Membership to Copyright Treaties

core

Files Size Format Created Updated License Source
2 54kB csv zip 6 months ago 2 months ago Open Data Commons Public Domain Dedication and Licence 1.0 World Intellectual Property Organization
This data provides the details of the membership by states to WIPO administered treaties on the subject matter of copyright, namely: Beijing Treaty on Audiovisual Performances Berne Convention for the Protection of Literary and Artistic Works Brussels Convention Relating to the Distribution of read more
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Data Files

File Description Size Last changed Download
membership-to-copyright-treaties 75kB csv (75kB) , json (173kB)
membership-to-copyright-treaties_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 28kB zip (28kB)

This is a preview version. There might be more data in the original version.

Field information

Field Name Order Type (Format) Description
Contracting Party 1 string
Treaty 2 string
Signature Date 3 date (%Y-%m-%d)
Instrument Type 4 string
Instrument Date 5 date (%Y-%m-%d)
Entry Into Force Date 6 date (%Y-%m-%d)

Read me

This data provides the details of the membership by states to WIPO administered treaties on the subject matter of copyright, namely:

  • Beijing Treaty on Audiovisual Performances
  • Berne Convention for the Protection of Literary and Artistic Works
  • Brussels Convention Relating to the Distribution of Programme-Carrying Signals Transmitted by Satellite
  • Marrakesh Treaty to Facilitate Access to Published Works for Persons Who Are Blind, Visually Impaired or Otherwise Print Disabled
  • Convention for the Protection of Producers of Phonograms Against Unauthorized Duplication of Their Phonograms
  • WIPO Copyright Treaty
  • WIPO Performances and Phonograms Treaty

Data

The data is taken from the tables found on WIPO’s website, it’s free and can be viewed for each treaty individually from this link.

Note that WIPO administers other intellectual property treaties that cover subject matter outside copyright (e.g. trademarks) which are not included in this data package.

License

These data are made available under the Public Domain Dedication and License v1.0 whose full text can be found at: http://www.opendatacommons.org/licenses/pddl/1.0/

Import into your tool

Data-cli or just data is the program to get and post your data with the datahub.
Download CLI tool and use it with the datahub almost like you use git with the github:

data get https://datahub.io/core/membership-to-copyright-treaties
data info core/membership-to-copyright-treaties
tree core/membership-to-copyright-treaties
# Get a list of dataset's resources
curl -L -s https://datahub.io/core/membership-to-copyright-treaties/datapackage.json | grep path

# Get resources

curl -L https://datahub.io/core/membership-to-copyright-treaties/r/0.csv

curl -L https://datahub.io/core/membership-to-copyright-treaties/r/1.zip

If you are using R here's how to get the data you want quickly loaded:

install.packages("jsonlite", repos="https://cran.rstudio.com/")
library("jsonlite")

json_file <- 'https://datahub.io/core/membership-to-copyright-treaties/datapackage.json'
json_data <- fromJSON(paste(readLines(json_file), collapse=""))

# get list of all resources:
print(json_data$resources$name)

# print all tabular data(if exists any)
for(i in 1:length(json_data$resources$datahub$type)){
  if(json_data$resources$datahub$type[i]=='derived/csv'){
    path_to_file = json_data$resources$path[i]
    data <- read.csv(url(path_to_file))
    print(data)
  }
}

Note: You might need to run the script with root permissions if you are running on Linux machine

Install the Frictionless Data data package library and the pandas itself:

pip install datapackage
pip install pandas

Now you can use the datapackage in the Pandas:

import datapackage
import pandas as pd

data_url = 'https://datahub.io/core/membership-to-copyright-treaties/datapackage.json'

# to load Data Package into storage
package = datapackage.Package(data_url)

# to load only tabular data
resources = package.resources
for resource in resources:
    if resource.tabular:
        data = pd.read_csv(resource.descriptor['path'])
        print (data)

For Python, first install the `datapackage` library (all the datasets on DataHub are Data Packages):

pip install datapackage

To get Data Package into your Python environment, run following code:

from datapackage import Package

package = Package('https://datahub.io/core/membership-to-copyright-treaties/datapackage.json')

# print list of all resources:
print(package.resource_names)

# print processed tabular data (if exists any)
for resource in package.resources:
    if resource.descriptor['datahub']['type'] == 'derived/csv':
        print(resource.read())

If you are using JavaScript, please, follow instructions below:

Install data.js module using npm:

  $ npm install data.js

Once the package is installed, use the following code snippet:

const {Dataset} = require('data.js')

const path = 'https://datahub.io/core/membership-to-copyright-treaties/datapackage.json'

// We're using self-invoking function here as we want to use async-await syntax:
;(async () => {
  const dataset = await Dataset.load(path)
  // get list of all resources:
  for (const id in dataset.resources) {
    console.log(dataset.resources[id]._descriptor.name)
  }
  // get all tabular data(if exists any)
  for (const id in dataset.resources) {
    if (dataset.resources[id]._descriptor.format === "csv") {
      const file = dataset.resources[id]
      // Get a raw stream
      const stream = await file.stream()
      // entire file as a buffer (be careful with large files!)
      const buffer = await file.buffer
      // print data
      stream.pipe(process.stdout)
    }
  }
})()
Datapackage.json