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Introduction to Module

Standards for data represent an operational requirement for global observation network systems and are largely based around the FAIR principles. GCRMN utilises a data “tier” system, which allows for data to be compared spatially and temporally and aggregated across different resolutions important for identifying status & trend information. The data quality and resolution of taxonomy and functional groups which provides a framework for integrating data across the network.

Building on knowledge within a monitoring institution and across an observation network allows for clear documentation on how data are collected, standardised and aggregated. There are a number of tools for Knowledge Management and collaborative research which facilitate the production of reproducible research. Coding in R and the use of git and Github provide useful support for routine documentation and version control for data management and communication.

This module highlights core elements of the GCRMN Data Standards and Reproducible research. Please watch this short introductory video for the module for more detail on what is to be covered in this training session:

Video instruction

Next steps

We will now go into more detail for GCRMN data standards and reproducible research.