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WIGI is a project producing a open data set about the gender, date of birth, place of birth, ethnicity, occupation, and language of biography articles in all Wikipedias. Our data set comes from Wikidata, the database the feeds Wikipedia, and is updated weekly. This website shows a few demonstrations of what can be done with that information.

This project started as a personal research interest, and is now funded by a Wikimedia Foundation Grant.


The website is based on popularly used Python based static site generator, Nikola. After post processing of Wikidata, graphs are generated using Bokeh, another Python based interactive visualization library targeting web browsers.

We currently intend to display four graphs: Gender by Culture, Gender by Country (World Map), Gender by Date of Birth, and Wikipedia Language by Gender.

Run it locally

Getting the data

To run the site offline, you must download a set newest and newest-changes snapshot data from the server. A tar file containing these latest changes is available at snapshot data.

Please download and extract at a convenient location.

Running the site

We recommended installing conda, an open source python package and environment management tool. The installation instructions can be found on their respective websites. Please install the Python 3 version or create a Python 3 environment as current setup supports only Python 3.

Once you have cloned the repository, run the following command inside the directory to install dependencies:

pip install -r requirements.txt

In case pip is missing, run conda install pip. Once the installation is complete (might take a while), next step is to configure the location to your data directory.

Open inside the plots/ folder and edit the data_dir path to the location where you extracted snapshot_data in previous step. Rename the file to or create a new one if you wish.

Finally, run:

nikola build && nikola serve

If everything goes fine, you should be able to see WIGI website in action at

Please note that you need use the Nikola provided server to serve the requests. The output of nikola build is a self contained, static website in the output/ directory, which can be rendered by any server. A quick python server, for example.

How does it work?

All you need to know for running the WIGI website and playing with graphs is to run nikola build && nikola serve. If, however, you want to add more graphs or play with new data, there are couple of things to note.

It all starts with the file in the repository root directory. This file is used to configure how Nikola behaves and how does it generate static HTML pages from templates.

  1. All the posts are constructed from their specific templates, which file metadata and instructions on how to render the specific HTML page. For example, gender by post has the following one line in the description:
.. template: gender_by_country.tmpl

This specifies the template to be used for creating the gender_by_country.html file. The templates are located in templates/ directory.

  1. Templates instruct how to build web page and where to embed Bokeh graph. For example, if you open gender_by_country.tmpl for example, you can find the following block which embeds the plot data (using a plot_helper.tmpl template file) on the page and renders it.
  1. The interesting part, as to how Nikola templates receive the plot data, can be answered by inspecting When nikola build is run, first is executed. In this file, we import our Bokeh plot generating functions and generate respective plots' data. These data are then made available to all the Nikola templates as a plots dictionary by putting them into GLOBAL_CONTEXT.
    'plots' : {
        'gender_by_country': {
            'newest': gender_by_country.plot('newest'),
            'newest_changes': gender_by_country.plot('newest-changes')
        'gender_by_culture': {
            'newest': gender_by_culture.plot('newest'),
            'newest_changes': gender_by_culture.plot('newest-changes')
These variables were referenced in the respective template files (as

explained in point (2) to embed the plot data.

All of this happens automatically by running nikola build.

Adding a plot

If you have a new plot to add, you need to add the following files:

  1. A Python script to generate the Bokeh plot data and import the function in Place the script in plots/ directory and see any existing file to learn about what the function should do and return.
  2. A template file <graph>.tmpl describing where you want to embed the plot data.
  3. A markdown file <post>.md referencing the template in the description, and other data (text, commentary, citations etc.,) you want along with the post.

Please see any existing file for clear example. Once you are done, run nikola build && nikola serve.

Using new data

Just add any updated data to the data_dir you have used in the file, and let your script use it.


Max Klein (@notconfusing), Vivek Rai (@raivivek), Harsh Gupta (@hargup)


WHGI Google Group is the best way to reach to us and community of users who have used WHGI. Alternatively, feel free to reach out to corresponding authors via email.


 author = {Klein, Maximilian and Gupta, Harsh and Rai, Vivek and Konieczny, Piotr and Zhu, Haiyi},
 title = {Monitoring the Gender Gap with Wikidata Human Gender Indicators},
 booktitle = {Proceedings of the 12th International Symposium on Open Collaboration},
 series = {OpenSym '16},
 year = {2016},
 isbn = {978-1-4503-4451-7},
 location = {Berlin, Germany},
 pages = {16:1--16:9},
 articleno = {16},
 numpages = {9},
 url = {},
 doi = {10.1145/2957792.2957798},
 acmid = {2957798},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {Biographical Database, Gender Disparities, Wikidata, Wikipedia},


All source code files are available under MIT License and content is available under a Creative Commons Attribution-ShareAlike 4.0 International License respectively.