# peskas.kenya.data.pipeline
The goal of peskas.kenya.data.pipeline is to implement, deploy, and
execute the data and modelling pipelines that underpin Peskas in Kenya,
a partnership between WorldFish and
Wildlife Conservation Society as part of the Asia-Africa Bluetech Superhighway project funded by the FCDO of the UK Government.
## The pipeline is an R package
peskas.kenya.data.pipeline is structured as an R package because it
makes it easier to write production-grade software. Specifically,
structuring the code as an R package allows us to:
- better handle system and package dependencies,
- forces us to split the code into functions,
- makes it easier to document the code, and
- makes it easier to test the code
We make heavy use of tidyverse style
conventions and the
usethis package to automate tasks during
project setup and deployment.
For more information about the rationale of structuring the pipeline as
a package check Chapter
3
in *Engineering Production-Grade Shiny
Apps*. The book is focused on Shiny
applications but the rationale also applies to data pipelines and
production-ready code in general.
## How the pipeline works
The pipeline is composed of different modules:
1. Data Collection: On site fishing landing surveys and continuous,
solar-powered GPS vessel trackers to collect and send data in near
real-time, alongside fishery metadata for a thorough data-gathering
process.
2. Pre-processing: Data formatting, shaping, and standardisation to
prepare the raw data for analysis.
3. Validation: Outlier detection and error identification, and includes
an alert system to maintain data quality.
4. Analytics: Modelling fisheries indicators, nutritional
characterization, and data mining to extract valuable insights.
5. Data export: Automated dissemination of processed and analysed
fisheries data to ensure accessibility and comprehension. This
involves restructuring data for dashboard integration and open
publication.
6. isualisation: Too …