Andrew Lih is Wikimedian at Large for the Smithsonian Institution in the United States and the Wikimedia Strategist for The Met Museum in New York City.
Wiki API Connector aims to simplify the extract-transform-load (ETL) process of metadata to Wikimedia projects without requiring complicated coding or software development. It was originally created as a tool to facilitate the import of Smithsonian Institution images and metadata to Commons and Wikidata (as a Wikibase-aware analog of GLAM Wiki Toolset or Pattypan). With the main core written in Python, the use of a familiar YAML configuration file to map an API's JSON fields to Wikidata properties and items might be a general solution useful for other GLAM entities or partner organizations. This session describes the early work done so far and seeks feedback on how it might be useful for other users and applications.
[pre-recorded] This session covers how The Met Museum has contributed object metadata and depiction information to Wikimedia projects and in return, how Wikidata content is brought back into The Met's database and made available via its open access API. We will discuss our recent work with Structured Data on Commons, including the tools, processes, modeling challenges, and the complexities of using references for SDC. We welcome dialogue and discussion on how to improve these practices.
This session examines and discusses some key Wikidata-driven tools in helping women biography projects for the Women in Red project and the Smithsonian Institution American Women's History Initiative including: * Listeria – the tool for generating worklists from Wikidata, including Women in Red’s Redlists and the Smithsonian's Funk List of women scientists * Infoboxes – how might Wikidata-derived infoboxes be improved on and more widely adopted * Mbabel – tool for one-click creation of draft articles based on Wikidata content * Translation – how might biographies in other language Wikipedia editions be used in translation tools and accessed in Listeria listings, and what is the current status of machine translation * Cradle – forms-based interface for generating new Wikidata items * WEF-Framework (and the challenge of women’s names) * Humaniki – Wikidata-driven statistics for tracking gender gap progress