We are excited to announce an upcoming collaboration between the Wikidata
development team and data science students from Purdue University. The goal
of this collaboration is to identify and address discrepancies between
Wikidata and external data sources, potentially providing new useful
mismatches for the Mismatch Finder. More details about the project can be
found here: Wikidata:Mismatch Finder/Purdue Summer of Data 2024
For those unfamiliar with the Mismatch Finder
<https://www.wikidata.org/wiki/Wikidata:Mismatch_Finder>, it is a tool that
identifies potential discrepancies between Wikidata items and external
databases, which are then presented to editors for review and correction.
This tool also suggests new statements that should be part of Wikidata, but
need a human-review step before adding them. As part of this project, the
students will work on providing mismatches for the Mismatch Finder and
addressing the discrepancies while receiving guidance and support. All
their work will be open source and released under open licenses.
Your Participation Matters
We seek your active participation in helping us identify data sources that,
when compared with Wikidata, could generate significant mismatches. We are
particularly interested in datasets that are free to use, easily
accessible, and ideally helpful for data that is used on Wikipedia. We have
collected potential data sources that we could work with in T304448
<https://phabricator.wikimedia.org/T304448>, and we would like you to add
more to the list.
Beyond dataset suggestions, we would also appreciate your feedback on what
exactly we should match, as these datasets are often extensive and broad.
If you have any questions, concerns or feedback, please leave us a note on
the project’s talk page: Wikidata talk:Mismatch Finder/Purdue Summer of
Mohammed S. Abdulai
*Community Communications Manager, Wikidata*
Wikimedia Deutschland e. V. | Tempelhofer Ufer 23-24 | 10963 Berlin
Phone: +49 (0) 30 577 116 2466
Grab a spot in my calendar for a chat: calendly.com/masssly
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