ForestQB: An Adaptive Query Builder to Support Wildlife Research
Omar Mussa, Omer Rana, Beno\^it Goossens, Pablo Orozco-terWengel,, Charith Perera
TL;DR
ForestQB is an adaptive, user-friendly SPARQL query builder designed to help wildlife researchers access Linked-Data without requiring expertise in Semantic Web technologies.
Contribution
It introduces a novel form-based and natural language integrated query builder tailored for bioscience and wildlife research users.
Findings
Enables researchers to construct complex queries without prior Semantic Web knowledge.
Improves accessibility of Linked-Data for non-technical users.
Demonstrates effective integration of form-based and natural language interfaces.
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 available at https://iotgarage.net/demo/forestQB
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Taxonomy
TopicsSemantic Web and Ontologies · Biomedical Text Mining and Ontologies · Natural Language Processing Techniques