Commons:Structured data/GLAM/Why

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The value of the content shared from the collections of Galleries, Libraries, Archives, and Museums in the Wikimedia ecosystem is already well known, since these items compose and bring reliability to a good part of the pages from the Wikimedia platforms. The value of Wikimedia for GLAMs are also several, especially those that already have GLAM-Wiki initiatives, and it can be extended with the use of Structured data on Commons.

Translatability

One of the main values of Structured data on Commons is the fact that it improves the translatability of metadata from media files, making them multilingual. When metadata is shared in a structured way, it becomes more easily translatable since users only need to translate terms and not entire phrases and contexts.

Currently, MediaWiki works in more than 300 languages. Therefore, with SDC, media files and their metadata become more accessible to people who speak other languages and, within the Wikimedia ecosystem, become even more available to be understood and widely used in other Wikipedia languages, improving the reach of GLAM media files across Wikimedia.

Accessibility

Drawing Lessons in St Augustin Museum - Flickr - AlphaTangoBravo - Adam Baker.jpg

As stated in the previous topic, Structured data on Commons improves accessibility in other languages, thus reaching more people. However, there is still another way to reach other people: through accessibility for people with disabilities.

Using Structured data on Commons, it is possible to develop accessibility features, such as structured file capitions for media files, to improve and expand access for people with visual impairments who wish to access all content available on Wikimedia, as well as items of GLAM collections.





Machine-readability

Like the metadata available on Wikidata, Commons now also has a better system for reading data by machines (or machine-readability). With Structured data on Commons, metadata from GLAMs about the items depicted and their media representation become structured, therefore, more readable by machines and even properly enter digital cataloging standards, such as the MARC (machine-readable cataloging) standards, and become more accessible, especially for digital extraction, researches, and even to graphical and tabular views or queries.

The machine-readability on-wiki is also extended by the Structured data Across Wikimedia project.

Connectivity

State Library of Victoria La Trobe Reading room 5th floor view.jpg

Structured data on Commons also facilitates connectivity and information convergence. Items, together with their media files and metadata from different creators, countries, movements, and periods all become more interconnected in just one place, Wikimedia Commons, thanks to the data shared in a structured way.

In this sense, not only the works, but also GLAM institutions and their collections become more interconnected to the Wikimedia ecosystem and the internet in general, building an entirely more knowledge-focused, connected, complete, and accessible environment for readers, users, and heritage institutions.

Findability

Promoting a more interconnected ecosystem and with good quality structured metadata available, Structured data on Commons also supports better file findability across the Wikimedia platforms. On Wikimedia Commos, thanks to the new search system, MediaSearch, which is an image-focused way to find media on Commons, items that have structured data are more findable and identifiable by readers and editors looking for certain media files and what is depicted in them.

Structured data on Commons will also promote better findability on various Wikipedia languages, once the Structured data across Wikimedia project is fully accomplished.

Usability

As Structured data on Commons supports better findability, it also promotes greater usability across Wikimedia projects, such as the use of images in Wikipedia articles in several languages. This will be specifically developed further through the Structured data across Wikimedia project, which will allow machines to recognize Wikimedia content and suggest relationships to other Wikimedia content, such as across the various Wikimedia platforms, through the image recommendations project.