Context

Column

Data Colletion Framework

Source: STECF 2019

Source: STECF 2019

Column

Annual Economic Report

Source: Carvalho et al. 2018

Source: Carvalho et al. 2018

Motivation

Introduction

Column

Dashboard

Source: Pearson Scott Foresman - Archives of Pearson Scott Foresman, donated to the Wikimedia Foundation

Source: Pearson Scott Foresman - Archives of Pearson Scott Foresman, donated to the Wikimedia Foundation

Reproducable Workflow

Source: Wickham and Grolemund (2017)

Source: Wickham and Grolemund (2017)

R Markdown

Examples

Column

DataTable

datatable(iris)

Modified Tabular Data

ggplot2: Income

Themes: bbplot

Source: BBC, 2019

Source: BBC, 2019

Spatial

Column

Overview

Spatial Example with fish catches data

Data:

  • Fish catches reported by Finnish trawlers in 2017
  • ICES (International Council for the Exploration of the Seas) statistical rectangles

There needs to be a link-variable to merge the data with spatial information

Packages:

  • sf for reading and linking data with geographic information
  • mapview provides funtions to create interacitve maps with spatial data

Estimating the value

  • The value of cathces can be estimated by multiplying with fish prices by species

Notes:

After linking the catch data and statistical rectangles creating dynamic maps is easy

mapview(fish_data, zcol = ‘mapping variable’)

Landings by species

Value of Landings by species

Discussion

Column

Preliminary Findings

R provides efficient tools for

  • data manipulation
  • statistical computing
  • graphics
  • communication

R Markdown workflow is

  • Dynamic: one document for code and report
  • Reproducable: output is always produced from the source code
  • Portable: enables large number of final outputs
  • Compact: brings closer the analysis and reporting of results

Some useful packages:

  • flexdashboard: R Markdown Format for Flexible Dashboards
  • ggplot2: Elegant Data Visualisations Using the Grammar of Graphics
  • DT: A Wrapper of the JavaScript Library ‘DataTables’
  • mapview: provides functions to create interactive visualisations of spatial data

Future Work

  • Clarify the needs for data validation and reporting
  • Consistency: internal r package
  • Data sources and integration: EconomyDoctor and Px-Web

References

BBC (2019). bbplot. GitHub repository, https://github.com/bbc/bbplot

Carvalho, N., Keatinge, M. and Gullen, J. (2018). The 2018 Annual Economic Report on the EU Fishing Fleet. [ebook] Publications Office of the European Union. Available at: http://publications.jrc.ec.europa.eu/repository/bitstream/JRC112940/kj-ax-18-007-en-n.pdf

Scientific, Technical and Economic Committee for Fisheries (STECF) (2019). STECF - European Commission. https://stecf.jrc.ec.europa.eu/.

Wickham, H., and Grolemund, G. (2017). R for Data Science. http://r4ds.had.co.nz/.