11.2 The GND initiative 2017-2021: Developing a Backbone for the Web of Cultural and Scientific Data

Combing data beyond the boundaries of systems and domains is the major concern of the linked data movement. One serious problem for the semantic web is dealing with reliability: Can the data be trusted and do processes exist that guarantee a high data quality? Of the same importance is sustainability: Is a resource stable enough to be citable, or will it be gone at some point? These questions are of special importance in the context of research, where citability is essential, and for higher-level services that are based on this kind of data. While it is not necessary for every dataset to provide a maximum degree of reliability in order to be useful, we believe that in the heart of the linked data web a reliable and stable core is needed, a backbone of trust, and that cultural heritage institutions are in a unique position to provide parts of this core: connecting their local knowledge bases could lead to a huge graph of cultural and scientific information that is both reliable and persistent.

Especially authority files like the “Gemeinsame Normdatei” (GND) make up the perfect bridges and stable anchors for cross-domain connections. Various museums, archives, research organizations and other partners outside the library domain (like Wikipedia) already contribute to the GND and it is widely connected to diverse datasets and collections all over the world. But there is still much to be done to implement our vision of a cross-domain cloud-based interlinking platform. The organization, rules, services and infrastructure around the GND need a complete revision to deal with the quickly growing network and to reconcile the requirements of the heterogeneous domains and disciplines. Further challenges are the strengthening of the support for the management and visualization of semantic connections, the integration into global data generation processes, as well as the utilization of improvements in the area of data analysis and machine learning (datamining). Together with the GND partners, the German National Library will start an initiative to move the GND to the next level. By 2021, the GND is to be gradually modernized, reorganized and expanded. In this lecture, we will line out the key opportunities and challenges and the highlights of our approach.