Libraries and museums around the globe are transforming their catalogs and records into Linked Data to foster linkage and navigation across data silos. This in return significantly enriches their own assets with valuable information stemming from related sources. The result is a large Knowledge Graph of cross-linked resources typically based on standards such as RDF or OWL. However, navigating and querying large graphs is challenging. Sure, many retrieval tasks are best served by standard user interfaces based on forms and fields. Despite that data providers and users often complain about poor tool support for explorative navigation through complex cross-linked library data. In fact, there should be something in between query forms and SQL/SPARQL query syntax. We will discuss tool support for visually analyzing and querying large LOD volumes with the help of example data from museums and the scholarly domain for providers and users. This includes interactive network rendering approaches, faceted search and other visualization paradigms that promise to ad hoc understand, analyze and track graph-based data as a whole. Relevant benchmark criteria in this respect are among others: - Scalability of visualization approach and user orientation (data provider & user) - User guidance during data exploration (data provider & user) - Support in detection of data patterns or flaws to increase data quality (data provider) - Presumed knowledge of the data schema or query languages (user).