Metadata from IPBES on Zenodo

Technical Guideline Series

Abstract

To be added

GitHub Repository

Methods

Setup and get records from Zenodo

#|

# Load the zen4R library
library(zen4R)
library(openalexR)

Thank you for using openalexR!
To acknowledge our work, please cite the package by calling `citation("openalexR")`.
To suppress this message, add `openalexR.message = suppressed` to your .Renviron file.

library(dplyr)

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

fn <- file.path("data", "ipbes_zenodo_records")
if (!file.exists(paste0(fn, ".rds"))) {
  # Authenticate with Zenodo
  zen <- ZenodoManager$new(token = Sys.getenv("Zenodo_IPBES_RO"))

  # Get the community ID
  community_id <- "ipbes"

  # Get the community info
  community <- zen$getCommunityById(community_id)

  # Get all deposits with ipbes somwhere
  ipbes_zenodo <- zen$getRecords(community_id)

  # Filter records based on the community ID
  ipbes <- sapply(
    ipbes_zenodo,
    function(record) {
      "ipbes" %in% unlist(record$metadata$communities)
    }
  )

  ipbes_zenodo <- ipbes_zenodo[ipbes]

  rm(ipbes)

  saveRDS(ipbes_zenodo, paste0(fn, ".rds"))
} else {
  ipbes_zenodo <- readRDS(paste0(fn, ".rds"))
}

Get the dois and titles of the records

#|

dois <- data.frame()

for (i in seq(length.out = length(ipbes_zenodo))) {
  record <- ipbes_zenodo[[i]]
  dois <- rbind(
    dois,
    c(
      doi = record$metadata$doi,
      year = record$metadata$publication_date,
      title = record$metadata$title
    )
  )
}

names(dois) <- c("doi", "year", "title")

dois <- tibble::as_tibble(dois)

fn <- file.path(".", "data", "ipbes_works.rds")
if (!file.exists(fn)) {
  # Define the maximum chunk size
  chunk_size <- 50
  # Split the vector into chunks
  doi_chunks <- split(
    dois$doi,
    ceiling(seq_along(dois$doi) / chunk_size)
  )

  ipbes_works <- lapply(
    doi_chunks,
    function(dois) {
      openalexR::oa_query(doi = dois) |>
        openalexR::oa_request(count_only = FALSE)
    }
  ) |>
    unlist(recursive = FALSE)

  saveRDS(ipbes_works, file = fn)
} else {
  ipbes_works <- readRDS(file = fn)
}

Results

Keywords

Number of keywords per Deposit

#|

ipbes_zenodo |>
  sapply(
    FUN = function(x) {
      x$metadata$keywords |>
        unlist() |>
        length()
    }
  ) |>
  table() |>
  knitr::kable(
    col.names = c("Number of keywords", "n")
  )

Number of keywords	n
0	129
1	61
2	44
3	77
4	21
5	10
6	13
7	8
8	1
9	1
10	1

The deposits without keywords

#|

ipbes_zenodo |>
  lapply(
    FUN = function(x) {
      kws <- x$metadata$keywords |>
        unlist() |>
        paste0(collapse = " | ")
      result <- list(
        no_kws = x$metadata$keywords |>
          unlist() |>
          length(),
        title = paste0("<a href='", x$links$self_html, "' target='_blank'>", substr(x$title, 1, 60), "</a>"),
        keywords = kws
      )
      return(result)
    }
  ) |>
  dplyr::bind_rows() |>
  dplyr::arrange(no_kws, title) |>
  IPBES.R::table_dt()

Keywords used in the deposits

#|

ipbes_zenodo |>
  sapply(
    FUN = function(x) {
      x$metadata$keywords |>
        unlist()
    }
  ) |>
  unlist() |>
  table() |>
  sort(decreasing = TRUE) |>
  knitr::kable(col.names = c("Keyword", "n"))

Keyword	n
IPBES	178
Data management report	47
Assessment	36
data management policy	31
Values Assessment	30
Invasive alien species	27
Global Assessment	20
Supplementary material	19
Europe and Central Asia Assessment	18
Chapter 4	15
Summary for Policymakers	14
Table	13
Chapter 2	12
Figure	11
SPM	11
Full assessment report	9
Values	9
Chapter	8
Chapter 3	8
Chapter 6	7
Chapter 5	6
Regional assessment	6
Africa Assessment	5
Decision	4
Summary for policymakers	4
Biodiversity	3
Chapter 1	3
data and knowledge management policy	3
data management	3
Future	3
ILK	3
Land Degradation and Restoration Assessment	3
Pollination Assessment	3
Scenarios and Models Assessment	3
Valuation	3
Americas Assessment	2
Arabic	2
Asia and the Pacific Assessment	2
Capacities	2
Chinese	2
Data Management	2
Decision-making	2
Diverse	2
FAIR	2
French	2
Just	2
Methods	2
Operationalization	2
Russian	2
Spanish	2
stakeholder engagement	2
survey	2
Sustainable	2
active data management	1
Anthrome	1
Approaches	1
Archetypes	1
Biocultural conservation	1
Biome	1
Brightspot cases	1
CARE	1
CARE principles	1
Climate change	1
Climate Change	1
Conceptualization	1
Constitutions	1
COVID-19	1
Data and knowledge management policy	1
data backup	1
Data Management Policy	1
Data Management Report, Nature Futures Framework	1
Data Policy	1
Dataset	1
Decision making	1
Diverse values	1
DOI	1
Earth Stewardship	1
FAIR principles	1
Gap	1
global, species rarity, endemicity	1
Indicators	1
Indigenous Peoples and local communities	1
IPBES, Data Management Policy	1
IPBES, Senckenberg, Data Management, Policy, FAIR	1
IPBES, Values, Assessment, Figures, Chapter 1	1
IPBES, Values, SPM, Values	1
IPCC	1
IPCCC	1
Knowledge Management	1
long-term vision	1
Methodological	1
Methodological guidance	1
Methodologies	1
Model	1
Nature	1
Nature Futures Framework	1
open science	1
Option	1
Pandemics	1
Pathway	1
Plural Value Approach	1
Policy	1
Policy initiatives	1
Policy instruments	1
Pollination assessment	1
Scenario	1
scenarios, biodiversity, ecosystem services, nature’s contributions to people, nature futures, IPBES, visioning, narratives	1
Science-Policy	1
Stakeholder Survey	1
Transformative change	1
Transformative governance	1
VA	1
Values assessment	1
Zenodo	1

Licenses and Access

Licenses

#|

ipbes_zenodo |>
  sapply(
    FUN = function(x) {
      l <- x$metadata$license
      if (is.null(l)) {
        l <- "NULL"
      }
      return(l)
    }
  ) |>
  unlist() |>
  table(useNA = "always") |>
  knitr::kable(
    col.names = c(
      "license",
      "n"
    )
  )

license	n
cc-by-4.0	346
NULL	20
NA	0

The deposits without licenses are

#|

ipbes_zenodo |>
  lapply(
    FUN = function(x) {
      if (is.null(x$metadata$license)) {
        result <- list(
          title = substr(x$title, 1, 60),
          link = paste0("<a href='", x$links$self_html, "' target='_blank'>", x$doi, "</a>")
        )
      } else {
        result <- NULL
      }
      return(result)
    }
  ) |>
  dplyr::bind_rows() |>
  dplyr::arrange(title) |>
  knitr::kable()

title	link
2020 Stakeholder Survey of the Intergovernmental Platform on	10.5281/zenodo.4121916
DISCARD_IPBES Invasive Alien Species Assessment: Chapter 2.	10.5281/zenodo.10052573
Hotspots of endemism and rarity - Figure 2.2.3 IPBES Global	10.5281/zenodo.4957887
IPBES Core Indicators - Harmonized Dataset	10.5281/zenodo.4564763
IPBES Country Borders Package	10.5281/zenodo.5883633
IPBES IAS assessment, data management report for Chapter 2.	10.5281/zenodo.5746076
IPBES Invasive Alien Species Assessment: Chapter 1. Figures,	10.5281/zenodo.10622445
IPBES Invasive Alien Species Assessment: Chapter 1. Introduc	10.5281/zenodo.10677041
IPBES Invasive Alien Species Assessment: Chapter 2. Trends a	10.5281/zenodo.10677067
IPBES Invasive Alien Species Assessment: Chapter 3. Drivers	10.5281/zenodo.10677074
IPBES Invasive Alien Species Assessment: Chapter 3. Figures,	10.5281/zenodo.10627673
IPBES Invasive Alien Species Assessment: Chapter 4. Figures,	10.5281/zenodo.10633229
IPBES Invasive Alien Species Assessment: Chapter 4. Impacts	10.5281/zenodo.10677193
IPBES Invasive Alien Species Assessment: Chapter 5. Figures,	10.5281/zenodo.10633264
IPBES Invasive Alien Species Assessment: Chapter 5. Manageme	10.5281/zenodo.11437851
IPBES Invasive Alien Species Assessment: Chapter 6. Figures,	10.5281/zenodo.10633484
IPBES Invasive Alien Species Assessment: Chapter 6. Governan	10.5281/zenodo.10677227
IPBES Invasive Alien Species Assessment: Full report	10.5281/zenodo.11629357
IPBES Long-term Vision on Data and Knowledge Management	10.5281/zenodo.5513474
Interactive Dashboard of the 2020 Stakeholder Survey of the	10.5281/zenodo.5046948

Access Rights

#|

ipbes_zenodo |>
  sapply(
    FUN = function(x) {
      x$metadata$access_right
    }
  ) |>
  table(useNA = "always") |>
  knitr::kable(
    col.names = c(
      "access right",
      "n"
    )
  )

access right	n
embargoed	2
open	320
restricted	44
NA	0

The non-open deposits are:

#|

ipbes_zenodo |>
  lapply(
    FUN = function(x) {
      if (x$metadata$access_right != "open") {
        result <- list(
          title = substr(x$title, 1, 60),
          access_right = x$metadata$access_right,
          link = paste0("<a href='", x$links$self_html, "' target='_blank'>", x$doi, "</a>")
        )
      } else {
        result <- NULL
      }
      return(result)
    }
  ) |>
  dplyr::bind_rows() |>
  dplyr::arrange(title) |>
  knitr::kable()

title	access_right	link
2020 Stakeholder Survey of the Intergovernmental Platform on	restricted	10.5281/zenodo.4121916
DISCARD_IPBES Invasive Alien Species Assessment: Chapter 2.	restricted	10.5281/zenodo.10052573
Hotspots of endemism and rarity - Figure 2.2.3 IPBES Global	restricted	10.5281/zenodo.4957887
IPBES Core Indicators - Harmonized Dataset	restricted	10.5281/zenodo.4564763
IPBES Country Borders Package	restricted	10.5281/zenodo.5883633
IPBES IAS assessment, data management report for Chapter 2.	restricted	10.5281/zenodo.5746076
IPBES Invasive Alien Species Assessment, data management rep	embargoed	10.5281/zenodo.5766070
IPBES Invasive Alien Species Assessment, database for Chapte	embargoed	10.5281/zenodo.5706617
IPBES Long-term Vision on Data and Knowledge Management	restricted	10.5281/zenodo.5513474
IPBES TCA Chapter 1. Analysis of contributions on what trans	restricted	10.5281/zenodo.12532308
IPBES TCA Chapter 1. Analysis of knowledge gaps / IPBES tran	restricted	10.5281/zenodo.11657378
IPBES TCA Chapter 1. Creation of a case studies database / I	restricted	10.5281/zenodo.10260234
IPBES TCA Chapter 1. Literature and data review regarding th	restricted	10.5281/zenodo.10245400
IPBES TCA Chapter 1. Literature review determining the princ	restricted	10.5281/zenodo.11657640
IPBES TCA Chapter 1. Literature review of case studies with	restricted	10.5281/zenodo.10246745
IPBES TCA Chapter 2. Content analysis of most potentially tr	restricted	10.5281/zenodo.10548648
IPBES TCA Chapter 2. Systematic literature review on visions	restricted	10.5281/zenodo.10252320
IPBES TCA Chapter 3. Identification of on-going initiatives	restricted	10.5281/zenodo.10250564
IPBES TCA Chapter 3. Review of knowledge on theories and fra	restricted	10.5281/zenodo.10250534
IPBES TCA Chapter 3. Systematic review of literature on tran	restricted	10.5281/zenodo.10523261
IPBES TCA Chapter 4. Review of literature on colonial modern	restricted	10.5281/zenodo.10250610
IPBES TCA Chapter 4. Review of literature on institutional m	restricted	10.5281/zenodo.10252251
IPBES TCA Chapter 4. Review of literature on limited access	restricted	10.5281/zenodo.10251409
IPBES TCA Chapter 4. Review of literature on power imbalance	restricted	10.5281/zenodo.10251326
IPBES TCA Chapter 4. Review of literature on unsustainable c	restricted	10.5281/zenodo.10252305
IPBES TCA Chapter 5. Shifting power towards just and sustai	restricted	10.5281/zenodo.10304954
IPBES TCA Chapter 5. Addressing unsustainable production and	restricted	10.5281/zenodo.10262310
IPBES TCA Chapter 5. Biodiversity conservation assessment me	restricted	10.5281/zenodo.10261652
IPBES TCA Chapter 5. Capacity building and technology transf	restricted	10.5281/zenodo.10262495
IPBES TCA Chapter 5. Inventory options for transformative ch	restricted	10.5281/zenodo.10264136
IPBES TCA Chapter 5. Review of options for achieving the 205	restricted	10.5281/zenodo.10262647
IPBES TCA Chapter 5. Views and Values / IPBES transformative	restricted	10.5281/zenodo.10305489
IPBES TCA. Corpus of literature on transformative change / I	restricted	10.5281/zenodo.10479548
IPBES nexus assessment - Chapter 2, data management report	restricted	10.5281/zenodo.10119408
IPBES nexus assessment - Chapter 2, data management report	restricted	10.5281/zenodo.10119473
IPBES nexus assessment - Chapter 2, data management report	restricted	10.5281/zenodo.10119431
IPBES nexus assessment - Chapter 2, data management report	restricted	10.5281/zenodo.10119511
IPBES nexus assessment - Chapter 3, data management report	restricted	10.5281/zenodo.10119540
IPBES nexus assessment - Chapter 4, data management report	restricted	10.5281/zenodo.10119750
IPBES nexus assessment - Chapter 4, data management report	restricted	10.5281/zenodo.10119625
IPBES nexus assessment - Chapter 5.1 – BIODIVERSITY, data m	restricted	10.5281/zenodo.10119872
IPBES nexus assessment - Chapter 5.2 – WATER, data manageme	restricted	10.5281/zenodo.10119960
IPBES nexus assessment - Chapter 5.4 – HEALTH, data managem	restricted	10.5281/zenodo.10119986
IPBES nexus assessment - Chapter 6, data management report	restricted	10.5281/zenodo.10120033
IPBES nexus assessment - Chapter 2, data management report 1	restricted	10.5281/zenodo.10101030
Interactive Dashboard of the 2020 Stakeholder Survey of the	restricted	10.5281/zenodo.5046948

IPBES Deposits Network

fn <- file.path("data", "ipbes_network.rds")

if (!file.exists(fn)) {
  relations <- lapply(
    ipbes_zenodo,
    function(rec) {
      relation <- rec$metadata$related_identifiers
      if (is.null(relation)) {
        return(NULL)
      }
      result <- rec$metadata$related_identifiers |>
        dplyr::bind_rows() |>
        dplyr::mutate(
          year = rec$metadata$publication_date,
          doi = rec$metadata$doi,
          title = rec$metadata$title,
          keywords = rec$metadata$keywords |>
            unlist() |>
            paste(collapse = "; "),
        )
      return(result)
    }
  ) |>
    dplyr::bind_rows() |>
    dplyr::left_join(
      y = read.table("input/relation_direction.txt", header = TRUE),
      by = "relation"
    )

  nodes <- unique(
    c(
      relations$doi,
      relations$identifier
    )
  )

  edges <- rbind(
    relations |>
      filter(
        direction == "to"
      ) |>
      dplyr::select(
        from = doi,
        to = identifier
      ),
    relations |>
      filter(
        direction == "from"
      ) |>
      dplyr::select(
        from = doi,
        to = identifier
      )
  )

  network <- list(
    nodes = nodes,
    edges = edges
  )

  ipbes_network <- list(
    nodes = nodes,
    edges = edges,
    relations = relations
  )
  rm(nodes, edges, relations)

  saveRDS(ipbes_network, fn)
} else {
  ipbes_network <- readRDS(fn)
}

keywords <- lapply(
  ipbes_zenodo,
  function(x) {
    result <- c(
      doi = x$doi,
      keywords = x$metadata$keywords |>
        unlist() |>
        paste(collapse = "` || `")
    )
    result["keywords"] <- paste0("`", result["keywords"], "`")
    return(result)
  }
) |>
  dplyr::bind_rows()

fn <- file.path("figures", "ipbes_network.html")

## Simple forceNetwork
networkData <- data.frame(
  src = ipbes_network$edges$from,
  target = ipbes_network$edges$to,
  stringsAsFactors = FALSE
)

nodes <- data.frame(
  name = ipbes_network$nodes,
  # title = ipbes_network$nodes$,
  # doi = ipbes_network$nodes$doi,
  stringsAsFactors = FALSE
)

nodes$id <- 0:(nrow(nodes) - 1)

# create a data frame of the edges that uses id 0:9 instead of their names
edges <- networkData |>
  left_join(nodes, by = c("src" = "name")) |>
  select(-src) |>
  rename(source = id) |>
  left_join(nodes, by = c("target" = "name")) |>
  select(-target) |>
  rename(target = id) |>
  mutate(width = 1)


## this will be the URL which will be opened when clicked on the node
nodes$doi <- paste0("https://doi.org/", nodes$name)

# # make a grouping variable that will match to colours
x <- nodes |>
  dplyr::left_join(
    keywords,
    by = c("name" = "doi")
  )

nodes$group <- "Other"
nodes$group[grep("`Assessment`", x$keywords)] <- "Assessment"
nodes$group[grep("`Data management report`", x$keywords)] <- "Data Management Report"
nodes$group[grep("`SPM`", x$keywords)] <- "SPM"


# nodes$oa_id <- nodes$name
# nodes$name <- nodes$author

# control colours with a JS ordinal scale
ColourScale <- 'd3.scaleOrdinal()
                         .domain(["SPM",      "Assessment", "Data Management Report", "Other"])
                         .range(["#00ff26", "#FF6900",  "#0000FF",              "#694489"]);'


nwg <- networkD3::forceNetwork(
  Links = edges,
  Nodes = nodes,
  Source = "source",
  Target = "target",
  NodeID = "name",
  # Nodesize = "nodesize",
  Group = "group",
  # Value = "width",
  opacity = 0.9,
  zoom = TRUE,
  colourScale = DT::JS(ColourScale),
  fontSize = 20,
  legend = TRUE,
  clickAction = "window.open(d.doi)"
)

nwg$x$nodes$doi <- nodes$doi


networkD3::saveNetwork(
  nwg,
  file = fn,
  selfcontained = TRUE
)

unlink(
  gsub(
    fn,
    pattern = "\\.html",
    replacement = "_files"
  ),
  recursive = TRUE,
  force = TRUE
)


nwg

IPBES Deposits Network

#|

ipbes_network$relations |>
  dplyr::select(
    doi,
    year,
    relation,
    identifier,
    direction,
    title,
    keywords
  ) |>
  IPBES.R::table_dt(
    fixedColumns = list(leftColumns = 3)
  )

IPBES deposits on Zenodo with OpenAlex ids

This is a quick and dirty table - it could made nicer - but it fulfills it’s purpose.

ipbes_works |>
  openalexR::works2df() |>
  dplyr::select(
    # year = publication_year,
    # title,
    doi,
    oa_id = id
  ) |>
  dplyr::mutate(
    doi = gsub(pattern = "https://doi.org/", replacement = "", x = doi)
  ) |>
  dplyr::left_join(
    x = dois,
    by = c("doi" = "doi")
  ) |>
  dplyr::mutate(
    doi = paste0("<a href='https://doi.org/", doi, "' target='_blank'>", doi, "</a>"),
    oa_id = ifelse(
      is.na(oa_id),
      "",
      paste0("<a href='", oa_id, "' target='_blank'>", gsub(pattern = "https://openalex.org/", replacement = "", oa_id), "</a>")
    )
  ) |>
  select(
    doi,
    oa_id,
    year,
    title
  ) |>
  IPBES.R::table_dt()

Suggested hierarchy of keywords

I suggest the following mandatory keyword scheme. Follow the chart from left to write until you reach your type of deposit. All in bold in that path need to be specified (e.g. Chapter as well as Chapter 3 when the deposit).

Additional keywords can be added.

Q: Should we start all mandatory standardised keywords with e.g. _ to make them identifyable from the additional keywords?

Suggested hierarchy of keywords