Digitality is a cause and a consequence of different data cultures. It applies to the 10 research projects that are included in this volume. They are rooted in various humanities disciplines such as art history, philosophy, musicology, religious studies, architectural history, media studies, and literature studies. As diverse as the disciplines are the objects and their formats, which are the subject of this book. The cultural data of the projects include recordings of music and spoken word, photographs and other types of images, handwriting, typoscripts and maps. The oldest material dates back to 500 BCE, followed by medieval times, the 18th and 19th centuries, early 20th century and the present. All projects share that they study their material with digital methods, although digitality comes into play at different moments and layers in each of the projects. Hardly readable manuscripts from the 18th century have to be treated with specialized OCR-methods while Plato’s texts are already available in digital form, and therefore open up other affordances for analysis. Special analysis possibilities had to be developed for certain image sources. For all projects, however, it is equally true that only the digitization of the objects makes them accessible to the methods that are the subject of this book. @en

Information on the history of architecture is embedded in our daily surroundings, in vernacular and heritage buildings and in physical objects, photographs and plans. Historians study these tangible and intangible artefacts and the communities that built and used them. Thus valuable insights are gained into the past and the present as they also provide a foundation for designing the future. Given that our understanding of the past is limited by the inadequate availability of data, the article demonstrates that advanced computer tools can help gain more and well-linked data from the past. Computer vision can make a decisive contribution to the identification of image content in historical photographs. This application is particularly interesting for architectural history, where visual sources play an essential role in understanding the built environment of the past, yet lack of reliable metadata often hinders the use of materials. The automated recognition contributes to making a variety of image sources usable for research.

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