WorldFish is a winner of the CGIAR Platform for Big Data in Agriculture’s 2018 Inspire Challenge. The winning proposal, ‘An integrated data pipeline for small-scale fisheries’, was selected from more than 130 submissions.
Recommended publications
- Illuminating hidden harvests: The contribution of small-scale fisheries to sustainable development
- Catch trend and stock assessment of Hilsa Tenualosa ilisha using digital image measured length-frequency data
- Narrative assemblages for power-balanced coastal and marine governance. Tara Bandu as a tool for community-based fisheries co-management in Timor-Leste
WorldFish, in partnership with Pelagic Data Systems, is a winner of the CGIAR Platform for Big Data in Agriculture’s 2018 Inspire Challenge. The award was presented following three days of presentations and pitches during the platform’s second annual congress—Decoding the Data Ecosystem—in Nairobi, Kenya from 3 to 5 October 2018.
The Inspire Challenge encourages the use of big data approaches to advance agricultural research and development. The winning entries are innovations with real potential for developmental impact, have mobilized underused or misused data, and demonstrate meaningful partnerships with CGIAR and other sector members.
WorldFish’s proposal, ‘An integrated data pipeline for small-scale fisheries’, was selected from more than 130 submissions in four categories: Revealing Food Systems, Monitoring Pests and Diseases, Disrupting Impact Assessment and Empowering Data-Driven Farming.
The proposal, which falls under Revealing Food Systems, aims to uncover the hidden contribution of fish to the livelihoods and food and nutrition security of over 3 billion people around the world.
ICTs for better fisheries management
“Every day, about 40 million small-scale fishers go out fishing, yet virtually none of these activities or yields are documented. This long-standing global data deficiency underpins SDG 14—Life Below Water—but can now be solved by small, mobile and affordable information and communication technologies (ICTs),” explains Alex Tilley, WorldFish Fisheries Scientist, who wrote the proposal.
“WorldFish has been trialing and adapting a digital catch documentation system built from open source software in Timor-Leste since 2016, and has recorded catch from more than 7000 small-scale fishing trips. This prototype workflow has been developed to automate data collation and management and provide summarized, easy-to-use fisheries analytics for government partners. Since February 2018, we have used Pelagic Data Systems’ solar-powered vessel tracking system to document 4500 fishing trips from 80 boats in high resolution.”
The proposed project will pilot the combination of these ICTs to develop a decision-making dashboard for fisheries managers, and use preliminary data to define models of fishing behavior from geospatial movements of boats and highlight patterns of production suitable for management of food systems. The pilot will provide proof of concept in Timor-Leste before transitioning to scale.
“Qualitative assessment of impact will be achieved through measurements of uptake and usability by different levels of government, and through integration tests with a database of catch data from previous and unrelated WorldFish projects,” Tilley continues. “We will also compare national catch statistics generated from our system with those of traditionally used FAO data, and model the growth rate and time necessary for fish production to match national development goals.”
USD 100,000 received in project funding
In addition to the award, the WorldFish proposal received USD 100,000 in project funding. The team will have 12 months to implement the pilot and can then present their results to a panel of judges in October 2019 to compete for a further USD 250,000 Scale-Up grant.
The other 2018 Inspire winners are:
CubicA: Agriculture Advisory App | Bioversity, Dalberg Data Insights & Viamo
Revealing Informal Food Flows through Free Wifi | CIAT & GSO (Vietnam)
Smart Seed Selection | CIMMYT & BioSense Institute
Use CML to Estimate Rainfalls for Agriculture | IFPRI & Cornell University
