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.
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 Structured data on Commons, 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.
As stated in the previous topic, Structured data on Commons improves accessibility in other languages, thus reaching more users. However, there is still another important way to reach other readers: through accessibility for people with disabilities.
Using Structured data on Commons, it's possible to develop accessibility features, such as structured file captions for media files, to improve and expand access for people with visual impairments who wish to access all content available on Wikimedia (especially on such a visual platform like the Wikimedia Commons), as well as items of GLAM collections.
Like the metadata available on Wikidata, Wikimedia Commons now also has a better system for reading data by machines (or machine-readability) and it's not solely dependent on plain-text descriptions anymore. With Structured data on Commons, metadata from GLAMs related to the media files also become structured, and therefore, readable by machines, part of digital cataloging standards, and more accessible for statistics, analytics, or making different visualizations available (such as graphs, tables, or queries). It also facilitates research and even identifying content gaps.
The machine-readability on-wiki is also extended by the Structured data Across Wikimedia project.
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.
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 Commons, thanks to the new search system, Media Search, which is an image-focused way to find media on Commons, media files that have structured data are more findable and identifiable by readers and editors looking for certain items 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.
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.