Charles Joseph Minard’s visualization of the Napoleonic Army’s advance and subsequent retreat from Russia in the 1812-13 campaign is widely cited as one of the most effective graphical depictions of data drawn from statistical sources (see Fig. 3). The thickness of the line indicates the strength of the army during its peregrinations back and forth across Europe whilst the lower graph maps those fluctuations against the recorded temperature on the return leg of the march.
The clarity of information that this graphical display imparts is an impressive model of what visualization can achieve and is a useful benchmark for the type of digital output that it might be possible to create for various forms of historical data.
The Visual Spatial Technology Centre (VISTA) at the University of Birmingham is one of leading centres in the UK for visualization research and one of the many activities that it supports is the Medieval Logistics project. During a recent Methods Network meeting, Helen Gaffney laid out some preliminary ideas for a visualization of the catastrophic defeat of the army of Emperor Romanus IV at Manzikert in 1071. Using data from: settlement land use; known historical logistics issues; and ecological, environment and terrain data, she proposed a vizualisation that encompassed a variety of aspects of decision theory (including network, game and optimal foraging theories) in order to elucidate the defeat of the Emperor’s army at the hands of the less numerous Turkish forces.
Other initiatives in development at Birmingham include a project to investigate and visualize how drapery and adornment in the classical period would have affected movement and interaction between figures; and another demonstration involved the 3D visualization of the contents of a Canopic jar, which is thought to contain a human liver. This kind of work marks out territory shared by historical studies and the cultural heritage sector and in terms of the cross-disciplinary sharing of tools, it is clear that methods employed by curatorial and conservation professionals, not least in how to describe objects effectively (using tools such as the CIDOC-CRM ontology), could be of enormous value to historians.
The Wroxeter Hinterland Project, also based at the University of Birmingham, is a useful example of a project that employed an arsenal of tools to interpret the remains of a Romano-British urban archaeological environment.
[quote]An international team of archaeologists is carrying out the total exploration of the city by non-destructive remote sensing methods, including magnetometry, resistivity, electrical imaging, seismic scanning, ground probing radar, airborne hyper- and multi-spectral scanning, and satellite imaging.
The University of Birmingham, The Wroxeter Hinterland Project, (http://www.iaa.bham.ac.uk/bufau/research/wh/Base.html)[/quote]
Archaeology as a discipline is generally credited as having had more exposure over a longer period to technological means of research than most other arts and humanities subject areas and as such, represents an enormously useful pool of expertise for colleagues in neighbouring areas of historical research who are looking for new ways of analysing data in their area of research. Another centre of expertise is the King’s College Visualisation Lab, who are involved with a range of 3D visualization projects that attempt to map internal and external spaces using historical data sources to define verisimilitude as far as possible with the original environments.
[img_assist|nid=207|title=Fig. 4 Reconstruction of Inigo Jones' Barber Surgeons Anatomy Hall, 1636|desc=|link=node|align=center|width=600|height=450]
Using 3D Studio Max and other tools, stunning results are possible that give fresh insights into how historical spaces were perceived and used and a recent initiative called the ‘London Charter’ is an acknowledgement that the visualization community requires standardised methods for documenting working practices.
At a more accessible level for the individual scholar, devices such as timelines, lexis pencils, graphs and cluster dendrograms are all examples of data visualization tools.