Sessions at TAG 2013: visualisation, anthropology and connectivity

logoThis year’s Theoretical Archaeology Group meeting is coming up, and my friends are organising a cool set of sessions there. Sara Perry, Cat Cooper and Gareth Beale are hosting a session called “Seeing, Thinking, Doing: Visualisation as Knowledge Creation”. Their key message is that visualisations are not neutral: they can lie, hide information, or enhance communication of a message. Whatever they do, a critical evaluation of the use of visualisations in archaeology is necessary. I would love to see some infovis and network visualisation studies there! You can read the full abstract below, or visit their blog.

Fiona Coward, Rosie Read and colleagues will chair a session ‘Archaeology and Anthropology: Squabbling siblings, star-crossed lovers or bitter enemies?’. It will discuss the differences between the two disciplines in the past, present and future. See the abstract below.

Two other sessions that got my interest are those by Ben Jervis and colleagues: ‘ANT(ics) and the Thingliness of Things: Actor-Network Theory and other Relational Approaches in Prehistoric and Historical Archaeology’ and ‘It’s All Material Culture, Ain’t It! Connectivity and Interdisciplinarity in Material Culture Studies’.

For more info on TAG 2013 Bournemouth visit their website.

Seeing, Thinking, Doing: Visualisation as Knowledge Creation
Organizers: Gareth Beale (Gareth.Beale@soton.ac.uk), Catriona Cooper (catriona.cooper@soton.ac.uk) & Sara Perry (sara.perry@york.ac.uk)

Decades of enquiry have born witness to the importance of visualisation as a critical methodology in archaeological research. Visual practices are intimately connected to different ways of thinking, shaping not only how we interpret the archaeological record for diverse audiences, but how we actually see and conceive of that record in the first instance (before investigative work has even begun). A growing body of volumes, workshops and symposia* testify to the centrality of visualisation in processes of deduction, narrative construction, theory-building and data collection – all those activities which lie at the heart of the discipline itself. But these testimonials generally still lay scattered and detached, with researchers and visual practitioners often talking at cross-purposes or working in isolation from one another on issues that are fundamentally linked.
Following the success of Seeing, Thinking, Doing at TAG Chicago in May 2013 (http://seeingthinkingdoing.wordpress.com), we seek here to delve further into such issues, concentrating on those bigger intellectual tensions that continue to reveal themselves in discussions of the visual in archaeology. We welcome short papers attending in depth to any of the following five themes:
(1) Realism and uncertainty
(2) Ocularcentrism
(3) Craftspersons and visualisation as craft
(4) Historical forms of, and past trends in, visualisation in archaeology
(5) Innovative approaches to representing the archaeological record
The session will be linked across two continents with a discussant in Canada as well as the main presentations in Bournemouth. We are happy to include speakers willing to participate remotely, via Google Hangout, and we encourage all contributors to add their perspectives to our group blog prior to – and following – the session: http://seeingthinkingdoing.wordpress.com. The papers will be accompanied by a roundtable discussion, where we will analyse the five themes—and related intellectual trends in visualisation—at an overarching level.
*E.g., Molyneaux 1997; Smiles and Moser 2005; Bonde and Houston 2011; “Seeing the Past,” Archaeology Center, Stanford University, Stanford, USA, February 4–6, 2005; “Past Presented: A Symposium on the History of Archaeological Illustration,” Dumbarton Oaks, Washington, DC, October 9–10, 2009; “Visualisation in Archaeology,” University of Southampton, Southampton, UK, April 18–19, 2011.
Bonde, S. & Houston, S. (eds.) 2011. Re-presenting the Past: Archaeology through Image and Text. Oxford: Joukowsky Institute Publications/Oxbow.
Molyneaux, B.L. (ed.) 1997. The Cultural Life of Images: Visual Representation in Archaeology. London: Routledge.
Smiles, S. & Moser, S. (eds.) 2005. Envisioning the Past: Archaeology and the Image. Malden, MA: Blackwell.

‘Archaeology and Anthropology: Squabbling siblings, star-crossed lovers or bitter enemies?’
The relationship between the disciplines of archaeology and anthropology (social/cultural and biological) goes back a long way, but the nature of that relationship has varied hugely over that time. The papers in this session seek to investigate how archaeology and anthropology relate to one another today, academically and professionally, and to debate whether the disciplines should work to come together in future, or contemplate a permanent separation. Does archaeology offer anything to anthropologists, or anthropology to archaeologists? In what areas might closer collaboration be useful? Or have the two disciplines drifted so far apart that no rapprochement is possible or desirable? This session will aim to address these questions from as broad a perspective as possible, including for example papers considering the historical development and/or future trends of the disciplines, the academic or professional relationship between them, case studies demonstrating how the disciplines might benefit (or indeed not benefit) from closer links, or why they should forge their own, more independent identities etc.
All relevant details about the conference can be found here: https://microsites.bournemouth.ac.uk/tag2013/welcome/. We would like to invite anyone interested in presenting a paper in our session to submit their proposal by September 8th to Fiona Coward: fcoward@bournemouth.ac.uk; Rosie Read: rread@bournemouth.ac.uk or to myself: sschwand@gmail.com.

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Interface workshop

Yesterday I chaired a workshop with Marco Büchler at the Interface conference in London. It was well attended and the discussion we got going was stimulating. You can download the presentation slides here or through the bibliography page. We also prepared handouts with a summary of the workshop and some software and bibliographic resources, download it here.

The workshop aimed to give an introduction to networks as a way of thinking. We covered some basic network ideas, visualisation and analysis. As an example we explored seven different English translations of the Holy Bible. Using networks we could see what sections were reused throughout the translations and what not. It turned out that throughout the centuries subtle and less subtle differences seeped into the translations, fascinating stuff!

Like everyone else at the conference I also gave a two minute lightning talk, really cool but challenging experience! Download the slides here or on the bibliography page.

Awesome art by Aaron Koblin

Just saw this TED talk by Aaron Koblin, a digital artist who’s work has inspired me for a while now. His art shows stunning examples of the fact that we have so much data available everywhere that relates in unsuspecting ways. If we bother to add things up, like he does for hand-drawn sheep, Johnny Cash still images, flight patterns, $100 bills and even voice samples, we see surprising things emerge that you would not expect by just looking at a single image or sample. His work on flight patterns is stunning and has been exhibited in the New York MOMA recently.

Check out his work online. And check out his talk below. Believe me, you’ll be surprised!

Conference Newcastle ‘Networks and Scales’ 23 May

I would just like to remind you all that next Monday the School of Historical Studies at Newcastle University will host a Postgraduate conference titled ‘Networks and Scales: Relating the local and the global’. I will present a paper myself on issues surrounding the archaeological application of network analysis, the potential of a multi-scalar network method, and show examples from the ‘Urban connectivity in Iron Age and Roman Southern Spain’ project directed by Simon Keay and Graeme Earl.

I am very much looking forward to the event, the list of speakers looks very promising.

Have a look for yourself:

This interdisciplinary conference seeks to address the notion of networks across boundaries and disciplines. Are we aware of the networks within which our subjects exist? Do we address sufficiently issues of network and scale in the past? How do we make connections between the often narrow focus of doctoral research and the local and global scales within which we practice?

The variety of papers that we were offered has been thrilling and it has been a great pleasure to organise what looks set to be an interesting and stimulating day. The papers transcend the disciplines of archaeology, history, ancient history, classics and history of medicine bringing together diverse research interests and a range of researchers united by a common interest in connecting different people, places and things, building links between data and interpretation and locating the local or individual in broader networks. We hope that today will provide the opportunity for our speakers and audience to both explore and create new networks.

We would like to take this opportunity to thank the people without whom today would not be possible. Firstly, our sincere thanks to Professor Keith Wrightson and Professor Norman McCord for offering their continued support for the poster and paper prizes respectively. Our thanks are also due to the judging panels for said prizes. In addition we would like to thank the School of Historical Studies for their financial support, and in particular Dr. Helen Berry, director of postgraduate studies. We are grateful to those who have submitted posters, and hope that you have found it a useful experience. We would like to thank our speakers for offering such varied and intriguing abstracts and, we are sure, thought-provoking and interesting papers.

Finally, it is a great pleasure to welcome Professor Richard Hingley of Durham University as our key note speaker. We are honoured to have him address the conference and can think of no better way to end the day than with his lecture on networking frontiers.

Schedule for the Day

9.30am – Registration in the Research Beehive

Exploring Network Theories

10.00am Tom Brughmans – Complex networks in archaeology: Urban connectivity in Roman southern Spain

10.30am Keith Scholes – Recovering past networks : An approach to Early Medieval trade and communications

11am Coffee

11.30am Piotr Jacobsson – Re-assembling Aceramic Cyprus

12.00pm Louise Tolson- Exclusive/Inclusive: Public involvement and collaboration in the archaeology of the recent past

12.30pm Lunch

Scaling Sickness and Health

1.30pm Michelle Gamble – Bones, people and populations: A palaeopathological case study from Chalcolithic Cyprus

2.00pm Graham Butler – “Elizabeth Ferney, having procured a foul distemper, ordered into the workhouse until cured”: The Parish, the parish workhouse and parochial medicine in Newcastle-upon-Tyne, 1770-1830

2.30pm Coffee

Networks of Power

3.00pm David Linden – One Nation Networking: Baroness Elles and European Toryism

3.30pm Fiona Noble – Sulla and Aphrodisias: Greek and Roman Interaction in the 1st century BC.

4.00pm Jonathan Dugdale – Pagodas, Patronage and Power: The Role of State Sponsored Buddhism in Liao Dynasty China

4.30pm Coffee and Judging of the Keith Wrightson Poster Prize

5.15pm Presentation of the Keith Wrightson Poster Prize and the Norman McCord Prize for the best paper

5.30pm Key Note Address

Professor Richard Hingley – ‘Networking the study of frontiers’

6.30pm Wine reception and dinner at Barkolo.

CAA2011 networks session summary and discussion

The networks session at CAA2011 in Beijing was a success! We had some great papers and a fascinating discussion. Read the summaries of the papers, the questions and answers, as well as the discussion here. Read more about the session, including the abstracts and the introduction on the dedicated page.

The first presentation of the day was by Maximilian Schich and Michele Coscia talking about ‘Untangling the Complex Overlap of Subject Themes in Classical Archaeology’.

Maximilian and Michele used the Archäologische Bibliographie, a library database consisting of over 450.000 titles, 45.000 classifications, and 670.000 classification links. They looked at the co-occurrence of classifications, creating networks where two classifications are connected if they appear in the same book as well as networks where classifications are connected when the same author writes about them. Using whatever database software you can look at the local level of this massive dataset. This was not of interest to the authors. In stead, Max and Michele looked at the bigger picture. They devised a method that allowed them to explore the dataset on three different scales: the local level (database level), the meso-level and the global level. On the global level they were able to identify academic communities, but also clusters of communities (so communities of communities). They also looked in detail at how these communities evolved over time. On the meso-level they threshold the data based on co-occurrence and significance, which produced interesting results. Max and Michele concluded that this approach to academic literature allows us to look at the fine-grained structure of how archaeology actually works. Their three-level method using hierarchical link clustering and association rule mining made it blatantly clear that complex overlaps are everywhere in academia!

Questions: Guus Lange asked what type of clustering was applied, to which Max responded that no clustering was performed on nodes but on the links. Graeme Earl asked how the classifications were derived from the database and whether they thaught about exploring how the classifications themselves grew and transformed. Max replied that there is no limit to the number of books per classification but there is a sharp limit to the number of classifications there are per book. What is interesting, he said, is that we nevertheless get this big picture. Tom Brughmans wrapped up with a final question about how long it took them to do this work. Michele and Max mentioned that it took them one year but once the workflow is engineered it could be done in two weeks time.

Diego Jimenez was our next speaker. He presented on ‘Relative Neighborhood Networks for Archaeological Analysis’.

Diego is interested in archaeological attempts to find meaningful spatial structure between archaeological point data. He relies on graph theory to find structure based purely on the spatial distribution of points and suggests objective ways of analysing connections between them. In his talk Diego focused mainly on the methodology rather than any specific applications. Rather than nearest neighbour approaches, he suggested a relative neighbourhood concept as the basis for his method. Two points are relative neighbours if the regions of influence drawn around this pair does not include other points. Graphs can be constructed using this concept. Most interestingly, Diego mentioned that a parameter beta can be included to change the regions of influence. This allows for a series of graphs to be created with different levels of connectivity. Diego suggested some space syntax approaches to analysing these graphs including graph symmetry, relative asymmetry and distributedness.

Questions: Maximilian Schich was interested in how control was defined in Diego’s analysis of the graphs and mentioned that peripheral nodes might often have a high level of control in a network. Diego mentioned that these are indeed important patterns that need to be acknowledged by archaeologists and his method would be a way to be sensitive to them.

After Diego we had the honour of listening to a historians experiences with network analysis. Johannes Preiser-Kapeller talked about ‘Networks of border zones – multiplex relations of power, religion and economy in South-eastern Europe, 1250-1453 CE’.

Johannes’ paper made it very clear that, although archaeologists can rarely obtain datasets of such quantity or quality as in other disciplines, we still have sources that inform us of different types of relationships for which a networks approach can lead to highly interesting results. He constructed five distinct networks from different data types (streets, coastal sea routes, church administration, state administration, participants of the 1380 synod) some of which were compared for three different moments in time (1210, 1324, 1380). Initially some general measurements, like average distance, clustering coefficient and density, are used to explore the topology of individual networks, as well as compare between networks of different sources. Secondly the overlap of groups of related nodes is identified to explore the correlation between different networks. Johannes then merged all these networks to create what he considers a multiplex representation of frameworks of past human interactions. Thirdly, the combined effects of the multiplex network on the topology of social interaction, as illustrated through the participants in the 1380 synod, is explored. He concluded by stating that this framework that emerged from different sources might be more than merely the sum of its parts. In short, even though we are dealing with fragmentary and limited datasets, applying a networks perspective explicitly might still guide us to highly interesting and surprising results.

Mihailo Popovic presented the final paper before lunch. His talk titled ‘Networks of border zones – a case study on the historical region of Macedonia in the 14th century AD’ was strongly related to that of his colleague and fellow historian Johannes.

Mihailo’s paper explored the border zone between the Byzantine empire and the emerging Serbian state in the 14th century AD. His case-study focused on the area of the city Stip and the valley of the river Strumica. Four central places were identified in the valley on the basis of written medieval sources: the towns of Stip, Konce, Strumica, and Melnik. Mihailo is interested in understanding how these places interact with each other. For example, can an exclusive relationship between the central places and the surrounding smaller settlements be assumed? Or did all settlements interact equally with each other? Mihailo stresses the importance of evaluating the landscape on the ground to explore how this might have influences urban interactions. Based on Medieval written sources that identify the larger settlements as religious, administrative and economic centres, he argues for an exclusive relationship of the larger towns with the smaller ones. This leads to astral-shaped networks. Mihailo’s analysis shows that Strumica has the highest closeness centrality value, whilst Stip has the highest betweenness value. To conclude he stressed the wider questions that his networks approach leave open: is the settlement pattern complete? Is the network realistic in view of the landscape? Is the networks’ astral-shape justifiable or did the villages also interact with each other? May we assume interactions between other villages? How to integrate human behaviour?

We reconvened in the afternoon to listen to Ladislav Smejda talking about ‘Of graphs and graves: towards a critical approach’

Ladislav discussed the artefact distributions from a cemetery dated around 200 BC. He explored eleven attributes consisting of grave dimensions and the presence or absence of grave good categories, which can appear in many combinations. Ladislav limited the relationships of co-presence of grave goods to statistically significant correlations, which resulted in a graph representing his eleven attributes and relationships of positive and negative correlations between them. He then moved on to divide the graph into two substructures. Substructure A is defined by correlations between ornaments (faience beads, bone beads, hair ornaments) and grave depth. Substructure B includes stone artifacts, cattle ribs and grave length. These two sets seem to show strongly different patterns, which can be explored as networks. Simple networks were created based on the presence or absence of artefacts significant to either substructure A or B, showing different structured. Secondly, Ladislav introduced the concept of the hypergraph where the edges are more like areas in which more than one node can be included. Ladislav concludes that a graph theory and network analysis approach is useful to handle, visualise, and explore the structure of archaeological datasets, whilst leaving plenty of options open to take the analysis further with different tools (like GIS).

Questions: Ladislav’s presentation sparked many questions, partly because we had plenty of time in the afternoon due to serious changes in the conference schedule. So I decided to transcribe the questions as a simple dialogue.

Leif Isaksen: what does the negative correlation mean? That the attributes don’t occur together?

Ladislav: they don’t appear together with statistical significance.

Maximilian Schich: what’s the negative correlation with grave depth and faience beads?

Ladislav: deep graves have bone beads and shallow graves tend to have faience beads.

Leif Isaksen: how has the grave depth been recorded?

Ladislav: data was taken from excavation reports. There is no specification of how they measured that. The whole site was excavated by a single person. Possibly grave depth was measured from the top soil downwards.

Maximilian Schich: You could compare every link in this diagram, maybe as an XY diagram where you have bone beads vs grave depth for example. Do you know how many bone beads there are? How many graves? Are these measured just as presence/absence or as real counts?

Ladislav: There are 70 graves with bone beads, and 470 graves in total. I tried both approaches but presence/absence is better because in many cases it was impossible to count precise numbers. I don’t think it is important to know how many bone beads they had exactly.

Maximilian Schich: so you could draw an XY diagram. If you only have 470 graves it’s very easy to draw a histogram. And instead of the correlation you could give us all the data points.

Ladislav: I did all these things. At the moment I have so many outputs of this data that it could not be presented in a 15 minute paper. Clearly there is much more you could with this data.

Maximilian Schich: how can you assign grave depth to a region where there is no grave?

Ladislav: the grey background is just an interpolation of the grave points. The crucial thing this shows is that there are no deep graves on one end of the matrix and no shallow graves on the other.

Diego Jimenez: is there any significance in the distribution of objects within each grave, and is that relevant for the analysis.

Ladislav: it’s recorded, I tried to follow this up but not with graph theory.

Diego Jimenez: this is what sparked my interest in using graphs, as I used it to understand the spatial distribution of artefacts within graves. The spatial arrangement might have a symbolical importance.

Tom Brughmans: it’s a good example of a network within a network as well.

Leif Isaksen: it would be great to see these graves’ locations projected in geographical space, did you pursue a geographical approach as well?

Ladislav: yes, but that is the topic of another presentation.

Tom Brughmans: I am not sure if the statistics used to explore correlations are necessary, because these correlations might just emerge when exploring the co-presence of different types of artefacts as a network.

Ladislav: the presence/absence is exactly what is represented, so it is a different way of achieving the same thing.

Maximilian Schich: you have enough data but not too much to prevent a real networks visualisation. There is no need to reduce your data to a few nodes and links. All your data can be shown on one graph and a few histograms.

Ladislav: I did not do this because I am looking for the simplest possible structure, in the simplest possible representation.

Due to the changes in the conference schedule the afternoon also saw two unscheduled presentations by Leif Isaksen and myself being added to the network analysis session.

Tom Brughmans presented a paper titled ‘Facebooking the Past: a critical social network analysis approach for archaeology’.

I started out with a short fiction about how Cicero became consul of Rome thanks to Facebook and Twitter. Obviously, that is not the story we will find in the history books. But by making the analogy between modern ideas of social networks and past social processes it becomes clear what it is we are actually doing when using social network analysis. I argued that there are three issues related to the archaeological (and indeed historical) use of social network analysis. Firstly, that the full complexity of past social interactions is not reflected in the archaeological record, and social network analysis does not succeed in representing this complexity. Secondly, that the use of social network analysis as an explanatory tool is limited and it implies the danger that the network as a social phenomenon and as an analytical tool are confused. Thirdly, human actions are based on local knowledge of social networks, which makes the task of deriving entire past social networks from particular material remains problematic. To confront these issues I argued to turn the network from the form of analysis to the focus of analysis and back again in an integrated analytical process drawing upon ego-networks, complex real-world network models and affiliation networks approaches.

Discussion: the questions about this paper changed into a fascinating discussion about the nature of archaeological and historical data and how this influence our use of network techniques.

Maximilian Schich: I think that indeed data from today is different than from the past but only because more is different. In a sense I think it cannot be justified to say that we should not look for social networks because the data is incomplete. Modern day data, like mobile phone record for example, are also incomplete. Facebook does not cover all social interactions. One topic that has been mentioned a lot today is that of multiplex networks. There is a conceptual danger with this because it assumes that we can discretize between different types of networks, whilst actually that is not possible. When collecting data there is one thing that is definitely different from data like mobile phone networks for example, which is the multiplicity of opinion. If you collect something and I collect something the data will look completely different. All these things are complicated, a lot of time needs to be invested in this, I agree that we have to work with what we have. But we should not capitulate in front of this problem saying that it’s perfectly fine to just bullshit theoretically because the data is unavailable.

Tom Brughmans: I agree that archaeological data is not necessarily any different than data sociologists or physicists use, like mobile networks for example. Another example is e-mail communication. A sample of this type of social interaction might be limited because some people were out of office whilst you were taking the sample, and it is also an indirect reflection of social relationships as we explore the e-mail directly but not the people. So our data might not be different. But what possibly makes archaeology (and other historical disciplines) different is that all our theory is geared towards this issue. We are very aware that we are dealing with indirect fragmentary samples to explore dynamic processes in the past. Whilst in other disciplines scholars might over simplify this issue, in the historical disciplines we are very aware of it and cannot avoid it. Another difference might be what you said that when different people excavate the same thing, different data will emerge. But more crucial I think is that after collection the data is actually destroyed, it is not a repeatable test. The data only lives on in a structure that makes sense to the person who collected it. So given these two issues I think archaeological applications of social network analysis can be different from other disciplines.

Yasuhisa Kondo: Just a comment. I believe that social networking like Facebook and Twitter is also changing archaeologists’ behaviour. When I was in Oman a few months ago, for example, the Middle East crisis was picking up and I was informed about the situation of Egyptian heritage through social networks. Secondly, in Japan we use Facebook to collect data. So it is interesting to see that it is not only useful to think about present social relationships between archaeologists but also about past social networks.

Johannes Preiser-Kapeller: when comparing modern complex network analysis in physics and historical network analysis, in physics scholars don’t want to just analyse but they also want to explain, to understand the mechanism that makes the network function. They generate ideas on how such network actually worked, like through preferential attachment for example. We do not know if networks in the past actually worked in the same way, if such mechanisms can be imposed on historical networks. Our data sometimes isn’t even large enough to identify degree distributions that reveal power laws for example.

Tom Brughmans: I am glad that you bring this up because I have been struggling with a similar issue. Do these real-world network emergent properties actually explain anything. Aren’t they just a description of a complex network structure, of how it evolves rather than explain the network. The descriptive aspects of such models can easily be applied to historical data, when we accept the assumption that the whole is greater than the sum of its parts and complexity arises from local interactions. But it does not really explain much does it.
Johannes Preiser-Kapeller: modern complex network models assume that they are not merely descriptive but they are laws that explain how things like social relationships functioned. It’s more than description, they are looking for mechanisms. The question is if we can also identify such mechanisms for past networks which can help us to explain how social interaction worked.

Maximilian Schich: concerning the power-law thing, preferential attachment is only one of thousands of mechanisms which can result in a power law. And in some cases it can not even be proven that the power law is there because of a lack of data. So we cannot blame the people that came up with the idea of preferential attachment in the first place as if they assumed that it explained all power laws. It is not their fault that they got cited 60.000 times. We should acknowledge that this is just one model that actually works, and it explains a lot, just like the small-world model. But both of them are incomplete. Concerning historical networks: I think it is a big mistake of historians or other scholars in humanities to think that we are special, cause we are actually not. Of course we have different documentation and different numbers. But the underlying approach of hypothesis testing and of saying “let’s look at what structure the data has”, that is the approach complex network scientists have. They do not assume a universal law. This is the same approach taken in the humanities.

Mihailo Popovic: many people are not aware of the exact historical situation. Like 14th centure Byzanthium for example: 90% of the population lived in vilages, the flow of information does not exist on an international level it is a local thing.

Maximilian Schich: are you sure?

Mihailo Popovic: I am sure, based on the sources we have. Thirdly, there are slaves in the villages who’s movement is restricted. Finally, Illiteracy is immense. To come to my point: we have written sources that are written by 5% of the population, if even that. And of those perhaps 20% percent survive. So what do we do? We cannot just assume that comparing a dataset of six million people communicating over the internet with a historical dataset like the one I described can be done through the same approach. We have to face the reality of the historical period. It took us a lot of time and effort to collect these relatively small and still fragmentary datasets.

Maximilian Schich: but we can agree that things are being spread between people, even if they are not aware of it. Information can spread in the same way electricity spreads for example, electrons push other electrons along, not every electron goes all the way from Europe to China. We have such a situation where we can assume that some information was spread for most periods in the past. So to say that there are individuals who are immobile and construct sampling boundaries based on that, I don’t think such a strict limitation can work.

Johannes Preiser-Kapeller: of course, there was some kind of globalization already in the 14th century, there was some connection which even reached villages. It would be perfect if we could paint a picture of such a global system. We can do it on a superficial level, but we do not have the necessary sources to go in more depth. A prosopographic database of the Byzantine period, for example, contains 30.000 people. Of those, 80% were clerics and not more than 200 were farmers. We can see what is going on for the top 5% of the people, and we can see the mechanisms like preferential attachment working on this level. But we are still struggling with the artificial border created by our data, as you mentioned. We do not have the entire system. This sample problem will always be there in the historical discipline.

Maximilian Schich: that’s exactly the same problem as we have in any other discipline. It is not a history or non-history problem but a percolation problem. Physicists working on percolation have to come up with a solution and then we can make an educated gues of how much of the system we have.

Johannes Preiser-Kapeller: let me give you another example. When I showed my work to Stephan Thurner in Vienna, who worked on a massive dataset of 300.000 individuals interacting through a computer game, he said my dataset of only 200 aristocrats is not enough. If you do not have at least 1000 individuals you cannot identify any mechanism, you need statistical significance. So this is a limit imposed on historical disciplines in applying interesting mechanisms identified in complex real-world networks.

After the discussion we still had the pleasure to listen to Leif Isaksen talking about ‘Lines, Damned Lines and Statistics: Unearthing Structure in Ptolemy’s Geographia’. Sadly my tape recorder died at this point, so here is Leif’s abstract rather than a review.

Ever since the rediscovery of Ptolemy’s Geographia in 1295, scholars have noted that it is troublingly inconsistent both internally and with the environment in which it was supposedly compiled. The problem for analysts to overcome is that the catalogue has been corrupted, amended and embellished throughout its history. It is therefore imperative to find more robust means to look for structural trends. Recent publications of the theoretical chapters and a digital catalogue of coordinates provide a variety of new possibilities. We are not alone in advocating computational procedures but will discuss two techniques that do not appear to have been considered in the literature so far and the conclusions they appear to give rise to.

First, statistical analysis of the coordinates assigned to localities demonstrates clearly that ostensible precision (whether to the nearest 1/12, 1/6, 1/4, 1/3 or 1/2 degree) varies considerably by region and feature type and is locally heterogeneous. In other words, the composite nature of the data cannot only be confirmed, but we can build a clearer picture of how the sources varied by area. Secondly, while many studies have addressed either the point data or the finished maps, simple linear interpolation between coordinates following the catalogue provides a unique insight into the ‘invisible hand’ of the author(s). The unmistakable stylistic families that emerge, and the occasionally arbitrary limits imposed on them, provide further important evidence about the catalogue’s internal structure.

Complexity in the Big History

I just saw this TED talk by David Christian that might be of interest to readers of this blog. It’s about the emergence of complexity, and events in long-term history that bring about complexity. It gives an intriguing large-scale picture of the evolution of the universe backed up by beautiful animations. David Christian says collective learning is what makes humans different, and it’s cool to see that this talk itself is a direct result of collective scientific efforts, popular agreement and collective learning.

Check out the talk here, and visit the Big History project here.

“leaderless revolutions” in modern Egypt and … the past??

I just read this fascinating blog post by Zeynep Tufekci, assistant professor in sociology at the University of Maryland, Baltimore county. She states that through the democratic nature of the recent revolution in Egypt a hierarchy emerged. A fundamentally leaderless situation gave rise to popular leadership. According to the author this can be explained by the “rich get richer” effect, and she illustrates this with how People on Twitter using the hashtag ‘Jan25’ shows a scale-free power law. Apparently, those people tweeting about the revolution that have alot of followers will end up getting ever more followers. They have become the (digital) leaders of a headless revolutionary event. I find it interesting how this hierarchy and its immediate effects must have been the result of a critical mass of influence reaching a turning point, leading to revolutionary events.

Obviously Twitter is only one medium through which ideas can be spread, and in no way does the “rich get richer” effect explain WHY the revolution happened. What were the individual motivations that led to this large-scale event? What the scale-free model does imply, however, is that the event could not have taken place without these individuals and their actions, their decisions to follow increasingly popular charismatic (albeit digital) figures.

Could this perspective help us understand past revolutions?

Obviously ideas spread much slower in the past than in the present. But that does not mean that revolutions happened any slower or less spontaneous. How could we explore past revolutions through the material remains that we examine as archaeologists? I would be very interested in seeing how changes in material culture attest of a scale-free pattern. A perfect example is Bentley and Shennan’s work on Linear Bandkeramik in Germany. They showed that the patterns on these vessel evolved according to a scale-free power law, where popular motifs were expected to become ever more popular and more influential in future motif design. What fascinates me about this kind of research is that it does not incorporate any measure of originality in innovation. Motifs or ideas might not have been all that revolutionary, for example, but for some reason they became popular and widely adopted. Through them revolutions emerged, more as a result of their relation to other things/people/ideas than their inherent qualities. Still, the question of why this scale-free structure emerges and shapes revolutions remains unanswered. And what about truly revolutionary ideas? Does their adoption show a scale-free structure? And if not, is that really the reason why they did not catch on?

Geographic interconnections

In this blog post we continue our quest to develop a method for studying trade routes as they are reflected in the ceramic evidence. It provides an alternative and in some ways parallel to our previous post concerning Beta-skeletons.

A computerised model was developed by Rihll and Wilson (1991) to study the interconnections between sites based solely on their geographical coordinates, while taking size, importance and interactions between sites into account. The only thing one needs to enter into the model are the locations of all sites. Other factors are simulated and develop when running the model thanks to three assumptions:

  • Interaction between any two places is proportional to the size of the origin zone and the importance and distance from the origin zone of all other sites in the survey area, which compete as destination zones.
  • The importance of a place is proportional to the interaction it attracts from other places.
  • The size of a place is proportional to its importance.

Through a number of simulations starting from an initially egalitarian state (equal size and importance for all sites), the most likely pattern of interconnections between sites is determined.

Shawn Graham successfully used this model in his analysis of the brick industry in the Tiber valley. Networks of interconnections between sites in the Tiber valley were created to “explore the effects of geography, stripped of all other considerations” (Graham 2006b: 77; Graham 2009: 678-681).

As the Relative Neighbourhood Graph (RNG) this method uses straight line distances, which will allow us to study the influence of distance in the distribution of table wares. However, as it is a probabilistic model its potential for testing hypotheses is far greater.

We could use this method to create a network of all sites included in the distribution patterns of table wares. The network can be analysed to determine the relative positions of all sites, knowing that distance is a significant factor and taking size and importance into account, but most importantly, exactly knowing the value of all these factors for a given result.

We should stress that the simulated importance represents the importance of a site in the table ware trade, given that distance is a significant factor (this might require a revision of the mathematics underlying the model). Instead of running an egalitarian simulation, we can therefore enter the values for importance into the model as they are present in the ceramic data. When we rerun the model we will be able to analyse a network of a certain distribution in a certain period knowing that distance is influential and being able to calculate this influence. Moreover, we can compare these ceramic networks with multiple stages in the egalitarian simulation.

Again, this is just an idea that might bring us one step closer to understanding the decision made by people involved in the distribution of table wares, but it is by no means without its issues:

  • We assume a direct correlation between number of sherds and importance in trade patterns. Should we use the diversity and relative amounts of ceramic forms as an index of importance? As this is a simulation we accept that we enter arbitrary values for something we try to study (the relative position of sites in different ceramic distribution patterns). Still we should beware for circular thought patterns which will eventually tell us that the things we think are significant will turn out to be significant.
  • What with the ‘size’ factor? Should we remove it from the model or can it represent another aspect of ceramic trade?
  • Is it useful to apply this model to the ceramic evidence, or should we just run the analysis without including the number of sherds, to see how sites relate to one another in space? Such an approach might allow us to compare a distance-based simulation with Beta-skeletons of ceramic distributions?

Relative Neighbourhood graphs and Beta-skeletons

Although our preliminary method indicates that a reconstruction of pottery trade flows involves a lot of complications, we cannot seem to let this research topic go. One reason for this is that most archaeological attempts to study the ancient economy make interpretations about trade routes based on ceramic evidence (e.g. Abadie-Reynal 1989 ; Fulford 1989), yet none have ever attempted a networks approach. In this post we will discuss a geographical network in which distance is a significant parameter, an assumption that is not without its complications.

We believe that relative neighbourhood graphs (RNG) and Beta-skeletons might prove to be useful tools for constructing distance-based networks. Unlike other types of cluster analysis (e.g. nearest neighbour) these methods take the position of all points in account. Jiménez and Chapman (2002); discussed the archaeological application of RNG, and summarize its construction as a graph in which “the link between two points is determined by taking into account not only the proximity between the two points, but also the relative distance of each pair to the remaining points ». Lines are drawn between two neighboring points that have no other points in a region around them. By varying the size (beta) of the region of influence for each pair of points, graphs (called Beta-skeletons) can be created with different levels of connectivity: if the region is small, more relationships will be drawn between the points; if the region is large, the network will start to fall apart in smaller networks (see Fig. 1).

beta-skeletons example
Fig. 1 Beta-skeletons with varying regions of influence, indicating that for a higher value of beta the network will start to fall apart. Taken from Jiménez & Chapman 2002.

Of particular interest for our study is a Beta-skeleton of sites in the Eastern Mediterranean at the stage just before it starts to fall apart, so without any unconnected sub-networks (similar to the network for ‘Beta=2’ in Fig. 1). This Beta-skeleton can be analysed as a network, which will allow us to define the relative position of every site for the hypothesis “what if straight-line distance were a determining factor in the distribution of table wares?”

Such a network obviously avoids all complications but is invaluable in testing a distance-based hypothesis. For every ware in every period the number of sherds being transported from centre of production to centre of consumption can be plotted on such a Beta-skeleton (only including those sites in which the ceramics in question were found). We can easily compare the relative positions of sites in these transportation networks, as we know the influence of our basic ‘distance’ network.

To test our hypothesis that proximity is an important parameter in the distribution of table wares, we have to analyse our ceramic networks and compare them to our basic networks. If the relative position of sites weighted by the ceramic evidence is similar to sites in a ‘distance network’, we can conclude that distance played an important role in determining trade relations and thus trade routes. If there is a significant difference between ceramic and distance networks, we can conclude that distribution was influenced by other parameters, e.g. personal contacts of traders and land owners. Testing the hypothesis for 15-year periods will allow us to identify periods in which distance was more likely to be a determining factor than others.

Some of the numerous issues with this method should be listed:

• although RNG is a formidable method for cluster analysis, it still does not take into account any of the complexities that determine trade routes. Could this method be combined with a cost-surface analysis to paint a more accurate picture of regional overland trade?

• Will the ceramic evidence influence the distance network to such a degree that its basic connectivity can be altered?

• Using a Beta-skeleton as the basis for testing our hypothesis might lead us to find exactly what we were looking for (distance = significant) because it is inherent in the network. Should the Beta-skeleton be compared with a more neutral network of ceramic distribution through space?

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