Exploring cultural heritage with a set-based space-time cube

Since the creation of digital cultural heritage collections like Europeana, Trove, and Digital Public Library of America (DPLA) many art objects become available via the internet to its users. This gives the users the ability to view items which are not displayed in the museum, either because they are stored in a safe, under reconstruction or simply not in any physical exhibition. The questions if the collection is accessible enough for all users is still unanswered. Many of those collections are difficult to explore and targeted towards experts looking for specific items. Europeana, for example, has more than 50 million objects in its digital collection, which also makes it a big data challenge. This work aims to provide a detailed overview of current visualization techniques in the domain of cultural heritage. By including different set-based visualizations in this research, fitting techniques will