Data in Red - A holistic view on the bias for the English language and for AngloAmerican subjects

First a definition; "When data is biased, we mean that the sample is not representative of the entire population". This approach successfully underpins the Women in Red project currently a percentage of 18.51% women in English Wikipedia has been achieved. Compare the coverage of Anglo-American politicians with the politicians from the whole of Africa, the bias in the data at Wikidata is already obvious, it will then have numbers attached to it.

This is not a problem for Wikidata alone and yes, we can have a project and include a lot of data to get to a growth percentage as we did for the Women in Red. Worthwhile in its own right but in this way we do not forge a closer relation with its "premier brand Wikipedia". It would be mere stamp collecting.

The best argument for having data in Wikidata is that it is used. This is done in self selecting Wikipedias through global info boxes and lists. Interwiki links are used on every Wikipedia. Integrating the necessary functionality is a meta/technical affair and firmly for the Wikimedia Foundation to own. 

The functionality to make this happen implements an existing idea with additional twists.

• Pictures for the subject are linked to courtesy of Special:MediaSearch
• Automated descriptions are provided in every language to aid disambiguation. At first the functionality by Magnus is used and it is to be replaced with improved descriptions provided by Abstract Wikipedia
• A Reasonator like display is provided to inform on the data we have on an item.
• Suggestions for the inclusion in categories and lists are provided based on Wikidata definitions for categories and lists.
• To help people find sources, alternate sources, Scholia is included when there are papers about the subject. Once existing citations are available, they are an additional resource

In essence this is a toolset that you can opt into as an individual and/or it is the standard for a project. Particularly for the smaller projects this will prove to be really valuable; it will prevent false friends, it indicates heavily linked items that do not have an article. It stimulates the addition of labels because it is beneficial in finding illustrations. 

This proposal is relatively low tech and it will bring our many communities together by providing widely the information that is available to us.

Thanks,

     GerardM