International Council for the Exploration of the Sea
Working Group on Technology Integration for Fishery-Dependent Data (WGTIFD).pdf (1.57 MB)

Working Group on Technology Integration for Fishery-Dependent Data (WGTIFD; outputs from 2020 meeting)

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posted on 2022-02-11, 09:24 authored by ICESICES

The Working Group on Technology Integration for Fishery-Dependent Data (WGTIFD) examines electronic technologies and applications developed to support fisheries-dependent data collection, both on shore and at sea, including electronic reporting (ER), electronic monitoring (EM), positional data systems, and observer data collection. The primary objective of this report is to inventory and review the various hardware, software applications, and approaches to fisheries dependent data collection. The report identifies the challenges and successes of electronic technology programmes worldwide; reviews the technical, policy, and analytical considerations for utilizing data from electronic technologies; and reports on the developments in machine learning and computer vision technologies and their applications in fisheries dependent data collection. WGTIFD also started to examine the risks and benefits of different technologies and how to integrate data from technologies; these topics will be examined further by the working group in the next year.

There are a number of tools that are being adopted more widely across a range of fisheries, vessel sizes, etc., including ER systems that allow for self-reporting to meet certain data requirements and positional data systems such as vessel monitoring systems (VMS), which can provide near real time location of fishing fleets. EM has been gaining interest very rapidly over the last five years, but there are some challenges in terms of inadequate funding, lack of clear policies and standards, and the costs of manual video review and data transmission. In almost every instance of an EM program or project, computer vision (CV) and machine learning (ML) applications are being developed to reduce costs, and improve the timeliness and accuracy of information. While CV/ML alone will not lower the barrier entirely for much wider adoption of EM, these technology developments are advancing in the marine sciences and will help shape fisheries monitoring in the future.

The broad relevance of electronic technologies and the work of WGTIFD has been highlighted both within and beyond the ICES network in recent years. Fisheries and fishers have been greatly impacted by the resulting impacts from the COVID-19 pandemic, but many electronic technology programmes around the world have provided some amount of resiliency to data collection (e.g. observers were removed from vessels, but electronic monitoring was still deployed). Looking ahead, WGTIFD recommends working with data-poor stock assessment scientists and working groups to examine approaches for adding new types of electronic monitoring data into assessments to complement existing analyses that rely on data with a longer time-series.


Published under the auspices of the following ICES Steering Group or Committee

  • EOSG

Published under the auspices of the following ICES Expert Group or Strategic Initiative



ICES Scientific Reports





Contributors (Editors)

Brett Alger; Lisa Borges

Contributors (Authors)

Amos Barkai; Ana Rita Fraga; Brad McHale; Brant McAfee; Brett Alger; Brian Cowan; Carole Nedig Christopher McGuire; Christopher Zimmermann; Daniel Linden; Daniel Roberts; Edwin van Helmond Farron Wallace; Helen Holah; Howard McElderry; Jason Bryan; Jørgen Dalskov; Josh Keaton Julia Magdalena Wouters; Justin Defever; Karine Briand; Lauren Bonatakis; Lauren Clayton Lisa Borges; Luis Cocas; Maggie Chan; Mark Hager; Miguel Nuevo; Morgan Wealti; Nichole Rossi Oscar Gonzalez; Pascal Bach; Patrick Moelo; Rachel Kilburn; Raiana McKinney; Rubén Toro Samantha Stott; Sofie Vandemaele



Recommended citation

ICES. 2021. Working Group on Technology Integration for Fishery-Dependent Data (WGTIFD; outputs from 2020 meeting). ICES Scientific Reports. 3:03. 54 pp.