ethord

https://github.com/global-health-engineering/ethord

Repository

README.Rmd

---
output: github_document
always_allow_html: true
editor_options:
  markdown:
    wrap: 72
  chunk_output_type: console
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%",
  message = FALSE,
  warning = FALSE,
  fig.retina = 2,
  fig.align = 'center'
)

library(desc)
library(dplyr)
library(readr)
library(gt)
library(kableExtra)
library(fontawesome)
library(stringr)

# --- Define a list of package names ---
package_names <- list.files("inst/extdata", pattern = "\\.csv$", full.names = FALSE)
package_names <- basename(package_names) # Get just the base names
package_names <- package_names[!package_names %in% "dictionary.csv"]
package_names <- stringr::str_remove(package_names, "\\.csv$") # Remove .csv extension


organisation <- desc::desc_get_field("Organisation") # Assuming you have an 'Organisation' field in DESCRIPTION
browser_favicon_colour <- "lightblue"
```

# `r desc::desc_get_field("Package")`

***`r desc::desc_get_field("Title")`***



[![License: CC BY
4.0](https://img.shields.io/badge/License-CC_BY_4.0-lightgrey.svg)](https://creativecommons.org/licenses/by/4.0/)

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.16563064.svg)](https://zenodo.org/doi/10.5281/zenodo.16563064)



-----

## Installation

You can install the development version of `r desc::desc_get_field("Package")` from GitHub `r fontawesome::fa("github")` with:

```r
devtools::install_github("`r organisation`/`r desc::desc_get_field("Package")`", dependencies = TRUE)
```

-----

## Example Usage

Here's a quick example showing how to visualize the Open Research Data Program data:

```{r example-plot, fig.height=6, fig.width=10}
library(ethord)
library(ggplot2)
library(ggthemes)
library(dplyr)

portal |> 
  mutate(category = case_when(
    category == "Contribute" ~ "Contribute (30k)",
    category == "Explore" ~ "Explore (150k)",
    category == "Establish" ~ "Establish (1.5m)"
  )) |>
  mutate(category = factor(category, 
                                levels = c("Contribute (30k)", 
                                           "Explore (150k)", 
                                           "Establish (1.5m)"))) |>
  count(institutions, category) |> 
    mutate(institutions = str_wrap(institutions, width = 30)) |>
  ggplot(aes(x = reorder(institutions, n), 
             y = n,
             fill = category)) +
  geom_col(position = "dodge") +
  geom_label(aes(label = n),
             position = position_dodge(width = 0.9),
             show.legend = FALSE,
             color = "white",
             fontface = "bold",
             size = 3) +
  coord_flip() +
  labs(
    title = "Open Research Data Program of the ETH Board",
    subtitle = "Number of funded projects per institution and project category",
    y = "Number of projects",
    x = NULL,
    fill ="Project category:"
  ) +
  scale_fill_colorblind() +
  statR::theme_stat(base_size = 10) +
  theme(panel.grid.major.y = element_blank(),
        axis.text.y = element_text(size = 8))
```

-----

### Download as CSV Files

If you prefer to work with the data outside of R, you can download individual datasets as CSV files.

1.  **Right-click** on the "Download CSV" link for the dataset you want.
2.  Select **"Save Link As"** [`r fontawesome::fa("chrome", fill = browser_favicon_colour)`](https://www.google.com/chrome/) [`r fontawesome::fa("edge", fill = browser_favicon_colour)`](https://www.microsoft.com/edge/) [`r fontawesome::fa("firefox", fill = browser_favicon_colour)`](https://www.mozilla.org/firefox/) or **"Download Linked File"** [`r fontawesome::fa("safari", fill = browser_favicon_colour)`](https://www.apple.com/safari/).
3.  Choose where you'd like to save the file on your computer.

```{r, echo=FALSE, message=FALSE, warning=FALSE}
extdata_path <- paste0(desc::desc_get_field("URL"), "/raw/main/inst/extdata/")

readr::read_csv("data-raw/dictionary.csv") |>
  dplyr::distinct(file_name) |>
  dplyr::mutate(file_name = stringr::str_remove(file_name, "\\.rda$")) |> # Ensure .rda is removed
  dplyr::rename(dataset = file_name) |>
  dplyr::mutate(
    CSV = paste0("[Download CSV](", extdata_path, dataset, ".csv)")
  ) |>
  knitr::kable()

```

## Data

```r
library(`r desc::desc_get_field("Package")`)
```

```{r, echo=FALSE, results='asis', message=FALSE, warning=FALSE}
# Iterate through each package name and generate content
for (pkg_name in package_names) {
  cat("\n---\n\n") # Separator for each dataset

  # Conditionally load data if it's not already in the environment
  # Assuming 'pkg_name' is also the name of the dataset object once loaded
  if (!exists(pkg_name)) {
    data(list = pkg_name, package = desc::desc_get_field("Package"))
  }

  current_data <- get(pkg_name)

  cat(paste0("### ", pkg_name, "\n\n"))
  cat(paste0("The dataset `", pkg_name, "` has `", nrow(current_data), "` observations and `", ncol(current_data), "` variables\n\n"))

  # Display head of the dataframe using gt
  cat("```r\n")
  cat(paste0("get(\"", pkg_name, "\") |> \n"))
  cat("  head(3) |> \n")
  cat("  gt::gt() |> \n")
  cat("  gt::as_raw_html()\n")
  cat("```\n\n")

  # Render the gt table in the Rmd output
  print(
    current_data |>
      head(3) |>
      dplyr::mutate(
        across(where(is.character), ~ stringr::str_trunc(., width = 50, ellipsis = "..."))
      ) |> 
      gt::gt() |>
      gt::as_raw_html()
  )

  cat("\n\n") # Newlines for spacing

  # Overview of variable names
  cat("For an overview of the variable names, see the following table.\n\n")
  
  # Filter dictionary for the current dataset
  dictionary_table <- readr::read_csv("data-raw/dictionary.csv") |>
    dplyr::filter(file_name == paste0(pkg_name, ".rda")) |> # Ensure matching .rda
    dplyr::select(variable_name:description)

  if (nrow(dictionary_table) > 0) {
    print(
      dictionary_table |>
        knitr::kable(booktabs = TRUE) |>
        kableExtra::kable_styling(
          full_width = FALSE,
          bootstrap_options = c("striped"),
          position = "center"
        )
    )
  } else {
    cat("No dictionary entry found for this dataset.\n\n")
  }
}
```

## License

Data are available as
[CC-BY](https://github.com/`r desc::desc_get_field("Organisation")`/`r desc::desc_get_field("Package")`/blob/main/LICENSE.md).

## Citation

```{r, echo=FALSE, message=FALSE, warning=FALSE}
citation(desc::desc_get_field("Package"))
```

Owner

Citation (CITATION.cff)

# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "ethord" in publications use:'
type: software
license: CC-BY-4.0
title: 'ethord: ETH Board Open Research Data (ORD) Program Project Metadata and Report
  Data'
version: 0.0.3
doi: 10.5281/zenodo.16563064
abstract: This data package contains metadata and report data from 96 research projects
  funded by the joint Open Research Data (ORD) program of ETH Zurich, EPFL, and the
  four research institutes of the ETH Domain. The package includes project-level metadata,
  such as project titles, descriptions, and categorizations (Establish, Explore, Contribute),
  as well as data extracted from reports submitted by each project, providing insights
  into the projects' objectives, methods, outcomes, and impacts.
authors:
- family-names: Massari
  given-names: Nicolo
  email: nmassari@ethz.ch
  orcid: https://orcid.org/0009-0006-8421-930X
- family-names: Schöbitz
  given-names: Lars
  email: lschoebitz@ethz.ch
  orcid: https://orcid.org/0000-0003-2196-5015
- family-names: Tilley
  given-names: Elizabeth
  email: tilleye@ethz.ch
  orcid: https://orcid.org/0000-0002-2095-9724
repository-code: https://github.com/Global-Health-Engineering/ethord
url: https://github.com/Global-Health-Engineering/ethord
date-released: '2025-07-28'
contact:
- family-names: Massari
  given-names: Nicolo
  email: nmassari@ethz.ch
  orcid: https://orcid.org/0009-0006-8421-930X

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