Skip to main navigation menu Skip to main content Skip to site footer
Submitted October 8, 2026
Published 2026-10-15

Artículos

Vol. 8 No. 1 (2026): Revista Colegiada de la Ciencia

FAIR marine data management model with IODE articulation in Panama


DOI https://doi.org/10.48204/j.colegiada.v8n1.a11460

Cover image

References
DOI: 10.48204/j.colegiada.v8n1.a11460

Published: 2026-10-15

How to Cite

Peralta-Araúz , H. (2026). FAIR marine data management model with IODE articulation in Panama. Revista Colegiada De Ciencia, 8(1), 45–63. https://doi.org/10.48204/j.colegiada.v8n1.a11460

Abstract

Marine data management in developing countries faces structural challenges such as institutional fragmentation, lack of regulatory frameworks, and capacity limitations, hindering the adoption of FAIR principles (Findable, Accessible, Interoperable, Reusable). This study, with a qualitative approach complemented by a descriptive quantitative component, aimed to design a national marine data network model based on FAIR principles for Panama, articulated within the framework of the IOC-UNESCO IODE programme and OBIS. Fourteen semi-structured interviews were conducted, and a questionnaire was administered to 25 participants from key institutions (University of Panama, ARAP, STRI, UTP, UMIP, and

others).   Quantitative results revealed that 88.0% generate marine data, but 68.2% store it in internal

 

 

 

 

databases without interoperability. Knowledge of IODE platforms is limited: OceanExpert is known by 52.0% of participants, AquaDocs by 48.0%, and OBIS by 40.0%. Furthermore, 100% of participants expressed willingness to participate in training, identifying lack of funding (64.0%) and lack of specialized personnel (20.0%) as the main barriers. Qualitative analysis identified five structural gaps: storage fragmentation, absence of a national data policy, heterogeneity of capacities, low adoption of standards, and incipient governance. As the main contribution, the REPANDAMAR model (Panamanian Marine Data Network) is proposed, a distributed architecture with centralized coordination integrating regulatory, organizational, technical, training, and service components. Limitations include the reduced sample size (n=25) and the qualitative approach, which limit statistical generalization; nevertheless, source triangulation allows the identification of transferable patterns to similar contexts.

Downloads

Download data is not yet available.