FindingGLAMs/White Paper

Expanding what is possible around GLAMs on the Wikimedia projects
A White Paper as Guidance for Future Work
developed as part of the FindingGLAMs project

• Background
• Case Study 1: FindingGLAMs
• Case Study 2: SANG
• Case Study 3: WORD
• Case Study 4: DOCS
• Case Study 5: EMPOWER
• Case Study 6: ORDER
• Case Study 7: AROUND
• Conclusions

You can find a print-ready version of this document on Wikimedia Commons.

= Background =

• 
  Embroidered map sampler (1783). Many GLAMs collaborate with the Wikimedia community to share their collections. Among them is the Metropolitan Museum of Art with several hundred thousands images on Wikimedia Commons.

FindingGLAMs

FindingGLAMs was a project by Wikimedia Sverige in collaboration with UNESCO and the Wikimedia Foundation, with generous funding from the Swedish Postcode Lottery Foundation. It ran from August 13, 2018 to February 29, 2020.

The overarching goal of the project was to improve the representation of the world’s cultural heritage institutions – Galleries, Libraries, Archives and Museums (GLAMs) – and their collections on the Wikimedia platforms. We initiated several types of activities within the project to achieve that goal; one of them was adding structured data about GLAMs to Wikidata to make it fast and easy to find them, which gave the project its name.

We embarked upon this project in hopes of laying the foundation for long-term and sustainable collaboration between cultural heritage institutions and the Wikimedia movement (the global community of contributors to Wikipedia, Wikidata and other projects hosted by the Wikimedia Foundation). That is why a large part of FindingGLAMs was done together with our GLAM partners and their collections, with an eye on identifying problems, challenges and possibilities for improvement. In this white paper, we present what this work has taught us about the technical infrastructure for content partnerships in a number of case studies.

These case studies and the experience we have gained in the process will allow us to reduce the time and learning curve needed to share content from institutional partners in the future and greatly enhance the amount of high quality knowledge that can be made available to the general public through the Wikimedia platforms.

For a more detailed overview of the other activities included in the FindingGLAMs project, apart from the GLAM content uploads, see Case Study 1: FindingGLAMs.

Structured Data on Commons are opening up new opportunities

Structured Data on Commons (SDC) is a project that provides the technical infrastructure to complement the wikitext, templates and categories on Wikimedia Commons with structured data, which is machine-readable, queryable, straightforward to add and edit, and multilingual (currently up to 300 languages). This will make media files much easier to describe, discover, understand and analyze. This project is being developed by the Wikimedia Foundation and the first functionalities were enabled to the public in January 2019. The team working on this project was also developing case studies and coordinated the work with the FindingGLAMs project.

Case Study 6 describes Structured Data on Commons in the context of a GLAM collection and explores this technology in more detail.

Standing on the shoulders of giants

Wikimedians have collaborated with GLAM institutions for a long time. Synergies between the two sectors feel natural, unavoidable even. The Wikimedia community works towards making the world's knowledge available for everyone, and it is the world's libraries, museums, galleries and archives that for centuries have been safeguarding and sharing knowledge. At the same time, it is in the interest of GLAMs to reach wider and more diverse audiences. Wikipedia being one of the world's most popular websites, it is a superb platform to target. Some GLAMs are famous worldwide, but for the majority of them, attracting audiences outside their home countries or regions is a challenge. For them, the access to a free, multilingual platform with a worldwide readership is invaluable.

Some GLAMs, educational institutions and similar organizations employ Wikimedians in Residence – experienced members of the Wikimedia Community who serve as liaisons between the organization and the open knowledge movement. By supporting the organizations in sharing their resources under open licenses and educating them about the Wikimedia platforms, Wikimedians in Residence build mutual understanding and lay the foundation for sustainable, long-term collaboration between the organizations and the Wikimedia movement. The first assignment of this type took place at the British Museum in 2010; since then, over 150 organizations around the world have welcomed Wikimedians in Residence, including the US National Archives, the National Library of Israel, the Bodleian Libraries and the National Museum in Warsaw. While most of these have been short-term assignments, there are also some long-term collaborations; UNESCO has had a Wikimedian in Residence since 2015.

The global GLAM-Wiki initiative connects Wikimedians working together to support cultural heritage institutions who want to work with Wikimedia to produce open-access, freely-reusable content for the public. One of their tasks is documenting the GLAM collaborations taking place around the globe to provide examples of what can be done with the Wikimedia platforms and to inspire both Wikimedians and GLAMs to work with free materials.

The Metropolitan Museum of Art in the United States is an example of a successful partnership between a high-profile cultural institution and Wikimedia. In 2017, the museum launched their Open Access Policy, putting over 406,000 images of public-domain artworks under the CC0 waiver. This is the most generous of the Creative Commons tools, enabling anyone to freely copy, modify and distribute the materials, including for commercial use. Those images were then uploaded to Wikimedia Commons by a Wikimedian in Residence.

A year later, it was clear that the resources shared by the museum were very popular. The nearly 4,000 images included in Wikipedia articles were reaching 10 million viewers per month. What was particularly interesting is that the most popular artworks reached a much larger audience through Wikipedia than through the museum's own website; a third of that audience came from Wikipedia articles in languages other in English. One of the world's most famous museums still benefited tremendously from sharing their materials on open platforms.

On the other end of the GLAM-Wiki spectrum, there are initiatives by the Wikimedia community to better describe the world's cultural heritage. A notable example is the Sum of All Paintings project, aiming at creating a Wikidata item for every notable painting in the world. This covers every painting in the collection of a notable institution or created by a notable artist: an ambitious scope. The project coordinates the efforts of Wikimedians across the globe who collect information about open-access data on artworks and work together to upload it to Wikidata and improve it. Institutions that have released such data include the Finnish National Gallery, the Tate Gallery and the Minneapolis Institute of Art.

Other Wikimedians are collaborating to improve the information about cultural heritage institutions and increase its re-use on Wikipedia. The Sum of All GLAMs project was carried out by the Wiki Movement Brazil User Group in collaboration with OpenGLAM CH, with the goal of laying the foundations for an international knowledge base for heritage institutions. An important part of the project was examining and improving the data modelling standards for cultural heritage institutions. Another was the implementation of Wikidata-driven infoboxes on Wikipedia in various languages, making it possible to quickly create articles with essential information from Wikidata. The WikiProject Heritage Institutions is an informal initiative on Wikidata dedicated to the coordination of activities regarding heritage institutions, including the Sum of All GLAMs and FindingGLAMs projects.

The Sum of All GLAMs project had similar goals as Wikimedia Sverige’s FindingGLAMs, but a different focus; for example, we chose not to work on implementing Wikidata-driven infoboxes, and put more emphasis on rapid data ingestion through dataset uploads and crowdsourcing rather than on data cleansing and modelling issues. Our similar ambitions, as well as the fact that the timelines of our projects partially overlapped, lead to many interesting discussions and exchange of experiences. If anything, two projects focused on GLAMs in Wikidata running in parallel increased the visibility of this subject matter among the Wikimedia community, shining the light on the many problems to tackle and the different ways for volunteers to get engaged.

Why Case Studies?

Wikimedia Sverige has a decade of experience of content partnerships. What we have learned from uploading materials to Wikimedia Commons and Wikidata on a large scale is that while every GLAM and every collection is unique and idiosyncratic, they have a lot in common. By studying real life projects, we hope to highlight the challenges and problems that Wikimedians – both independent volunteers and affiliates – face when working with the different types of content that cultural heritage institutions collect and share. We also hope that our experiences will be interesting and helpful for cultural heritage institutions engaged in, or considering getting engaged in, collaboration with the open knowledge movement.

Method for choosing Case Studies

Our intention in selecting the case studies was to represent the breadth of material that Wikimedians encounter in their work with content shared by GLAM institutions. We were particularly interested in exploring media and data types that are less straightforward to work with than a “typical” GLAM collaboration e.g uploading a number of digitized artworks to Wikimedia Commons.

The purpose of this white paper is not merely to describe our projects, but, most importantly, to highlight the problems and challenges that need to be solved in order to strengthen the technosocial infrastructure of content partnerships. That is why we decided to engage in projects that were new to us, with an emphasis on new and imperfect technologies, such as Structured Data on Commons and Lexicographical data on Wikidata. We believe that using those technologies to solve real life problems can provide valuable guidance for their development.

Finally, the choice of case studies was heavily influenced by our GLAM partners and the material they could provide while the FindingGLAMs project was underway. We actively approached a number of partner organizations we have previously worked with and asked if they had specific content they wanted to share, offering our support in the cases when they did. This in itself was valuable as it renewed contact and allowed us to deepen our relationship with a number of important cultural heritage institutions in Sweden.

References