Sandra Fauconnier

In 2019, Wikimedia Commons is [https://commons.wikimedia.org/wiki/Commons:Structured_data undergoing a major update]: it is now possible to describe files on Wikimedia Commons with [https://commons.wikimedia.org/wiki/Commons:Structured_data multilingual, structured, machine-readable data from Wikidata]. Structured Data on Commons produces new challenges for the Wikimedia Commons and Wikidata communities: how to describe media files properly, how to model the metadata ('ontology') around them? At the moment of submitting this proposal (early June 2019), the communities have brainstormed data modelling and ontology [https://commons.wikimedia.org/wiki/Commons:Structured_data/Properties_table in an on-wiki properties table]. Wikimania 2019 in August is a good opportunity to gather and to look at the current status of data modelling, to pinpoint the most urgent challenges and to brainstorm paths forward.

In 2019, [https://commons.wikimedia.org/wiki/Commons:Structured_data Wikimedia Commons is undergoing a major update]: it is now possible to describe files on Wikimedia Commons with multilingual, structured, machine-readable data from Wikidata. This hands-on tutorial for Structured Data on Wikimedia Commons newbies will teach you, step by step, how to get started with structured data on Commons: how to upload files with structured data, how to edit existing files and add structured data to them, how to search structured data on Commons. If, by August 2019, some nice volunteer-built tools already exist that allow to work with structured data at scale, these will also be demonstrated.

Making assessments about the copyright status of a work remains a challenge notwithstanding the tools that CC has developed over the years, such as the Public Domain Mark and CC0. It is also hard to communicate to end users about the laws that apply to their particular use of a work. Copyright is jurisdiction based, which means each country has their own copyright and public domain rules. These differing laws presents challenges for digitizers of content and reusers of digital online surrogates. Several efforts and projects offer partial solutions for these challenges; however they tend to serve single jurisdiction or regional needs, are loosely coordinated, and are not integrated into a unified solution that works starting from the moment of digitization and continuing through to the public that encounters them over the Internet. Ideally, the public domain is the easiest part of the knowledge commons to assess and reuse, but the current environment makes it challenging at each stage in the process of getting that content to a public. Creative Commons and other key stakeholders such as Wikimedia brought forth this Project for initial discussion with our community and stakeholders at the CC 2019 Global Summit in Lisbon. The outcomes of the 4 hours session at the Summit can be found [https://docs.google.com/document/d/1Sl5eFsodKnw0BWhgyMHuOyU94B4RanjYYsp4IwPm_BA/edit# here]. At this session, we expect to be able to follow on some of the data modelling challenges in relationship with the [https://www.wikidata.org/wiki/Help:Copyrights Help:Copyrights] page on Wikidata. We want to gather feedback and input from the community that is working in the intersection of GLAM institutions and Wikidata. Creative Commons will bring some of its legal expertise on copyright and open licensing, and we expect to engage more with the Wikidata community to leverage the different languages and community needs, and better refine our initial project.

Other people: Maarten Zeinstra Scann Alex Stinson

The importance and the extremely high usage of Wikipedia and the other Wikimedia projects have lead many organizations across the world to think about how they can contribute with information and knowledge, what their role could be in the free knowledge ecosystem and how they can become an active participant. Over the years, many millions of data items and media files have been contributed to Wikidata, Wikimedia Commons and other Wikimedia projects through collaborations between Wikimedia communities and external content partners. However, many potential partnerships are still untapped because of lacking technical infrastructure to support batch uploads and editing, analytics, data synchronization and more. This makes content partnerships difficult to access, especially for less well-resourced communities and content partners. Through the work in the [[m:FindingGLAMs|FindingGLAMs]] project and the [[c:Commons:Structured data|Structured Data on Commons]] project a number of identified problems have been identified and worked on. The aim has been to lay the groundwork for better tools for cultural partnerships. By using these case studies we will discuss what are the most commons problems encountered in the GLAM partnership workflow, and what technical resources are needed to solve them. We will highlight what sustainable and participatory paths we see moving forward and how the wider movement could and should be engaged and how the work can help empower them.

Other people: John Andersson

In 2019, Wikimedia Commons is [https://commons.wikimedia.org/wiki/Commons:Structured_data undergoing a major update]: it is now possible to describe files on Wikimedia Commons with [https://commons.wikimedia.org/wiki/Commons:Structured_data multilingual, structured, machine-readable data from Wikidata]. '''[https://commons.wikimedia.org/wiki/Commons:Structured_data Structured Data on Commons]''' opens many new perspectives for content partnerships and GLAM-Wiki projects that use Wikimedia Commons, including multilingual descriptions and more refined exchange of data between institutions and Wikimedia projects. In the past year, several GLAM institutions and Wikimedia communities have worked on '''[https://commons.wikimedia.org/wiki/Commons:Structured_data/GLAM/Projects pilot projects]''' that explore and demonstrate the intricacies and potential of structured data for GLAM-Wiki activities. After a brief presentation about the new features on Wikimedia Commons, there is a panel and Q&A session, with demonstrations and discussions around these pilot projects.

Other people: Satdeep Gill André Costa