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Context

The origins of this course have come from the need to build capacity in the regional nodes of the GCRMN and facilitate data integration at regional and global levels. A workshop for the Eastern Tropical Pacific region in February 2019 provided an opportunity for early career researchers from the region to learn the basic working of the regional data repository and techniques for data standardisation, linking, and visualisation. This course is largely based on this experience.

The data cleaning, standardisation, analysis and visualisation is based on the R statistical language, as it provides broad functionality for data management and quality assurance but also includes analytical tools, mapping and visualisation. Mastering R can be a lifelong commitment and it is unrealistic to expect that a short course can cover all aspects of R.

Instead, this course focuses on teaching a set of core skills related to data standardisation, linking to external data, and visualisation relevant to routine coral reef monitoring. As GCRMN serves as a global observation network, the course also aims to provide competency in data standards, documentation, and introduction to tools for conducting reproducible research.

This wiki page provides an overview of the core competencies to be delivered as part of this course and a description of the general approach.

Core Competencies

The core competencies and skills to have upon completing the course include:

  1. Knowledge of GCRMN data standards, links with other global observation and reporting systems, FAIR principles (Findable, Accessible, Interoperable, Reusable).
  2. Setting up of a data repository for ‘reproducible research’, including version control, project documentation and distributed collaboration using git and github
  3. Techniques for data standardisation, quality assurance and quality control (based on dplyr, tidyr and other packages from the tidyverse)
  4. Competence in visualisation of timeseries trends for site level and aggregate data, including techniques for representing spatial and temporal variation (based on ggplot and complimentary packages)
  5. Techniques for mapping and spatial representation of coral reef monitoring data, including GCRMN standards for geographic coordinates, projections for regional mapping and data representation (based on sp, raster and sf packages)
  6. Competence in linking data to project documentation, reporting and creation of dissemination materials using rmarkdown and wiki pages in github
  7. Linking of coral reef monitoring data with additional variables (e.g. environmental, socio-economic data, fisheries data) from remote online sources, including data retrieval from global data platforms such as Fishbase, IUCN Redlist, GBIF.

In order to deliver on these skills, this wiki page provides an overview of the basic core structure and planned presentation of information and exercises.

Basic Approach

In this wiki, each course module consists of a few pages of introductory material and context for the module, examples of version control, documentation and coding followed by examples with coral reef monitoring data. These examples will be linked to code and example data contained within this repository.

The introductory material and examples will be followed by a set of Homework examples for participants to apply the learned skills to working examples. This could be done on data supplied by CORDIO or by working with own data sets. The anticipation of the Homework is that course participants will be able to accomplish this within 2-3 hours outside of the formal course sessions.

Video Instruction

Next steps

With a better understanding of how monitoring coral reef ecosystems fit into global and regional management and reporting frameworks, let’s go to the first module on data standards.