_jct_overview.qmd

---
title: "Hybrid Open Access Dashboard"
subtitle: "How open are hybrid journals in transformative agreements? You can analyse progress made over time by open license, publisher and country. You can also monitor the availability of publisher-provided metadata in Crossref."
execute:
  echo: false
  warnings: false
  message: false
sidebar: true
aliases:
  - jct.html
params:
  - download_path: NULL
---

<!-- Required R packages -->

```{r setup}
#| echo: false
#| message: false
source("R/setup.R")
source("R/utils.R")
```

<!-- data preparation -->

```{r data prep}
#| echo: false
#| message: false
jn_ind_df <- hoaddata::jn_ind |>
dplyr::mutate(cr_year = as.character(cr_year)) |>
  dplyr::mutate(cc = factor(
    cc,
    # Order by permissiveness
    levels = c(
      "CC BY",
      "CC BY-SA",
      "CC BY-NC",
      "CC BY-NC-SA",
      "CC BY-ND",
      "CC BY-NC-ND"
    ))) |>
    # only JCT journals
    filter(issn_l %in% hoaddata::jct_hybrid_jns$issn_l)

jn_aff_df <- hoaddata::jn_aff |>
dplyr::mutate(cr_year = as.character(cr_year)) |>
  dplyr::mutate(cc = factor(
    cc,
    # Order by permissiveness
    levels = c(
      "CC BY",
      "CC BY-SA",
      "CC BY-NC",
      "CC BY-NC-SA",
      "CC BY-ND",
      "CC BY-NC-ND"
    ))) |>
    # only JCT journals
    filter(issn_l %in% hoaddata::jct_hybrid_jns$issn_l)
```


<!-- Teaser -->

The share of Open Access articles with a Creative Commons license in `r format(length(unique(jn_ind_df$issn_l)), big.mark = ",")` hybrid journals derived from [cOAlition S Transformative Agreement Public Data](https://journalcheckertool.org/transformative-agreements/) is as follows:


```{r teaser}
#| echo: false
#| message: false
#| warning: false
#| results: asis
source("R/teaser.R")
basic_stat(jn_ind_df = jn_ind_df, jn_aff_df = jn_aff_df)
```

<small><sup>*</sup>Journal articles from lead authors based in Germany. Country affiliation data derived from OpenAlex.</small>

<!-- Creative Commons license prevalence-->

## Creative Commons licenses over time

Percentage of Open Access in hybrid journals included in transformative agreements by Creative Commons license types as provided by Crossref.

```{r cc_over_year_data}
#| echo: false
#| message: false
#| warning: false
source("R/cc_over_year.R")
```


::: {.panel-tabset}

## Global

```{r cc_global_plot, message=FALSE}
cc_df <- cc_ind_global(jn_ind_df = jn_ind_df)
cc_global_plot <- plot_cc_variants_by_year(cc_df = cc_df)
# Return SVG
girafe(
  ggobj = cc_global_plot,
  width_svg = 9,
  height_svg = 6 * 0.618,
 options = list(opts_tooltip(
    css="background-color:white;
;font-size:1.15em;padding:10px;border-radius:5px;box-shadow: 0 0 10px 0 rgba(0, 0, 0, 0.5)",
    opacity = .95),
    opts_toolbar(saveaspng = FALSE)))

export_files(.data = cc_df, .plot = cc_global_plot, width = 9, height = 6 * 0.618)
```


## Germany<sup>*</sup>

```{r cc_de_plot, message=FALSE}
cc_df <- cc_ind_de(jn_aff_df = jn_aff_df)
cc_de_plot <- plot_cc_variants_by_year(cc_df = cc_df)
# Return SVG
girafe(
  ggobj = cc_de_plot,
  width_svg = 9,
  height_svg = 6 * 0.618,
 options = list(opts_tooltip(
    css="background-color:white;
;font-size:1.15em;padding:10px;border-radius:5px;box-shadow: 0 0 10px 0 rgba(0, 0, 0, 0.5)",
    opacity = .95),
    opts_toolbar(saveaspng = FALSE)))

export_files(.data = cc_df, .plot = cc_de_plot, width = 9, height = 6 * 0.618)
```

<small><sup>*</sup>Journal articles from lead authors based in Germany. Country affiliation data derived from OpenAlex.</small>

:::

### Creative Commons licenses over time by publisher

Percentage of Open Access in hybrid journals included in transformative agreements by Creative Commons license types and Top 13 publishers in terms of total Open Access articles published in these journals between 2017 and 2024.

```{r}
#| echo: false
#| message: false
#| warning: false
# Data prep
source("R/data_prep.R")
```

::: panel-tabset

## Global

```{r publisher_cc}
#| echo: false
#| message: false
#| warning: false
source("R/publisher_cc.R")

top_13_global <- top_13_plot("global")
# Return SVG
girafe(
  ggobj = top_13_global ,
  width_svg = 9,
  height_svg = 10 * 0.618,
 options = list(opts_tooltip(
    css="background-color:white;
;font-size:1.15em;padding:10px;border-radius:5px;box-shadow: 0 0 10px 0 rgba(0, 0, 0, 0.5)",
    opacity = .95),
    opts_toolbar(saveaspng = FALSE)))

export_files(
    .data = top_13_global$data,
    .plot = top_13_global,
    width = 9,
    height = 10 * 0.618,
    .drops = c("tooltip_group", "publisher_fct"))
```

## Germany<sup>*</sup>

```{r publisher_cc_de}
#| echo: false
#| message: false
#| warning: false

top_13_de <- top_13_plot("de")

# Return SVG
girafe(
  ggobj = top_13_de,
  width_svg = 9,
  height_svg = 10 * 0.618,
 options = list(opts_tooltip(
    css="background-color:white;
;font-size:1.15em;padding:10px;border-radius:5px;box-shadow: 0 0 10px 0 rgba(0, 0, 0, 0.5)",
    opacity = .95),
    opts_toolbar(saveaspng = FALSE)))

export_files(
    .data = top_13_de$data,
    .plot = top_13_de,
    width = 9,
    height = 10 * 0.618,
    .drops = c("tooltip_group", "publisher_fct"))
```

<small><sup>*</sup>Journal articles from lead authors based in Germany. Country affiliation data derived from OpenAlex.</small>

:::

## Publishing market

### Publishing market over time

Hybrid journal publisher portfolio analysis, showing publishing market shares in terms of total and Open Access article volume. Dashed lines represent median OA percentage (red) and median publication output (orange). Note that only hybrid journals included in transformative agreements are shown.


```{r}
#| echo: false
#| message: false
#| warning: false
# Data prep
source("R/data_prep.R")
my_df <- summarize_pubs(var_summary = c(cr_year, esac_publisher)) |>
  tidyr::complete(cr_year, esac_publisher, collection) |>
  mutate_if(is.numeric, ~ replace(., is.na(.), 0)) |>
  mutate(pub_col =  "#999999")
```

::: {.panel-tabset}

```{r}
#| echo: false
#| message: false
#| warning: false
source("R/pub_scatter.R")
```

## Global

```{r publishing_market_global}
#| echo: false
#| message: false
#| warning: false
plot_scatterplot(my_df, collection = "global")
# Export
my_df |>
  dplyr::filter(collection == "global") |>
  mutate(oa_prop = oa_articles / articles) |>
  export_files(.drop = c("pub_col"))
```
  
## Germany<sup>*</sup>

```{r publishing_market_de}
#| echo: false
#| message: false
#| warning: false
plot_scatterplot(my_df, collection = "de")
# Export

my_df |>
  dplyr::filter(collection == "de") |>
  mutate(oa_prop = oa_articles / articles) |>
  export_files(.drop = c("pub_col"))
```

<small><sup>*</sup>Journal articles from lead authors based in Germany. Country affiliation data derived from OpenAlex.</small>

:::

### Market shares

Publisher market shares as measured by articles published between 2017 and 2024 in hybrid journals included in transformative agreements.

```{r}
#| echo: FALSE
source("R/publisher_market_share.R")
```

::: panel-tabset

## Global

```{r market_shares}
# Return SVG
market_shares_global <- plot_pub_shares(.cat = "global")

girafe(
  ggobj = market_shares_global,
  width_svg = 6,
  height_svg = 5 * 0.618,
 options = list(opts_tooltip(
    css="background-color:white;
;font-size:1.15em;padding:10px;border-radius:5px;box-shadow: 0 0 10px 0 rgba(0, 0, 0, 0.5)",
    opacity = .95),
    opts_toolbar(saveaspng = FALSE)))

export_files(
    .data = market_shares_global$data,
    .plot = market_shares_global,
    width = 6,
    height = 5 * 0.618,
    .drops = c("my_tooltip"))
```

## Germany<sup>*</sup>

```{r market_shares_de}
# Return SVG
market_shares_de <- plot_pub_shares(.cat = "de")

girafe(
  ggobj = market_shares_de,
  width_svg = 6,
  height_svg = 5 * 0.618,
 options = list(opts_tooltip(
    css="background-color:white;
;font-size:1.15em;padding:10px;border-radius:5px;box-shadow: 0 0 10px 0 rgba(0, 0, 0, 0.5)",
    opacity = .95),
    opts_toolbar(saveaspng = FALSE)))

export_files(
    .data = market_shares_de$data,
    .plot = market_shares_de,
    width = 6,
    height = 5 * 0.618,
    .drops = c("my_tooltip"))
```

<small><sup>*</sup>Journal articles from lead authors based in Germany. Country affiliation data derived from OpenAlex.</small>

:::

### Publisher league: Hybrid Open Access output

This interactive table highlights the output of hybrid Open Access publishers by year, sorted by total annual publication volume. It shows the number and proportion of Open Access articles made available under a Creative Commons licence in hybrid journals included in transformative agreements. The table also shows the number of hybrid journals per portfolio and the corresponding percentage of hybrid journals with at least one OA article. You can filter by publisher, publication year and between a global and a country-specific view with respect to lead author publications from Germany.

::: column-body-outset

```{r publisher_league}
#| echo: false
#| message: false
#| warning: false
source("R/publisher_league.R")
# Prepare data
table_df <- publisher_league_data_prep()

# Crosstalk init
shared_publisher_df <- SharedData$new(table_df)

# React table
g <- publisher_league_reactable(shared_publisher_df, .collection = "jct")

htmltools::div(
  class = "agreement-tbl",
  # filters,
  htmltools::div(class = "filters",
                 htmltools::div(
                   class = "filter-input",
                   filter_select(
                     "filter_publisher",
                     "Search publisher",
                     shared_publisher_df,
                     ~ esac_publisher,
                     multiple = TRUE
                   )
                 ),
    htmltools::div(
      class = "filter-input",
      filter_select(
        "filter_year",
        "Publication Year",
        shared_publisher_df,
        ~ cr_year,
        multiple = FALSE
      )
    ),
    htmltools::div(
      class = "filter-input",
      filter_select(
        "filter_input",
        "Global / Germany",
        shared_publisher_df,
        ~ collection,
        multiple = FALSE
      )
    ),
  ),
  # table
  g
)

export_files(
    .data = table_df,
    .drops = c("max_all_group", "max_cc_group", "max_jn_group")
)
```

:::


```{js, echo = FALSE}
 /* https://stackoverflow.com/a/66216595 */
$(document).ready(function() {
    document.getElementById("filter_year").getElementsByClassName("selectized")[0].selectize.setValue("2023", false);
     document.getElementById("filter_input").getElementsByClassName("selectized")[0].selectize.setValue("Global", false);
});
```


## Country view

This section shows how hybrid open access has been adopted in different parts of the world. The analysis is based on the country affiliation of lead authors. Lead authors are the first named authors of scholarly articles, who have typically conducted most of the research presented in the article, although the role of lead authors can vary across disciplines. We used OpenAlex as a data source to determine the affiliation of lead authors.

### Open Access in hybrid journals by country

Open Access uptake in hybrid journals with a Creative Commons license per country. Shown are the Top 20 most productive countries in terms of articles published in hybrid journals included in transformative agreements between 2017 and 2024. The analysis is based on lead author country affiliations.

::: column-body-outset
```{r country_top_20}
#| echo: false
#| message: false
#| warning: false
source("R/country_top_20.R")

ggiraph::girafe(
  ggobj = country_multiple_plot,
  width_svg = 9,
  height_svg = 7 * 0.618,
  options = list(opts_tooltip(
    css="background-color:white;
;font-size:1.15em;padding:10px;border-radius:5px;box-shadow: 0 0 10px 0 rgba(0, 0, 0, 0.5)",
    opacity = .95),
    opts_toolbar(saveaspng = FALSE)))

export_files(
    .data = country_multiple_plot$data,
    .plot = country_multiple_plot,
    width = 9,
    height = 7 * 0.618,
    .drops = c("my_cols", "tooltip_text", ".group", "max_")
)
```
:::

### Country League

Publication volume in hybrid journals included in transformative agreements and Open Access share per country. You can search for specific countries, and filter by publisher and publication year. The analysis is based on country-affiliations of lead authors.

```{r}
#| echo: false
#| message: false
#| warning: false
source("R/country_publisher_league.R")
```


```{r country_league}
htmltools::div(
  class = "agreement-tbl",
  htmltools::div(
    class = "filters",
    htmltools::div(
      class = "filter-input",
      filter_select(
        "filter_country",
        "Countries",
        shared_oa_country_df,
        ~ country_name,
        multiple = TRUE
      )
    ),
    htmltools::div(
      class = "filter-input",
      filter_select(
        "filter_country_deal",
        "Publisher",
        shared_oa_country_df,
        ~ esac_publisher,
        multiple = FALSE
      )
    ),
    htmltools::div(
      class = "filter-input",
      filter_select(
        "filter_country_year",
        "Publication Year",
        shared_oa_country_df,
        ~ cr_year,
        multiple = FALSE
      )
    )
  ),
  react_table_oa_country
)

export_files(
    .data = shared_oa_country_df$data(), 
    .drops = c("max_group", "max_all_group")
)
```


```{js,echo = FALSE}
 /* https://stackoverflow.com/a/66216595 */
$(document).ready(function() {
    document.getElementById("filter_country_year").getElementsByClassName("selectized")[0].selectize.setValue("2023", false);
    document.getElementById("filter_country_deal").getElementsByClassName("selectized")[0].selectize.setValue("All", false);
});
```

## Open metadata

Open and comprehensive metadata are a key requirement of many transformative agreements. The following tables illustrate potential gaps in Crossref metadata for Open Access articles in hybrid journals included in transformative agreements.

### License metadata gaps

Comparison of open licence metadata in Crossref with Unpaywall via OpenAlex per year. You can compare global metrics with metrics only for articles by lead authors based in Germany. In addition to Crossref licence information, Unpaywall also analyses publisher websites to determine whether an article has been published under an open licence. More Open Access articles derived from Crossref may indicate a delay between metadata changes and Unpaywall-indexing, while more Open Access articles identified by Unpaywall suggest that publishers have not deposited licensing metadata in Crossref for all articles.


```{r upw_cr_license_gaps_data_prep}
#| echo: false
#| message: false
#| warning: false
upw_cr_diff_year <- hoaddata::cr_upw |>
  inner_join(esac_df, by = "issn_l") |>
  mutate(esac_publisher = forcats::fct_relevel(forcats::as_factor(esac_publisher), publ_league)) |>
  group_by(cr_year, esac_publisher, cat) |>
  summarise(
    article_total = sum(article_total),
    upw_hybrid_total = sum(upw_hybrid_total),
    cr_hybrid_total = sum(cr_hybrid_total)
  ) |>
  mutate(perc_upw = upw_hybrid_total / article_total,
         perc_cr = cr_hybrid_total / article_total) |>
  mutate(perc_diff = perc_cr - perc_upw) |>
  mutate(across(starts_with("perc_"), round, digits = 3)) |>
  select(-contains("total"),-article_total) |>
  relocate(perc_cr, .before = perc_upw)
```

```{r upw_cr_license_gaps_data_table}
source("R/cr_upw.R")

shared_upw_cr_diff_year <- SharedData$new(upw_cr_diff_year)
upw_cr_react_tbl <- upw_cr_react(shared_upw_cr_diff_year, "jct")

htmltools::div(
  class = "agreement-tbl",
  # filters,
  htmltools::div(class = "filters",
                 htmltools::div(
                   class = "filter-input",
                   filter_select(
                     "filter_cr_publisher",
                     "Publisher",
                     shared_upw_cr_diff_year,
                     ~ esac_publisher,
                     multiple = TRUE
                   )
                 ),
    htmltools::div(
      class = "filter-input",
      filter_select(
        "filter_cr_year",
        "Publication Year",
        shared_upw_cr_diff_year,
        ~ cr_year,
        multiple = FALSE
      )
    ),
    htmltools::div(
      class = "filter-input",
      filter_select(
        "filter_cr_input",
        "Global / Germany",
        shared_upw_cr_diff_year,
        ~ cat,
        multiple = FALSE
      )
    ),
  ),
  # table
  upw_cr_react_tbl
)

export_files(.data =  shared_upw_cr_diff_year$data())
```

```{js, echo = FALSE}
 /* https://stackoverflow.com/a/66216595 */
$(document).ready(function() {
    document.getElementById("filter_cr_year").getElementsByClassName("selectized")[0].selectize.setValue("2023", false);
     document.getElementById("filter_cr_input").getElementsByClassName("selectized")[0].selectize.setValue("Global", false);
});
```


### Crossref metadata coverage

This table shows the proportion of Crossref metadata that is publicly available for Open Access articles in hybrid journals included in transformative agreements. Publishers can use Crossref to share information about [Text and Data Mining (TDM)](https://www.crossref.org/blog/evolving-our-support-for-text-and-data-mining/ ), authors [(ORCID)](https://orcid.org/) and [funding](https://www.crossref.org/community/funders/). They can also open up [abstracts](https://i4oa.org/) and [reference lists](https://i4oc.org/) through Crossref.


```{r crossref_md_coverage}
#| echo: false
#| message: false
#| warning: false
source("R/open_md.R")
# Should be done in hoaddata  
pub_md <- hoaddata::jct_hybrid_jns |> 
  distinct(issn_l, esac_publisher) |> 
  inner_join(hoaddata::cr_md) |> 
  tidyr::complete(esac_publisher, cr_year, issn_l, cat) |>
  mutate(esac_publisher = forcats::fct_relevel(forcats::as_factor(esac_publisher), publ_league)) |> 
 mutate(across(where(is.numeric), replace_na, 0))

open_md_df <- shared_open_md_df(.data = pub_md, issn_l = pub_md$issn_l, publisher = pub_md$esac_publisher)

htmltools::div(
  class = "agreement-tbl",
  # filters,
  htmltools::div(
    class = "filters",
    htmltools::div(
      class = "filter-input",
      filter_select(
        "filter_open_md_cat_publisher",
        "Publisher",
        open_md_df,
        ~ esac_publisher,
        multiple = TRUE
      )
    ),
    htmltools::div(
      class = "filter-input",
      filter_select(
        "filter_open_md_input",
        "Metadata",
        open_md_df,
        ~ name,
        multiple = TRUE
      )
    ),
    htmltools::div(
      class = "filter-input",
      filter_select(
        "filter_open_md_cat_input",
        "Global / Germany",
        open_md_df,
        ~ cat,
        multiple = FALSE
      )
    ),
  ),
  # table
  open_md_react(
    open_md_df
    )
)

export_files(.data =  open_md_df$data())
```

```{js,echo = FALSE}
 /* https://stackoverflow.com/a/66216595 */
$(document).ready(function() {
    document.getElementById("filter_open_md_cat_input").getElementsByClassName("selectized")[0].selectize.setValue("Global", false);
});
```

## Journal table

This table presents the publication volume and Open Access share by journal between 2017 and 2024, comparing global metrics with metrics only for articles by lead authors based in Germany. Charts show the yearly Open Access share. You can search for journals or select a table header to sort by journal name or a metric.

::: column-body-outset


```{r}
#| echo: false
#| message: false
#| warning: false
my_df <- summarize_pubs(var_summary = c(cr_year, issn_l)) |>
  tidyr::complete(cr_year, issn_l, collection) |>
  mutate_if(is.numeric, ~ replace(., is.na(.), 0)) 
```

```{r journal_indicators}
#| echo: false
#| message: false
#| warning: false
source("R/journal_tbl.R")
htmltools::div(
  class = "agreement-tbl",
  journal_listing)
 
export_files(.data =  my_df)
```

:::

<small>Dashboard last compiled on `r format(Sys.time(), '%d %B, %Y')`.</small>

```{css}
.my-tbl {
  margin: 0 auto;
  width: 575px;
}
.tbl-header {
  margin: 18px 0;
  font-size: 1.25em;
}
.filters {
  display: flex;
  flex-wrap: wrap;
  margin-top: 4px;
  margin-bottom: 24px;
  margin-left: auto;
  margin-right: auto;
}
.filter-input {
  margin-top: 4px;
  margin-left: 32px;
  flex: 1;
  max-width: 250px;
}
.filter-input label {
  color: hsl(0, 0%, 45%);
  font-weight: 700;
  font-size: 13px;
  letter-spacing: 0.4px;
  text-transform: uppercase;
}
.group-header {
  font-weight: 700;
  font-size: 14px;
  letter-spacing: 0.4px;
  text-transform: uppercase;
}
.filter-input select,
.filter-input input[type="search"] {
  padding: 0 6px;
  height: 32px;
}
.filter-input input[type="search"] {
  /* Reset Bootstrap 3 styles */
  -webkit-appearance: searchfield;
}
.filter-input input[type="search"]::-webkit-search-cancel-button {
  /* Reset Bootstrap 3 styles */
  -webkit-appearance: searchfield-cancel-button;
}
.followers-tbl a {
  color: inherit;
}
.header {
  border-bottom: 2px solid #555;
  font-size: 14px;
  font-weight: bold;
  text-transform: uppercase;
}
.header:hover {
  background-color: #eee;
}
/* Highlight headers when sorting */
.header:hover,
.header[aria-sort="ascending"],
.header[aria-sort="descending"] {
  background-color: rgba(236, 236, 237, 1);
}
.agreement-footer {
  margin: 18px 0;
  font-size: 10px;
  }
  
.agreement-tbl {
  margin: 18px 0;
  font-size: 14px;
}
.bar-cell {
  display: flex;
  align-items: center;
}
.number {
  font-family: monospace;
  font-size: 14px;
  white-space: pre;
}
.label {
  font-size: 14px;
  white-space: pre;
}
.bar-chart {
  flex-grow: 1;
  margin-left: 6px;
  height: 14px;
}
.bar {
  height: 100%;
}
.border-left {
  border-left: 2px solid #b5b5b5;
}
.name {
  font-weight: 900;
}
```