3346 2022. ForestQB: An adaptive query builder to support wildlife research. Presented at: The 21st International Semantic Web Conference 2022, Hangzhou, China, 23-27 October 2022. CEUR Workshop Proceedings. , vol.3254

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Abstract

This paper presents ForestQB, a SPARQL query builder, to assist Bioscience and Wildlife Researchers in accessing Linked-Data. As they are unfamiliar with the Semantic Web and the data ontologies, ForestQB aims to empower them to benefit from using Linked-Data to extract valuable information without having to grasp the nature of the data and its underlying technologies. ForestQB is integrating Form-Based Query builders with Natural Language to simplify query construction to match the user requirements. (Demo is available at https://iotgarage.net/demo/forestQB)

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Advanced Research Computing @ Cardiff (ARCCA) Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Date of First Compliant Deposit:	28 January 2023
Last Modified:	14 Jun 2024 15:17
URI:	https://orca.cardiff.ac.uk/id/eprint/156340

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