Epistolary letter collections are stored in distributed local archives as letters are sent from one place to another. To find and study letters of a particular person or group on a global level, data from different local sources can be aggregated and harmonized into a global knowledge graph (KG). This paper argues that it is important to understand possible quality issues of the global KG that may arise due to the heterogeneity of the local datasets, aggregation process, and mutual linkedness of the local data. For example: In what ways do the local collections enrich each other? How complete is the aggregated dataset? Are there duplicates or misaligned entities and concepts in the aggregate? This paper presents a set of data-analytic tools to address such issues in order to support data literacy in Digital Humanities (DH) research. As a case study, the LetterSampo Finland Linked Open Data (LOD) KG is considered and the results are reported. It aggregates data about almost 1.3 million historical letters sent in the Grand Duchy of Finland (1809–1917) and 118 000 related actors harvested from 18 different archival data sources and 1670 fonds, enriched by data from 12 external databases.