OBIS dataset licenses

This is an overview of data licenses applied to OBIS datasets. In particular, it shows the distribution of public domain (CC0) and open licenses (CC BY, CC BY-SA), versus more restrictive licenses (such as CC BY-NC) across datasets and records. Creative Commons licenses other than CC0, CC BY, and CC BY-SA, are considered non-free because they impose restrictions on commercial and derivative use. The former licenses however, are conformant with the Open Knowledge Foundation’s Open Definition.

Nature Scientific Data recommends the use of CC0 or CC BY licenses. NCEI encourages the use of CC0 or CC BY for data produced by non-Federal entities.

Besides Creative Commons licenses, OBIS datasets also use other licenses such as:

• Open Government Licence - Canada (OGL-C)
• Open Data Commons Attribution License (ODC-By)
• ICES Data Policy

For the purpose of this analysis these licenses will be considered open, but the ICES Data Policy requires closer investigation as it mentions some exceptions on the use of CC BY.

Dataset metadata

Dataset metadata including licenses can be obtained from the OBIS API using the robis R package. Because the license field is free text, some cleanup is required.

library(dplyr)
library(ggplot2)
library(robis)
library(scales)
library(knitr)
library(stringr)
library(tidyr)

report_theme <- theme(
    axis.text = element_text(colour = "black"),
    axis.line = element_line(linewidth = rel(1)),
    axis.line.y = element_blank(),
    axis.ticks = element_line(), axis.ticks.y = element_blank(),
    panel.grid.minor = element_blank(),
    panel.grid.major.y = element_blank(),
    plot.background = element_blank(),
    panel.background = element_rect(fill = "#f5f5f5", colour = NA),
    legend.background = element_blank()
  )

categories <- c("Public domain", "Open", "Non-free")

full_datasets <- dataset()

datasets <- full_datasets %>% 
  select(id, records, intellectualrights, node_name, title) %>% 
  mutate(
    license = case_when(
      str_detect(intellectualrights, "CC-BY\\)?[- ]4.0") ~ "CC BY",
      str_detect(intellectualrights, "creativecommons.org/licenses/by/4.0") ~ "CC BY",
      str_detect(intellectualrights, "CC-BY-?NC\\)?[- ]4.0") ~ "CC BY-NC",
      str_detect(intellectualrights, "CC[- ]BY[- ]SA") ~ "CC BY-SA",
      str_detect(intellectualrights, "CC[- ]BY[- ]NC[- ]SA") ~ "CC BY-NC-SA",
      str_detect(intellectualrights, "CC[- ]BY[- ]NC[- ]ND") ~ "CC BY-NC-ND",
      str_detect(intellectualrights, "CC[- ]BY[- ]ND") ~ "CC BY-ND",
      str_detect(intellectualrights, "(?i)CC0") ~ "CC0",
      str_detect(intellectualrights, "waived all rights") ~ "CC0",
      str_detect(intellectualrights, "creativecommons.org/publicdomain/zero/1\\.0") ~ "CC0",
      str_detect(intellectualrights, "Open Data Commons Attribution") ~ "Open Data Commons Attribution",
      str_detect(intellectualrights, "(?i)unrestricted") ~ "CC0",
      str_detect(intellectualrights, "(?i)^restricted") ~ "Restricted",
      str_detect(intellectualrights, "remain property of") ~ "Restricted",
      str_detect(intellectualrights, "data.gc.ca/eng/open-government-licence-canada") ~ "Open Government Licence - Canada",
      str_detect(intellectualrights, "ICES Data Policy") ~ "ICES Data Policy",
      TRUE ~ "Unknown"
    )
  ) %>% mutate(
    intellectualrights = gsub("\\\n", " ", intellectualrights),    
    category = case_when(
      license == "CC0" ~ "Public domain",
      license == "CC BY" ~ "Open",
      license == "CC BY-SA" ~ "Open",
      license == "Open Data Commons Attribution" ~ "Open",
      license == "Open Government Licence - Canada" ~ "Open",
      license == "ICES Data Policy" ~ "Open",
      TRUE ~ "Non-free"
    )
  )

Records and datasets by license

First create a table of all licenses as they appear in the metadata, along with the clean name, and statistics on records and datasets.

licenses <- datasets %>% 
  group_by(license, intellectualrights, category) %>%
  summarise(datasets = n(), records = sum(records), .groups = "drop") %>%
  arrange(desc(records))

kable(licenses %>% head(10))

license	intellectualrights	category	datasets	records
CC BY	This work is licensed under a Creative Commons Attribution (CC-BY) 4.0 License	Open	2484	98196025
CC BY-NC	This work is licensed under a Creative Commons Attribution Non Commercial (CC-BY-NC) 4.0 License	Non-free	1830	23258292
CC0	To the extent possible under law, the publisher has waived all rights to these data and has dedicated them to the Public Domain (CC0 1.0)	Public domain	677	19307392
CC BY	This work is licensed under a Creative Commons Attribution Non Commercial (CC-BY) 4.0 License	Open	528	9000138
CC0	To the extent possible under law, the publisher has waived all rights to these data and has dedicated them to the Public Domain (CC0 1.0)	Public domain	30	2632396
CC BY	This work is licensed under a Creative Commons Attribution (CC-BY 4.0) License	Open	258	2266717
Unknown	Licence	Non-free	6	1452981
Unknown		Non-free	22	876991
Open Government Licence - Canada	rights: http://data.gc.ca/eng/open-government-licence-canada & http://www.canadensys.net/norms rights holder: Her Majesty the Queen in right of Canada, as represented by the Minister of Fisheries and Oceans	Open	2	812015
CC BY-NC	This work is licensed under a Creative Commons Attribution Non Commercial (CC-BY-NC) 4.0 License	Non-free	24	563017

Number of records

Here we look at the usage of (cleaned) licenses in terms of number of records.

license_stats <- licenses %>% 
  group_by(license, category) %>% 
  summarize(records = sum(records), datasets = sum(datasets), .groups = "drop") %>% 
  arrange(-records) %>% 
  mutate(
    license = factor(license, levels = rev(reorder(license, records))),
    category = factor(category, levels = categories),
    records_percentage = records / sum(records) * 100,
    datasets_percentage = datasets / sum(datasets) * 100
  )

ggplot(data = license_stats) +
  geom_bar(aes(y = license, x = records, fill = category), stat = "identity") +
  geom_text(aes(y = license, x = records, label = paste0(round(records_percentage, 1), "%")), vjust = 0.5, hjust = -0.2) +
  ggtitle("Licenses by number of records") +
  scale_fill_manual(values = c("#7ABD7E", "#FFB54C", "#FF6961")) +
  scale_x_continuous(
    expand = expansion(mult = c(0, 0.1)),
    labels = label_comma()
  ) +
  report_theme

Number of datasets

Here we look at the usage of (cleaned) licenses in terms of number of datasets

ggplot(data = license_stats) +
  geom_bar(aes(y = license, x = datasets, fill = category), stat = "identity") +
  geom_text(aes(y = license, x = datasets, label = paste0(round(datasets_percentage, 1), "%")), vjust = 0.5, hjust = -0.2) +
  ggtitle("Licenses by number of datasets") +
  scale_fill_manual(values = c("#7ABD7E", "#FFB54C", "#FF6961")) +
  scale_x_continuous(
    expand = expansion(mult = c(0, 0.1)),
    labels = label_comma()
  ) +
  report_theme

Records and datasets by node and license

In this section we look at license categories by node.

Number of records

node_license_stats <- datasets %>%
  separate_rows(node_name, sep = ",") %>% 
  group_by(node_name, category) %>%
  summarise(datasets = n(), records = sum(records), .groups = "drop") %>% 
  mutate(
    node_name = factor(node_name, levels = rev(sort(unique(node_name)))),
    category = factor(category, levels = categories)
  )

ggplot(data = node_license_stats) +
  geom_bar(aes(y = node_name, x = records, fill = category), stat = "identity") +
  scale_fill_manual(values = c("#7ABD7E", "#FFB54C", "#FF6961")) +
  scale_x_continuous(
    labels = label_comma()
  ) +
  ylab("node") +
  ggtitle("Number of records by node and license") +
  report_theme

Number of datasets

ggplot(data = node_license_stats) +
  geom_bar(aes(y = node_name, x = datasets, fill = category), stat = "identity") +
  scale_fill_manual(values = c("#7ABD7E", "#FFB54C", "#FF6961")) +
  scale_x_continuous(
    labels = label_comma()
  ) +
  ylab("node") +
  ggtitle("Number of datasets by node and license") +
  report_theme