Last week, I attended a European Science Foundation (ESF) Exploratory Workshop on Conceptualising European Landscapes Across Languages, Cultures, and Disciplines. The workshop took place in the Spanish mountains west of Madrid in the small town of Las Navas del Marqués. The venue was the fascinating Castillo-Palacio de Magalia, which (if I understood the tour correctly) was built in the late 16th century and then extensively remodelled by Franco as a retreat or headquarters for the women’s arm of the Falange. The building itself was beautiful and we were also very well (over)fed!
The format of the workshop consisted of two days of papers (including a long siesta each afternoon), followed by two broader discussion sessions on the final morning. Papers were presented on a variety of subjects, with particular themes developing around the meaning of the term “landscape” and the linguistics of landscape terminology. There were a number of papers from members of the LACOLA project at Lund University, which is another landscape-themed ERC project that began shortly before our own, albeit focused on linguistics rather than archaeology.
One idea that was introduced (by Zsolt Molnar) that I think might have particular application to archaeological models / narratives was that herders mentally classify their landscape based upon a minimum unit size equivalent to the spatial extent of a herd / flock. It seems to me that this might be a useful way to approach the definition of the minimum spatial resolution for study of past pastoral practices.
My own paper discussed my past work (available as a BAR: S2234) on mapping the uncertainty of archaeological dates, and how we might bring an element of this into the synthesis methodology we are currently intending to use for this project. It is a weakness of our current model that it can only express the temporality of data based upon period classifications, but there is potential for building probabilistic calculations of date into this. In essence, this would consist of dividing our study period up into time slices and then calculating the percentage probability of each type of site falling within each grid square for each time slice.
The question then is how we assess probabilities where there is more than one of each site type within a particular square: as we are assuming that most multiplicity is in fact duplication, I would think that the most appropriate answer would be to take the highest probability as being the most valid, rather than adding or multiplying probabilities (which would speak of slightly different things). However, my ideas on this front are still very vague… I hope to develop them further soon.
Overall, the workshop was a worthwhile (and enjoyable) experience and we would hope as a team to maintain links with the people involved, as we progress through our own study of the landscape in the past.