NEON EDUCATION bio photo

NEON EDUCATION

Devoted to open data and open source in science and education.

View All Tutorials

Tags

R programming (56)
Hierarchical Data Formats (HDF5) (15)
Spatial Data & GIS (22)
LiDAR (10)
Raster Data (14)
Remote Sensing (25)
Data Visualization (4)
Hyperspectral Remote Sensing (18)
Time Series (17)
Phenology (8)
Vector Data (6)
Metadata (1)
Git & GitHub (7)
(1) (1) (14) (1) (1) (1) (1)

Tutorial by R Package

dplyr (9)
ggplot2 (18)
h5py (2)
lubridate (time series) (7)
maps (1)
maptools (1)
plyr (2)
raster (26)
rasterVis (raster time series) (3)
rgdal (GIS) (24)
rgeos (2)
rhdf5 (11)
sp (5)
scales (4)
gridExtra (4)
ggtheme (0)
grid (2)
reshape2 (3)
plotly (5)

View ALL Tutorial Series




Twitter Youtube Github


Blog.Roll

R Bloggers

Overview

Verifiability and reproducibility are among the cornerstones of the scientific process. They are what allows scientists to “stand on the shoulder of giants”. Maintaining reproducibility requires that all data management, analysis, and visualization steps behind the results presented in a paper are documented and available in full detail. Reproducibility here means that someone else should either be able to obtain the same results given all the documented inputs and the published instructions for processing them, or if not, the reasons why should be apparent. From Reproducible Science Curriculum

Learning Objectives

At the end of this activity, you will be able to:

  • Summarize the four facets of reproducibility.
  • Describe several ways that reproducible workflows can improve your workflow and research.
  • Explain several ways you can incorporate reproducible science techniques into your own research.

Getting Started with Reproducible Science

Please view the online slide-show below which summarizes concepts taught in the Reproducible Science Curriculum.

View Reproducible Science Slideshow

A Gap In Understanding

Obstacles slowing adoption of reproducible science practices. Source: Reproducible Science Curriculum

Reproducibility and Your Research

Reproducibility spectrum for published research. Source: Peng, RD Reproducible Research in Computational Science Science (2011): 1226–1227 via Reproducible Science Curriculum

How reproducible is your current research?

View Reproducible Science Checklist

Thought Questions: Have a look at the reproducible science check list linked, above and answer the following questions:

  • Do you currently apply any of the items in the checklist to your research?
  • Are there elements in the list that you are interested in incorporating into your workflow? If so, which ones?

Additional Readings (optional)

  • Nature has collated and published (with open-access) a special archive on the Challenges of Irreproducible Science .
  • The Nature Publishing group has also created a Reporting Checklist for its authors that focuses primaily on reporting issues but also includes sections for sharing code.
  • Recent open-access issue of Ecography focusing on reproducible ecology and software packages available for use.