histoGraph is a web platform designed to help researchers to explore large multimedia archives. In this article we briefly introduce the functionality of histoGraph, a technical demonstrator exploiting the surplus value of human touch for the identification of identities in historical image collections through a hybrid crowd-sourcing approach. In Network visualization for Digital Humanities we can distinguish between two general perspectives: visualizations can be used to illustrate specific insights based on existing knowledge or to explore data and to discover something that is not yet known.
Within this larger concept of visual analytics we can see two perspectives: one that stipulates the idea of a holistic or “bigger” picture, so that we can gain insight by combining different information into one image (seeing the forest for the trees) and one that focuses on identifying the peculiar in a massive amount of information. We propose to build a bridge between the two: on the one hand an analytical tool to identify peculiarities and on the other an authoring tool for visual storytelling. This would offer us an interesting cross-connection with the idea of enhanced publication as it is understood by the Driver project.
histoGraph was developed by the FP7-funded project CUbRIK which focused on advanced multimedia search technologies. Alongside an app for exploring and searching fashion, histoGraph is one of two demos which implement the different modules.