Engineering Historical Memory. VISUALISATION SOLUTIONS FOR DIGITAL HISTORY
Engineering Historical Memory (EHM) is an ongoing initiative supported by about 130 scholars and engineers in collaboration with international cultural institutions and publishers. EHM explores the applicability of digital technologies (e.g., data visualisation, federated searches, sentiment analysis, blockchain) to the advancement of learning in historical sciences. EHM tested the results on web-based applications for maps, travel accounts, chronicles, codices, sites, and paintings focusing on Afro-Eurasia during the transition into modernity.
The EHM approach to history can be construed as a hybrid human-machine methodology because it relies on both human scholarly touch and machine computational power. The attributes of the EHM methodology (i.e., set of methods) can be named as follows.
Analytic, because of the scholarly mapping and parsing of information from primary historical sources.
Synthetic, in reason of the interactive visualisation of selected information.
Exploratory, because of the automatic search for online publications, images, videos, and news potentially relevant to the user’s choices.
Aggregative, as far as it allows interactive selections and visualisations of different sets of search results.
Non-narrative in principle, because the organisation of the materials into narratives is up to the user who generates gamut accordingly.
See in particular:
Zheng He's Navigation Chart (ca 1421-1430 CE) aka The Máo Kūn’s Map / Wǔbèi Zhì Chart (offered to the throne in 1628)