Visual Analytics for the image archive of the German Colonial Society (VaBiKo)

位于法兰克福的约翰·克里斯蒂安·森肯伯格大学图书馆的德国殖民学会图像档案馆收藏了德国殖民机构最重要的照片和出版物之一，其中包括大约55,000个图像载体。然而，目前，德国殖民协会图像收集的数字化版本在目前的质量标准下是不可用的，并且图像的可检索性受到不完整元数据的限制。这严重限制了研究人员对图像集合的使用。拟议的项目解决了这些问题，旨在为研究人员显著改善德国殖民学会图像档案的访问和可用性。加强对学术内容的获取将为继续重新评估德国殖民历史奠定基础。通过对图像内容的全面半自动索引，将大大扩展文档。在此过程中产生的额外元数据将有助于提高图像馆藏的可搜索性。该项目将持续提高图像收集的可见性和可寻性。此外，该项目将解决与使用这些藏品有关的伦理问题。现有的界面将被开发成一个多语言的门户网站，用于图像（和文本）馆藏的交互式语义搜索。研究过程将通过以下功能得到支持：-增强探索和展示选项；-使用深度学习技术改进图像馆藏的可搜索性和历史图像源的索引；-空间和时间信息的交互式可视化，以及基于相似性的图像分组和历史幻灯片的图像和文本链接；-根据现行标准增强数据管理，包括改进互操作性（接口和api）。

The image archive of the German Colonial Society at the Johann Christian Senckenberg University Library in Frankfurt houses one of the most important collections of photographs and publications of German colonial institutions, comprising approximately 55,000 image carriers. However, at the moment, the digitized versions of the German Colonial Society image collection are not available in current quality standards and the retrievability of the images is limited by incomplete metadata. This severely limits researchers’ usage of the image collection. The proposed project addresses these concerns and aims to significantly improve access and usability of the German Colonial Society's image archive for researchers. Enhanced access to content for scholarship will lay the foundation for the continued reappraisal of German colonial history. The documentation will be significantly expanded through comprehensive semi-automatic indexing of the image content. The additional metadata generated in the process will serve to improve the searchability of the image holdings. The project will sustainably increase the visibility and findability of the image collection. In addition, the project will address ethical issues related to the use of the collection. The existing interface will be developed into a multilingual portal for interactive, semantic search in image (and text) holdings. The research process will be supported through the following functionalities: - Enhanced exploration and presentation options; - Improved searchability of image holdings and indexing of historical image sources using deep learning techniques; - Interactive visualizations of spatial and temporal information as well as similarity-based grouping of images and the linking of images and text for the historical slideshows; - Enhanced data management according to current standards including improved interoperability (interfaces and APIs).