There are a number of books analysts can rely on if they need to identify and classify what historic architecture has been made of, physically, over time: dictionaries in which shapes and their successive specific combinations are named. There are also a number of books analysts can rely on if they need to spot and name the time slots to which pieces of historic architecture can be connected with.

And finally there are some books that relate changes in shapes over time to a context, and thereby provide means for analytical reasoning: a typical example is Viollet Le Duc’s encyclopaedia of architecture.

But in all three cases, graphics used to support the authors’ thesis almost never fully integrate the time parameter and the spatial features. They rather put them side by side, like in the classic timeline+ cartography paradigm, or provide low-level indications (with a limited number of variables taken into consideration) like in the typical map+arrows or map+layers paradigms.

And today, with computer platforms, what solutions can we rely on if we need to understand and represent the patterns of diffusion of an architectural trend, in time and space? Animation techniques, where time is one way or another mapped by time? These techniques are well suited for following trends and movements, but they also have proven inefficient in supporting analytical reasoning and explorative tasks.

Our claim is analytical reasoning on spatio-temporal diffusion patterns requires a step into abstraction that traditional figurative solutions like maps or 3D virtual models can’t offer.

Instead, we investigate how recent solutions stemming from the fields of Information visualisation and visual analytics can reveal these patterns, and more generally can support some important background tasks researches carry out when analysing the evolution of historic architecture, such as: relate findings on individual cases to general knowledge, underline contradictions, oddities, local architectural inventions, foster the understanding of the individual’s position with regards to trends at that time and that place, etc.

The contribution presents classic or emergent visual tools (namely, timelines, small multiples, time wheel, concentric time, multidimensional icons, feature lines) and demonstrates that combining them is a necessity when facing historic architecture datasets and related analytical reasoning tasks.

It introduces five combinations that have been implemented on a test case – Z.Dmochowski’s architecture of Poland (a respected classification of architectural facts & trends in Poland over a millennium, that combines morphological, stylistic and functional division lines) – and evaluated. The contribution presents pluses and minuses of these combinations, the arguments behind their making, how they have shed (or not) a new light on the test case.

Finally, the contribution discusses from a practical point of view how the specificity of the data handled in historic sciences can be taken into consideration in the visual analytics process, what techniques can be truly misleading irrelevant in that application context (typically, cleansing or clustering) and whether or not our point – a step into abstraction helps gaining insight into spatio-temporal diffusion patterns in historic architecture - has been made or not.