Peskas: Automated analytics for small-scale, data-deficient fisheries
| cg.contributor.affiliation | WorldFish | en_US |
| cg.contributor.affiliation | University of East Anglia, School of International Development | en_US |
| cg.contributor.donor | Foreign, Commonwealth & Development Office United Kingdom (Department for International Development United Kingdom) | en_US |
| cg.contributor.donor | The Minderoo Foundation | en_US |
| cg.contributor.donor | CGIAR Trust Fund | en_US |
| cg.contributor.initiative | Aquatic Foods | en_US |
| cg.coverage.country | Kenya | en_US |
| cg.coverage.country | Malawi | en_US |
| cg.coverage.country | Mozambique | en_US |
| cg.coverage.country | United Republic of Tanzania | en_US |
| cg.coverage.country | Timor-Leste | en_US |
| cg.coverage.iso3166-alpha2 | KE | en_US |
| cg.coverage.iso3166-alpha2 | MW | en_US |
| cg.coverage.iso3166-alpha2 | MZ | en_US |
| cg.coverage.iso3166-alpha2 | TZ | en_US |
| cg.coverage.iso3166-alpha2 | TL | en_US |
| cg.coverage.region | Eastern Africa | en_US |
| cg.coverage.region | South-Eastern Asia | en_US |
| cg.creator.identifier | Tilley, Alexander: 0000-0002-6363-0945 | en_US |
| cg.identifier.doi | https://doi.org/10.1016/j.softx.2024.102028 | en_US |
| cg.isijournal | ISI Journal | en_US |
| cg.issn | 2352-7110 | en_US |
| cg.journal | SoftwareX | en_US |
| cg.reviewStatus | Peer Review | en_US |
| cg.subject.actionArea | Resilient Agrifood Systems | en_US |
| cg.volume | 29 | en_US |
| dc.contributor.author | Longobardi, Lorenzo | en_US |
| dc.contributor.author | Sozinho, Villiam | en_US |
| dc.contributor.author | Altarturi, Hamza | en_US |
| dc.contributor.author | Cagua, E. Fernando | en_US |
| dc.contributor.author | Tilley, Alexander | en_US |
| dc.date.accessioned | 2025-01-06T13:36:19Z | en_US |
| dc.date.available | 2025-01-06T13:36:19Z | en_US |
| dc.identifier.uri | https://hdl.handle.net/10568/168549 | en_US |
| dc.title | Peskas: Automated analytics for small-scale, data-deficient fisheries | en_US |
| dcterms.abstract | Small-scale fisheries account for almost 90 % of global fisheries employment and are responsible for landing >40 % of the world's fish catch. Yet their importance to livelihoods and food and nutrition security in Least Developed Countries are only recently emerging due to the logistical, financial, and capacity challenges of gathering and interpreting data in this diverse, dispersed and informal sector. Peskas was designed as a low-cost solution to tackle this problem, providing a template workflow for ingestion and analysis to a decision dashboard, which can be adapted to different contexts and needs. | en_US |
| dcterms.accessRights | Open Access | en_US |
| dcterms.available | 2024-12-30 | en_US |
| dcterms.bibliographicCitation | Lorenzo Longobardi, Villiam Sozinho, Hamza Altarturi, E. Fernando Cagua, Alexander Tilley. (30/12/2024). Peskas: Automated analytics for small-scale, data-deficient fisheries. SoftwareX, 29. | en_US |
| dcterms.format | en_US | |
| dcterms.issued | 2025-02 | en_US |
| dcterms.language | en | en_US |
| dcterms.license | CC-BY-NC-4.0 | en_US |
| dcterms.publisher | Elsevier | en_US |
| dcterms.subject | small-scale fisheries | en_US |
| dcterms.subject | stock assessment | en_US |
| dcterms.subject | iuu fishing | en_US |
| dcterms.subject | fish | en_US |
| dcterms.subject | dashboard | en_US |
| dcterms.subject | near-real-time | en_US |
| dcterms.type | Journal Article | en_US |