The lecture focuses on the meaning of self-describing data, i.e. minimum metadata required. It describes the difficulties that arise analysing non-standardised data and it highlights the best practices to be used to create a seamless data treatment approach, from acquisition to interpretation. Whilst in marine sciences data policies are relatively defined, in marine robotics this is an unexplored ground. The purpose of the lecture is to stimulate a discussion and to lay out a common path to define a set of metadata and shared vocabulary for the data gathered by novel robotic platforms.

DATA POLICY AND CHALLENGES FOR MARINE ROBOTICS

Roberta Ferretti;Simona Aracri
2022

Abstract

The lecture focuses on the meaning of self-describing data, i.e. minimum metadata required. It describes the difficulties that arise analysing non-standardised data and it highlights the best practices to be used to create a seamless data treatment approach, from acquisition to interpretation. Whilst in marine sciences data policies are relatively defined, in marine robotics this is an unexplored ground. The purpose of the lecture is to stimulate a discussion and to lay out a common path to define a set of metadata and shared vocabulary for the data gathered by novel robotic platforms.
2022
FAIR data
marine robotics data
data policy
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/414420
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