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TAF User Guidelines

Introduction

Aim

The Transparent Assessment Framework (TAF) is a framework to organize data, methods, and results used in ICES assessments, so they are easy to find and rerun later with new data.

It will provide an online archive of final assessment for each year, for all stock categories. All data input and outputs are linked to existing or upcoming ICES data services.

Websites

URL Purpose
taf.ices.dk Main landing page
doc Documentation
wiki Wiki
ices-taf Assessments and other analyses
diagrams Introductory diagrams
tutorial Tutorial: Simple assessment
github_guidelines ICES GitHub

Packages

Package Links
icesTAF CRAN homepage and help pages
TAF CRAN homepage and help pages
ICES pkgs GitHub repositories and release history

General Principles

The TAF stock assessment workflow is scripted in a series of R scripts.

Core scripts Purpose
data.R preprocess data, write TAF data tables
model.R run analysis, write model results
output.R extract results of interest, write TAF output tables

Optional scripts include report.R (prepare plots and tables for the report) and utilities.R (custom functions used in the above scripts).

If a script becomes long, it is recommended to split it into separate scripts with the same filename prefix, e.g. report_plots.R and report_tables.R, where a main report.R script can simply source the underlying scripts:

source("report_plots.R")
source("report_tables.R")

TAF Data Flow

The TAF data presentation describes the flow of data from boot/initial/data to boot/data and finally to data.

TAF Data Format

CSV Files

Units

Tonnes, thousands of individuals

Boot procedure

Initial folder

The boot/initial folder contains the initial data and software that are not available online from another repository. These files are the basis of all subsequent analysis, and guarantee that the TAF analysis can be rerun later and will reproduce the original results, even if data in the underlying databases (outside of TAF) may have changed after the original analysis was submitted.

One objective of TAF is to document the data preparation. Therefore, the initial data files should represent the original data before the main preprocessing and data aggregation takes place. For example, the initial data could be the result of an SQL database query, selecting one species of interest and all relevant data columns for the analysis.

When using software that is not available online from another repository, boot/initial/software contains the model source and executable. A Windows executable is required, while Linux and macOS executables are optional.

Metadata

See taf.boot and process.bib in:

https://cran.r-project.org/web/packages/TAF/TAF.pdf

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