Ofunama, Preye and Denyefa C, Wari and Okogbue C, Blessing (2025) Digitizing biodiversity: Enhancing online access to indigenous aquatic species of the nun river. World Journal of Advanced Research and Reviews, 26 (3). pp. 668-674. ISSN 2581-9615
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Abstract
Data management involves data collection, analysis, interpretation and presentation for easy communication of findings to enhance knowledge advancement and innovations for development and nation building. The fisheries sector in Nigeria and Africa as a whole need detailed electronic database of indigenous aquatic fisheries resources and this can only be made possible with proper data collection, analysis, documentation to enhance their availability, accessibility and presented in formats that are usable for easy retrieval. This research involved a field study on the species composition of Nun River and a desktop survey of fisheries reports on aquatic macro-fauna such as the fin fishes and the respective researchers and/or authors involved. The tools for database development to organize the fisheries data are HTML, CSS, for structuring and styling the web pages for front-end development, PHP for back-end development, MySQL, XAMPP and AJAX for relational database management, development environment, and data communication. By this project, the local, common and scientific names of Nun River species are uploaded on the database for a start since there are many other rivers bifurcating from the Niger River in the study area (Nigeria) which will be retrieved from the desktop survey on other researchers. These fisheries data are organized for evidence-based decision making and policy development which is key in resource management and sustainable development of the fisheries sector.
Item Type: | Article |
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Official URL: | https://doi.org/10.30574/wjarr.2025.26.3.2228 |
Uncontrolled Keywords: | Environmental Resource Management; Database Development; Data Management; Nun River; Fisheries |
Depositing User: | Editor WJARR |
Date Deposited: | 20 Aug 2025 12:07 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/3942 |