2018 & 2019 Winner

An integrated data pipeline for small-scale fisheries

The Inspire Challenge is an initiative to challenge partners, universities, and others to use CGIAR data to create innovative pilot projects that will scale. We look for novel approaches that democratize data-driven insights to inform local, national, regional, and global policies and applications in agriculture and food security in real time; helping people–especially smallholder farmers and producers–to lead happier and healthier lives.

This proposal was selected as a 2018 pilot project and 2019 scale-up runner up project, with the team receiving a total of 225,000 USD to put their ideas into practice.

An integrated data pipeline for small-scale fisheries

Every day, about 40 million small-scale fishers go out fishing, yet virtually none of their activities or yields are documented. This global data deficiency means that small-scale fisheries contributions to local livelihoods and food security are often overlooked in policy, management, and development decisions.

This project aims to put small-scale fisheries data in the hands of fisheries officers, researchers, and local stakeholders by creating an automated data pipeline to highlight temporal and spatial changes in fish production.

The team has installed more than 300 vessel-tracking devices on boats in Timor-Leste, where the project piloted the concept, that transmit geospatial tracking data through cellular networks to an open-source, cloud-based decision dashboard. Cloud-based analytics and machine learning are then used to identify specific fishing activities.

The dashboard is one of the most sophisticated data collection systems for small-scale fisheries in the world, tracking fishing activities such as the number and type of fish caught by individual boats in near real-time.

New vessel-tracking technologies are sufficiently small and economical to gather the data needed to achieve Sustainable Development Goal 14: Conserve and sustainably use the oceans, seas, and marine resources for sustainable development.

The project also aims to highlight the crucial role of women in fisheries activities and relationship to dependable household food and nutrition security; gender dis-aggregated data standards are followed which will contribute to closing gender data gaps.

Following the successful national proof of concept in Timor-Leste, the project is currently scaling to seven additional countries in Africa and Asia.

Team

Alex Tilley | Email
WorldFish Scientist

Shaun Wilkinson
WorldFish Consultant

David Solomon | Email
CEO, Pelagic Data Systems

Project Partners

Wilderlab, a biomonitoring service based in Wellington, New Zealand, develops, improves, and maintains R scripted pipeline from catch data records to peskAAS decision dashboard. They also carry out statistical testing of nearest neighbour assignment.

WorldFish provides project leadership, on-the-ground activities, project implementation, and project reporting.

Pelagic Data Systems developed the integration of catch data with boat tracking data and innovates machine learning techniques to pattern detection in fishing behaviour and production over time and space.

Shaun Wilkinson explains the data tool behind the initiative.

Step by step

October 2018

US$100K grant

The project was one of five winners of the Inspire Challenge 2018 and was awarded US$100K at the second annual convention of the CGIAR Platform Big Data in Agriculture, 3-5 October 2018.

November 2018 - April 2019

Registration of fishers and installation of boat trackers

The WorldFish in-country team, in partnership with the Ministry of Agriculture and Fisheries (MAF), has deployed roughly 300 Pelagic Data Systems boat tracking units on artisanal fishing boats around Timor-Leste, including the enclave of Oecusse.

This partnership enables the project to support MAF in augmenting the national registration of small-scale fishing boats while installing tracking units at the same time.

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January - April 2019

Filtering data using machine learning

By teaching machines how to identify fishing activity based on the speed, trajectory, and tortuosity data collected by the PDS tracking units, fishing activities can be filtered from not-fishing activities and potentially flag for suspicious or unusual movement.

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April - July 2019

Capacity building, training, and participatory development of data systems

The project will provide three aspects of capacity building and training for government partners, fisher stakeholders, and data collectors:

  1. Installing and maintaining PDS trackers, attaching trackers to the boat in a way that is durable, non-damaging, and effectively exposing trackers to sunlight
  2. Collecting landing data
  3. Manipulating and comprehending decision dashboards

WorldFish and PDS trained and supported 11 new data collectors (one per coastal municipality) joining MAF.

A workshop with the Fisheries Directorate was held at the end of April to assess progress and evaluate how tools and processes match needs and aspirations.

 

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July 2019

Launch of near real-time monitoring system

The team launched the dashboard, Automated Analytics System for Small-Scale Fisheries in Timor-Leste (PeskAAS), which tracks fishing activities–including the number and type of fish caught by individual boats in near real-time.

TEST OUT THE TOOL

July 2019

Making headlines in Timor-Leste

The project made headlines in Timor-Leste for the launch of its near real-time small-scale fisheries monitoring system. The dashboard is one of the most sophisticated data collection systems for small-scale fisheries in the world. It puts important data in the hands of fisheries officers, researchers, and local stakeholders. The tool will ultimately enable better understanding the contribution of fish and fisheries to local livelihoods and food security.

READ MORE

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August 2019

Journal article publication

The first journal article using the peskAAS monitoring system was published in Frontiers in Marine Science. 

The study tests the effects of fish aggregating devices (FADs) at increasing fish production in Timor-Leste. FADs have shown success in improving catch rates elsewhere in the Pacific by making pelagic stocks more accessible to small-scale fishers.

Eight experimental FADs were deployed at four sites around Timor-Leste and catch and effort data from FAD and non-FAD fishing trips was recorded. Results show a significant positive effect of FADs on catch rates when controlling for random site variation, with FADs paying for themselves in roughly five months or less at three out of four sites.

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October 2019

System testing in seven additional countries in Asia and Africa

The team signed an agreement to expand their pioneering work to better understand stocks and catches from small-scale fisheries across seven countries in Africa and other parts of Asia.

The Memorandum of Understanding, signed at a special ceremony at WorldFish headquarters in Penang, Malaysia, provides the framework for WorldFish and Pelagic Data Systems to further develop and provide access to innovative data collection solutions for fisheries.

“Working closely with innovative partners in the private sector – especially the tech sector – can help us generate more and better data, which in turn can mean our research has a greater impact in supporting some most vulnerable people in the world,” said Dr. Alex Tilley, Scientist at WorldFish.

 

READ MORE

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August - October 2019

Evaluation of uptake, sustainability, and scalability

In the final stages of the pilot phase, an evaluation workshop will provide a final assessment of the system’s capacity and impact, an evaluation of uptake, and an assessment of the system’s sustainability and scalability to other countries and fisheries.

October 2019

US$125K scale-up grant

The project was awarded a 2019 Inspire Challenge Scale-up grant of US$125K at the third annual convention of the CGIAR Platform for Big Data in Agriculture, 16-18 October 2019.

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January - August 2020

Ongoing updates to the application dashboard

Updates are ongoing to the dashboard on two levels:

  • Augmented (paid tier): re-imagining fishing data, testing with stakeholders, integrating new system, using German train-tracking model to look at how fish catch quantities relate to time spent fishing (efficiency analysis).
  • Automated (open access, pending financial sustainability): optimizing for use by fishers

Updates are scheduled to be completed by August 2020.

February 2020

Financial sustainability model report

The team is working on producing:

  1. A brief of the peskAAS system with which to approach impact investors
  2. A report detailing potential business models for the scaling of the peskAAS fisheries data system, including a brief strategy summary and at least two different scaling approaches.
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March 2020

Journal article review and publication

An article titled, “PeskAAS: Automated analytics of relative fish abundance over time and space” is in review, and publication is expected in March.

May 2020

Addition to project team

A new data scientist from WorldFish will join the team.

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November 2020

Data security and ownership case study/manual

The importance of defining data security and ownership has become ever more apparent. Challenges faced by the team regarding defining their own accountability, inspired them to develop a manual on the subject, in collaboration with the BIG DATA Platform.

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August - December 2020

Field testing

Field testing of components is planned to take place in Lake Malawi, Cox’s Bazar, Bangladesh, and Penang, Malaysia. These locations are already transmitting vessel movement data.

Two pelagic tracking units have also been sent to Egypt, Nigeria, and Zambia, and plans are in place to improve data yield in these locations.

 

Stay tuned for more updates!

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