Most science is not reproducible or repeatable, even within the same lab group over time.

A reproducibility crisis

The scientific workflow

Instructions for preparation of the Biographical Sketch have been revised to rename the "Publications" section to "Products" and amend terminology and instructions accordingly. This change makes clear that products may include, but are not limited to, publications, data sets, software, patents, and copyrights.

PLOS Data Policy

the Data Policy states the ‘minimal dataset’ consists “of the dataset used to reach the conclusions drawn in the manuscript with related metadata and methods, and any additional data required to replicate the reported study findings in their entirety. This does not mean that authors must submit all data collected as part of the research, but that they must provide the data that are relevant to the specific analysis presented in the paper.

Access all available ecological data

Liberating 400+ million observation records
Full text 100k articles
Data from papers in > 200 journals

Accessing data behind papers - dryad

library(rdryad)
dryaddat <- download_url("10255/dryad.1759")
# Get a file given the URL
file <- dryad_getfile(dryaddat)
dim(file)

## [1] 131  30

Biodiversity records from museums

library(ecoengine)
pinus_data <- ee_observations(genus = "Pinus", georeferenced = TRUE, page = 1:25)
nrow(pinus_data$data)
# [1] 625

Get complete and current taxonomic records

classification(c("Helianthus annuus"), db = "ncbi")

## $`Helianthus annuus`
##                    name         rank
## 1    cellular organisms      no rank
## 2             Eukaryota superkingdom
## 3         Viridiplantae      kingdom
## 4          Streptophyta       phylum
## 5        Streptophytina      no rank
## 6           Embryophyta      no rank
## 7          Tracheophyta      no rank
## 8         Euphyllophyta      no rank
## 9         Spermatophyta      no rank
## 10        Magnoliophyta      no rank
## 11      Mesangiospermae      no rank
## 12       eudicotyledons      no rank
## 13           Gunneridae      no rank
## 14         Pentapetalae      no rank
## 15             asterids     subclass
## 16          campanulids      no rank
## 17            Asterales        order
## 18           Asteraceae       family
## 19          Asteroideae    subfamily
## 20 Heliantheae alliance      no rank
## 21          Heliantheae        tribe
## 22           Helianthus        genus
## 23    Helianthus annuus      species
## 
## attr(,"class")
## [1] "classification"
## attr(,"db")
## [1] "ncbi"

World Bank climate knowledge portal rWBclimate

library(rWBclimate)
eu_basin <- create_map_df(Eur_basin)
eu_basin_dat <- get_ensemble_temp(Eur_basin, "annualanom", 2080, 2100)

Taxon specific databases - AntWeb

library(AntWeb)
acd <- aw_data(genus = "acanthognathus")
aw_map(acd)

Sharing data - (figshare)

library(rfigshare)
id <- fs_create("Fisheries dataset", "A dataset containing catch for 4 important commerical fish species",
    "dataset")
fs_upload(id, "dat.csv")

A reproducible workflow (in R)

Load your own data
	
load all raw untransformed data.

Acquire additional data from the web

e.g. resolve taxonomic names, acquire additional datasets.

Document everything with metadata

The EML package makes it really easy to add valid EML to your data

Submit to a persistent repository

Share your data by submitting to figshare or one at your institution


Generate interactive maps, viewers.

The scientific workflow

The open scientific workflow