Data visu­al­isa­tion has become very vogue in the digital human­it­ies com­munity. Although there have been a scat­ter­ing of brave prac­ti­tion­ers over the past few years, only very recently has this inter­dis­cip­lin­ary area star­ted to fea­ture prom­in­ently at DH con­fer­ences as a main­stream prac­tise worthy of consideration.

For the last few months I have been look­ing for an oppor­tun­ity (i.e. a bit of time) to delve into R and Pro­cessing, spe­cific­ally with an eye towards tak­ing some exist­ing visu­al­isa­tions I am work­ing on to a new level.

The first book of interest is R in a Nut­shell by James Adler recently pub­lished by O’Reilly.

R is a lan­guage and an envir­on­ment to sup­port data ana­lyt­ics and visu­al­isa­tion. Its approach­able, extens­ible and open source. One of the advant­ages of R over other comers is the num­ber of rather pol­ished inter­pret­ers avail­able for it and some of the great examples float­ing about that have been con­struc­ted in R. Hence my interest. I come to this interest from a digital human­it­ies back­ground and wondered whether the lan­guage could be of use for work­ing with my own data com­ing from farm diar­ies explor­ing the cycle of sea­sonal farm activities.

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