Domino Effects of Cumulative Bias and Erroneous Data in Fisheries Big-Data Mapping Models - Case Study of GFW View on Transshipments - FishSpektrum

This report discusses the threat of erroneous data available to MCS practitioners which can in turn lead to poor decision making, loss of credibility and potentially the loss of independent and worthy technological projects.

The authors of the report emphasise the need for accurate, reliable data and reporting with scrutiny from peers to prove rigorous analysis.