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Without greater standardisation across practices and controlling for other types of data, it is difficult to produce deeper insight into national and international comparators for open access.

Some data, like the total number of GLAMs nationally, do not (yet) exist. Others are difficult to collect, like technical data on images (e.g., resolution, formats published and metadata scope) or collections level data (e.g., total collections, total digitised collections and the distribution of in-copyright versus public domain for underlying works). Some may produce speculative data or require their own in-depth study (e.g., on main differences in approaches across the GLAM sector, particularly by libraries and archives compared to galleries and museums).

In the UK, most instances of open GLAM appear to publish digital surrogates in low to very low resolution (e.g., at screen display resolution). Data on technical practice could produce meaningful assessments on the quality of assets published and the types of reuse enabled. However, few GLAMs document and/or publish this information or take consistent approaches for legacy reasons. Some limitations may be imposed by platform functionality. For example, Art UK limits images to 1200 pixels on the longest side.

The higher-level data collected by this study remains useful for comparing how GLAMs publish collections, interpret national law and enable reuse, and for identifying gaps.

For example, a glaring gap revealed in the map (see Section 3.2.) is where open access is occurring. Regions with aggregators have higher representation for many reasons, some of which are discussed immediately below. But the data shows GLAMs in the majority of the world (and their publics) are under-represented. This has implications for which countries and institutions are shaping open GLAM, as well as which collections by virtue of open access receive greater public and research attention and whose narratives and knowledge accompany them. To this point, language barriers also may contribute, both to reuse and to data collection, where standardised licences and tools are not used (e.g., Creative Commons) and instead policies must be read and understood in order to appreciate any reuse parameters.



Data aggregators and external platforms collect data from one or more sources, provide some value-added processing, and repackage the result in a reusable form. Examples include Europeana, Flickr Commons and Wikimedia Commons. These organisations have been crucial both for asset publication and for the exposure they bring to collections, as well as for data collection on open GLAM activity (i.e., this study).

Aggregators and platforms offer solutions to institutional barriers and challenges faced by GLAM staff and GLAMs themselves. Some participants mentioned that their organisation’s website lacked the technical capacity to publish or release high quality images due to bandwidth, storage infrastructure and systems within the institution. A website’s interface can be complicated to update and is often bespoke to a GLAM. Layers for rights statements must be maintained internally and built into the interface logic to display on the front-end. Participants noted the complexity of these systems (including the institution itself as a system) makes change slow. Some participants noted seeking funding for GLAM-specific projects to resolve or improve issues, but raised they also can introduce legacy issues, be designed for limited application or, where transferable, be difficult to A Culture of Copyright