This paper describes problems related to contemporary document analyses. Contemporary documents contain multiple
digital objects of different type. These digital objects have to be extracted from document containers, represented
as data structures, and described by features suitable for comparing digital objects. In many archival and machine
learning applications, documents are compared by using multiple metrics, checked for integrity and authenticity, and
grouped based on similarity. The objective of our work is to design methodologies for contemporary document processing,
visual exploration, grouping and integrity verification.