A practical workshop teaching hands-on experience with a variety of network science approaches will be offered the two days before the conference. Please note that workshop places are strictly limited to 20 people. Registration for the workshop is possible through the conference registration page.
Workshop programme:
Tuesday 22 August
10-12: an introduction to network science in archaeology. Key concepts, methods, and history of research (Tom Brughmans).
12-13: lunch
13-15: exploratory network analysis with Visone. Import archaeological data as network, network visualisation, network analysis (Tom Brughmans).
15-15:30: coffee break.
15:30-16:30: applying network approaches in archaeological research: personal experiences, advantages, pitfalls (Anna Collar, Fiona Coward).
16:30 onwards: informal project consultation in the pub. Discussions on how network science could work within your research context. Bring your data and fascinating research ideas and let’s talk.
Wednesday 23 August
9-10: an introduction to agent-based modelling in archaeology. Key concept, methods, hands-on tutorials, overlap and differences with network research (Iza Romanowska).
10-12: agent-based network modelling with Netlogo. First steps tutorial, simulate processes over networks, generate different network structures, importing networks, geographical layouts (Tom Brughmans).
12-13: lunch.
13-14: network visualisation. Key concepts, diverse approaches, temporal and multi-modal data, demonstration of NetworkCube as an example (Benjamin Bach).
14-14:30: coffee break.
14:30-15:30: Spatial Interaction Modelling I : Motivation and Description (Ray Rivers)
Spatial Interaction Models (SIMs) provide a useful framework for dynamical networks when data is too poor for Data modelling and when geography is important. The models described will range from intrinsically Bayesian Constrained Entropy/Gravity models through Intervening Opportunity Models to Cost-benefit Analysis.
15:30-16:30: Spatial Interaction Modelling II : Applications (Tim Evans)
In this session we look at some examples which illustrate the virtues and limitations of different models. In particular, we show how, despite uncertainties in the inputs and the stochastic ambiguities of the outputs, it is possible to develop robust outcomes.
16:30 onwards: informal project consultation in the pub. Discussions on how network science could work within your research context. Bring your data and fascinating research ideas and let’s talk.