reproducible research as part of the Open science movement

Még több ilyen

Internet-based Project work

Szerző: claudia rivera

A.I. - Artificial Intelligence

Szerző: Jonathan Cook

University of Oxford

Szerző: Estefanía Acevedo

Conceptions of Curriculum, Philosophical Foundations, and Curricular Designs

Szerző: Lauren Waite

reproducible research as part of the Open science movement

Practical tips

have a plan to organise, store, and make your files available

all files should be human readable

#comments in the machine readable codes

everything is a (text) file

.cvs or .txt

future-proof

document everything

session Info

R version 4.1.1 (2021-08-10)

Platform: x86_64-w64-mingw32/x64 (64-bit)

Running under: Windows 10 x64 (build 19043)

Matrix products: default

locale:

[1] LC_COLLATE=German_Austria.1252 LC_CTYPE=German_Austria.1252  LC_MONETARY=German_Austria.1252 LC_NUMERIC=C          

[5] LC_TIME=German_Austria.1252   

attached base packages:

[1] grid   stats   graphics grDevices utils   datasets methods  base   

other attached packages:

 [1] rmarkdown_2.11  gdata_2.18.0   captioner_2.2.3  gridExtra_2.3   rdrop2_0.8.2.1  data.table_1.14.2 ggridges_0.5.3  forcats_0.5.1   

 [9] stringr_1.4.0   dplyr_1.0.7    purrr_0.3.4    readr_2.0.2    tidyr_1.1.4    tibble_3.1.4   ggplot2_3.3.5   tidyverse_1.3.1  

[17] EMCluster_0.2-13 Matrix_1.3-4   MASS_7.3-54    readxl_1.3.1   rio_0.5.27    googleVis_0.6.10 usethis_2.1.3   

loaded via a namespace (and not attached):

 [1] fs_1.5.0     lubridate_1.7.10 httr_1.4.2    rprojroot_2.0.2  tools_4.1.1    backports_1.2.1  utf8_1.2.2    R6_2.5.1     

 [9] DBI_1.1.1     colorspace_2.0-2 withr_2.4.2    tidyselect_1.1.1 prettyunits_1.1.1 processx_3.5.2  curl_4.3.2    compiler_4.1.1  

[17] cli_3.0.1     rvest_1.0.1    xml2_1.3.2    desc_1.4.0    labeling_0.4.2  scales_1.1.1   callr_3.7.0    digest_0.6.28   

[25] foreign_0.8-81  pkgconfig_2.0.3  htmltools_0.5.2  dbplyr_2.1.1   fastmap_1.1.0   rlang_0.4.11   rstudioapi_0.13  farver_2.1.0   

[33] generics_0.1.0  jsonlite_1.7.2  gtools_3.9.2   zip_2.2.0     magrittr_2.0.1  Rcpp_1.0.7    munsell_0.5.0   fansi_0.5.0    

[41] lifecycle_1.0.1  stringi_1.7.4   yaml_2.2.1    pkgbuild_1.2.0  plyr_1.8.6    crayon_1.4.1   lattice_0.20-44  haven_2.4.3    

[49] hms_1.1.1     knitr_1.36    ps_1.6.0     pillar_1.6.3   codetools_0.2-18 pkgload_1.2.3   reprex_2.0.1   glue_1.4.2    

[57] evaluate_0.14   remotes_2.4.1   modelr_0.1.8   vctrs_0.3.8    tzdb_0.1.2    testthat_3.1.0  cellranger_1.1.0 gtable_0.3.0   

[65] assertthat_0.2.1 cachem_1.0.6   xfun_0.26     openxlsx_4.2.4  broom_0.7.9    memoise_2.0.0   ellipsis_0.3.2  

> 

Lab book

my example

GeoPT data interpretation

manuscript

submission to GGR

data source

software

programming language

Python

Jupyter Notebook

R

RStudio

knitr

storage

GitHub

Google Drive

Dropbox

reference manager

Zotero

open source

Citavi

subscription

collaborative writing platforms

Google Docs

Authera

Overleaf LaTeX

discovery

Google Scholar

ORCID

cornerstone of science

literature

Untertopic

books

AACH

Reproducible Research with R and RStudio

on GitHub

Zotero group

Open Science Training Handbook

What is reproducible research?

A Beginner's Guide to Conducting Reproducible Research

irreproducible research results

Nature - key reads

Nature - Reproducibility: A tragedy of errors

Nature - 1,500 scientists lift the lid on reproducibility

Schön scandal

Measles, Mumps, and Rubella (MMR) vacince and autism

measured here - reproduced everywhere

reproducible approach

raw data

data gathering

analysis

Research is considered to be reproducible when the exact results can be reproduced if given access to the original data, software, or code.

Research is considered to be reproducible when the exact results can be reproduced if given access to the original data, software, or code.

The "what" that needs to be reproduced is typically: * Actual results themselves, which includes: - Tables - Visualizations/figures/graphs - Values reported in the text * The statistical evidence in support of the findings (e.g., p-values, confidence intervals, credible intervals). * Data reduction procedures (normalisation values, corrections etc.)

Requirements for demonstrating the reproducibility There is widespread agreement that research can only be reproducible when: - The "raw" data is available, where "raw" refers to the data prior to any manipulation by the researcher (e.g., prior to any data cleaning and transformation). - A complete set of instructions is provided explaining all steps used in the processing and analyzing the data.

The entire report is written using code

That is, a file or files are provided which, when run, import the data, produce all the results, insert the results into the text of the report, and format the report.

Open/transparent

all data and materials are available

e.g. GitHub

Details about the system being used to run the analysis

libraries

software packages

specific version

Providing a set of files containing the

code

data derived tables, charts, graphics

data

classical approach

presentation

poster

pdf

talk

ppt

publication

journal

interpretation

Excel

data collection

local PC