From one GLAM CSV + photo collection , create a unified workflow using quickstatements + pattypan to upload everything in Commons and Wikidata in a user-friendly way
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The tool I was referring to that is 's an extensible open source web-app for transforming datasets and uploading data and media to online repositories.' is GLAMpipe:
http://glampipe.org/
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So, I have extracted a dataset consisting of 750 something old prints (end production date <1870) from the collection of our National Museum for Folk Culture.
.csv attached.
What I need help with now:
- it needs to be cleaned because there is sensitive data in there that can not be published on Wikidata (insurance value etc.), but Open Refine is giving me a hard time just separating the columns
- the file contains the image urls that are on our image server and need to be downloaded from there, but I do not know how to do this either.
So, can you help me? Or we can just start working on it together.
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From my understanding OpenRefine can help us for some of the task. We are lacking good documentation of OpenRefine. We might want to document OpenRefine for our usage.
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Bot by Rama to create Wikidata ID and Commons informations about one file of artwork picture
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Since OpenRefine already generates the QID of the items generated we don't need to do dev work, "only" to create a very user-friendly help page that details every step for GLAM institutions and Wikimedia photographers.
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Removing task assignee due to inactivity, as this open task has been assigned for more than two years (see emails sent to assignee on May26 and Jun17, and T270544). Please assign this task to yourself again if you still realistically [plan to] work on this task - it would be very welcome!
(See https://www.mediawiki.org/wiki/Bug_management/Assignee_cleanup for tips how to best manage your individual work in Phabricator.)
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I'm doing some cleanup of OpenRefine task in preparation for new development related to StructuredDataOnCommons (see this page for more context). As this task seems abandoned, I'm taking the freedom to close it. Feel free to re-open if I did this by mistake.
Do note that the new Structured Data on Wikimedia Commons features of OpenRefine (to be deployed around end 2021 and mid 2022) may be suitable for the use case mentioned in this task.