North Northumberland case study area visit

As we are rapidly approaching the second half of the second year of the project, data collection for the English Landscapes and Identities project has now practically reached its end. Whilst Chris Green spends his time pondering temporal fuzziness and creating nationwide trend surfaces (well, in between hanging out with surfer dudes on a beach in Western Australia…), Zena, Anwen, Laura and myself are starting to focus in earnest on our case study areas. Here is our most up-to-date map with the latest case study areas highlighted, now displaying a clear preference for random transects across various landscape zones:

Case study areas EngLaId, March 2013
Case study areas EngLaId, March 2013

Unlike the national survey, which will use data in an uncleaned format, we intend to work with ‘clean’ data-sets for our case study areas. We are still developing the cleaning methodology at the moment, which should hopefully be finalised by the time Chris Green is back from Down Under.

In the mean time, I decided to go on a little field trip to the North Northumberland case study area. The current area is depicted in more detail below, cutting across the upland zone of the Northumberland National Park as well as the more low-lying coastal zone:

Northumberland case study area: modern land use
Northumberland case study area: modern land use

Those that know the region will immediately see that this area includes a number of recent and ongoing projects that fall within the broad EngLaId period, such as recent work at Yeavering (http://www.gefrin.com/), Bamburgh (http://www.bamburghresearchproject.co.uk/), quite a few sites covered by the Historic Village Atlas (http://www.northumberlandnationalpark.org.uk/understanding/historyarchaeology/historicvillageatlas) and the Discovering our Hillforts Heritage project (http://www.northumberlandnationalpark.org.uk/understanding/historyarchaeology/hillfortheritageintroduction), but also, of course, the fantastic discoveries made by Archaeological Research Services at Lanton Quarries (http://www.archaeologicalresearchservices.com/lantonwebsite/index.htm).

The rationale behind the field trip was therefore two-fold. First, I wanted to familiarize myself with the landscape of this region of England – which, in terms of the coastal landscape at least, is not entirely dissimilar to my native country the Netherlands (note the particularly ‘prominent’ contours on the photo below…). (Once you turn around and go inland, though, the landscape looks totally different – too many hills!)

Holy Island, as seen from the tidal causeway
Holy Island, as seen from the tidal causeway

The second reason for my trip was to talk to as many people as possible about the archaeology of the region, trying to identify possible collaborations or at least shared interests. A big Thank You must therefore go to staff and students at the Department of Archaeology at the University of Durham, for organising a seminar where I could present the EngLaId project and discuss methodologies and ideas. In particular, I would like to express my gratitude to Rosemary Cramp, Sarah Semple, Tudor Skinner, Brian Buchanan and Sofia Turk for their feedback and suggestions.

The following day, I had a very informative discussion with Rob Collins, FLO for Northumberland, who showed me some really cool finds including a recently conserved ritually destroyed sword from a potentially new Anglo-Saxon cemetery site. Over the days that followed, I went out to visit two potential new Anglo-Saxon cemetery sites in the case study region, and looked at their wider landscape setting – for obvious reasons I won’t be able to show any photos here, but it was interesting to note some clear similarities between the two sites.

Following my meeting with Rob, I had a discussion with Sam Turner of Newcastle University about the use of Historic Landscape Characterisation. Although HLC is obviously first and foremost a planning tool, and therefore not optimally designed for academic research, we agreed that it’s use is nevertheless important, as the early medieval period remains frustratingly hard to detect in the archaeological record. To give an example, below is a pie chart detailing the relative quantities of entries relevant to the different EngLaId periods as detailed in the Northumberland HER, with the early medieval period representing only 6%:

Northumberland case study area: HER data by period
Northumberland case study area: HER data by period

And here is another one, this time comparing entries from the National Record of the Historic Environment:

Relative number of entries for each EngLaId period from the National Record of the Historic Environment for the Northumberland case study region
Relative number of entries for each EngLaId period from the National Record of the Historic Environment for the Northumberland case study region

As Rosemary Cramp stated after my presentation in Durham, the under-representation of the early medieval period is of course to a degree caused by the fact that the interest in the early medieval period in this part of the country is relatively recent, at least compared to antiquarian and earlier 20th-century archaeological interests, which focused largely on surviving prehistoric earthwork sites in the National Park. It will be interesting to compare this pattern to other parts of the country, especially those away from upland regions with good survival of earthworks.

One glimmer of hope for the early medieval period is provided by Rob Collins’s work within the PAS, as here, the data-set for the case study area comprises no less than 42% early medieval records! However, with a grand total of 51 finds in total (compare to several thousands for the Humber case study area, for example), much more metal-detecting and reporting remains to be done here.

PAS finds for case study area by period
PAS finds for case study area by period

Over the weekend, I spent some time visiting the Cheviot hills to explore the landscape around the two aforementioned cemetery sites, as well as the better-known landscape around Yeavering, climbing the Iron Age hillfort of Yeavering Bell to obtain a better picture of the royal palace site Ad Gefrin.

The eastern end of Ad Gefrin (the yellow field in the centre of the image), as seen from the eastern end of Yeavering Bell
The eastern end of Ad Gefrin (the yellow field in the centre of the image), as seen from the eastern end of Yeavering Bell
Yeavering Bell, as seen from Ad Gefrin
Yeavering Bell, as seen from Ad Gefrin

It was interesting as well to see some relict field systems on the slopes in the Cheviots from Yeavering Bell.

Cheviot Hills as seen from Yeavering Bell looking south, with faint traces of relict field system visible
Cheviot Hills as seen from Yeavering Bell looking south, with faint traces of relict field system visible lower down the north-facing slope, just below the darker vegetation

On Monday morning, Graeme Young of the Bamburgh Research Project was kind enough to come meet me for a chat and a tour around the castle and the excavation trenches (now covered in tarmac). It was very informative and inspiring to hear him talk about the project, and many thanks must go to him for taking the time off to come down despite the weather getting noticeably worse!

Hope-Taylor's old trenches reopened
Hope-Taylor’s old trenches reopened
Site of an early medieval coastal cemetery, as seen from Bamburgh Castle
Site of an early medieval coastal cemetery, as seen from Bamburgh Castle

That evening the rain and sleet started coming down in earnest, so it was good timing to have a HER visit arranged afterwards, where I went through a pile of grey literature to get a general sense of what was going on and request copies of a selection of reports, focusing on those which reported on relatively large-scale investigations. Many thanks must go to Liz Williams and other HER staff for arranging a desk, answering my questions and providing endless cups of tea!

The course of the Roman road known as the Devil's Causeway
The course of the Roman road known as the Devil’s Causeway

All in all, a very fruitful visit that resulted in a lot to think about, the most important conclusion I could draw from it probably being the importance of talking to local archaeologists. No matter how much the digital era has revolutionized the archaeological practice, local in-depth knowledge remains vital to our understanding of the past.

Fuzzy time (and the PAS)

We’ve been thinking recently about why and how we might apply the concept of temporal fuzziness (uncertainty) to our data, particularly because it is a research interest of mine (see Green 2011 for more details).

The reason why dealing with temporal fuzziness is important is well illustrated by the following graph, based upon the work of Frédéric Trément.  The graph shows how a dating of this villa site based purely upon the well-dated finewares would disguise the fact that the villa was very active into the fifth and sixth centuries, which actually account for the greatest amount of coarseware pottery.  If you ignore the coarsewares because of their poor dating, thus, you produce a false narrative of the history of activity on the site.

Comparison of fineware and coarseware dates from the villa site at Sivier, France (redrawn from Trément 2000 - Fig 9.16)
Comparison of fineware and coarseware dates from the villa site at Sivier, France (redrawn from Trément 2000 – Fig 9.16)

One way in which we can include less closely dated material in our analyses is to take account of temporal fuzziness.  In essence, this means defining a set of sub-periods and then calculating the probability (as a percentage in this simplest instance) of each object in the dataset falling within each sub-period.  This is essentially an adaptation of aoristic analysis, created for the study of crime patterns by Ratcliffe (his 2002 paper covers a more robust method than his previous work) and experimented with by various archaeologists.  Where appropriate, we can then sum these probabilities for each time-slice, to produce a model of changing deposition over time.

The most obvious dataset of ours to apply this fuzzy temporal analysis to is the PAS (Portable Antiquities Scheme) data.  This is because most PAS records represent a single object which has had start and end dates defined for it by the PAS team.  Some records need start and end dates adding (based upon the start and end periods, or in the absence of those, the broad periods) and some records need their start and end dates correcting (typically where they have been mistakenly reversed or where dates BC have not been given negative numbers), but all of this is possible to automate using Python scripts.  Once this data standardization has been completed, it is then possible to define a set of sub-periods and calculate the probability of each object falling within each sub-period (again, using a Python script).

PAS: summed probability by century
PAS: summed probability by century

The graph above shows the summed probabilities of PAS data when calculated and collated by centuries.  We can see here the general temporal profile of the PAS for our period, involving low levels of Bronze Age finds, increasing activity during the Iron Age, especially after the introduction of coinage, a massive increase through the Roman period, and then a return to lower levels of activity through the early medieval period.

PAS: summed probability by century: only objects of greater than 90% probability
PAS: summed probability by century: only objects of greater than 90% probability

The graph above then shows how the summed probabilities look if we only include objects with a greater than 90% chance of falling within each century.  Obviously, this example is a little fatuous, as it is not really very easy to date objects that precisely prior to the introduction of coinage, but it does make the point that only including very precisely dated material produces a biased temporal pattern.

PAS: summed probability by century: count of objects of greater than 0% probability
PAS: summed probability by century: count of objects of greater than 0% probability

At the opposite extreme, the graph above shows the count of objects within each century that have a greater than 0% probability of falling within said century.  Thus, in this graph, if an object spans three centuries, it is counted equally in all three.  Naturally, this method then produces another biased temporal pattern, this time over-representing activity in each century.

As such, the first graph, which takes account of the probability of every object is, in my opinion, the most honest representation of the temporal pattern.  However, as hinted above, century brackets are not really ideal, as objects can only very rarely be dated that precisely before coinage came into use.

PAS: mean probability by century
PAS: mean probability by century

This graph shows the mean probability (from 0.0 [0%] to 1.0 [100%], albeit the graph doesn’t scale that far) for all of the objects within each century bracket.  It shows that (on average) Middle Bronze Age and most Iron Age material is coarsely dated, that Later Bronze Age and Late Pre-Roman Iron Age material is better dated, that Roman material (particularly 4th century) is finely dated, and that most early medieval material falls somewhere between the prehistoric and Roman data in terms of its precision of dating.  The very low probabilities in the 5th century partially reflect the post-Roman transition, but are likely to be largely caused by the huge bulk of essentially 4th century Roman material that has been given an end date of 410 or 411.

The conclusion I draw from this graph is that we need to vary the width of our sub-periods over time to reflect the changing level of precision of dating within each period.  This ought to produce the most useful representations of temporal pattern, and is as equally simple to calculate as fixed century blocks.

PAS: alternative sub-period groupings
PAS: alternative sub-period groupings

This final graph, then, shows the summed probabilities for three different possible sets of sub-periods.  The y-axis is the summed probability and the x-axis is time from -1500 (1500 BC) to +1065 (AD 1065).

The orange line shows the same century brackets as before, which clearly is the worst model, as it reduces prehistory to a low-level trace yet also removes significant change in the Roman period (notably the sharp drops around AD 200 seen in both other lines).

The blue line shows a set of conventional sub-periods.  This shows a much more interesting temporal pattern than the century brackets.

The red line shows an alternative set of sub-periods, designed to break away from conventional dates assignments and to take more account of the changing rate of dating precision over time.  This is probably my preferred model, but there is no reason to make hard and fast choices, we can continue to experiment with multiple sets of sub-periods for now.

In the context of our project, this is very much preliminary work, intended to test out some of the possibilities of working with fuzzy temporality using our datasets.  I have also begun experimenting with building the EMC (the Early Medieval Corpus of Coin Finds maintained at the Fitzwilliam Museum, University of Cambridge) into this dataset.  There is also potential for doing something similar with the HER data that we have gathered, albeit implementation is more complex due to the variable structure of that data.  Once we have our methodology nailed down, it will become possible to construct graphs like the final one above for different types of object or for different regions of England.  We could also create a series of maps showing changing probabilities over time, perhaps combined into animations.

Whether this proves fruitful, only time will tell, but I do believe that this type of analysis has great potential for helping to explore continuity and change in EngLaId data.

Chris Green

References:

Green, C.T. 2011. Winding Dali’s clock: the construction of a fuzzy temporal-GIS for archaeology.  BAR International Series 2234.  Oxford: Archaeopress.

Ratcliffe, J.H. 2002. “Aoristic signatures and the spatio-temporal analysis of high volume crime patterns.” Journal of Quantitative Criminology 18(1), pp. 23-43.

Trément, F. 2000. “Prospection et chronologie: de la quantification du temps au modèle de peuplement. Méthodes appliquées au secteur des étangs de Saint-Blaise (Bouches-du-Rhône, France).” In Francovich, R. and Patterson, H. (eds.) Extracting meaning from ploughsoil assemblages. Oxford: Oxbow, pp. 77-91.