Akademik Veri Yönetim Sistemi
Aquatic Science and Engineering, cilt.40, sa.1, ss.42-52, 2025 (ESCI)
Recently, the mission of the aquaculture production sector in achieving sustainable development goals has become increasingly critical. Synthesizing large data sets with advanced technological tools in aquaculture is no longer a luxury but a necessity for significant progress. This article examines the pivotal role of Application Programming Interface (API) integration in advancing open science and collaborative research in aquaculture. It also explores the use of Artificial Intelligence (AI) to facilitate data analysis across disparate databases and proposes the establishment of a ChatGPT-like virtual environment to catalyze seamless global collaboration among researchers. A comprehensive overview is presented on the feasibility of a unified AI-driven database that collects, analyzes, and shares data, overcomes geographical constraints, and supports a shared information ecosystem. The article scrutinizes current implementations, identifies gaps in existing infrastructures, and outlines a robust framework for API integration that could significantly enhance innovation and operational efficiency in aquaculture research.