VERA: virtual environment for research in archaeology

The VERA (Virtual Environment for Research in Archaeology) project is based on a research excavation of part of the large Roman town at Silchester, which aims to trace the site's development from its origins before the Roman conquest to its abandonment in the fifth century A.D. [1]. The VERA project aims to investigate how archaeologists use Information Technology (IT) in the context of a field excavation, and also for post-excavation analysis. VERA is a two-year project funded by the JISC VRE 2 programme that involves researchers from the University of Reading, University College London, and York Archaeological Trust. The overall aim of the project is to assess and introduce new tools and technologies that can aid the archaeological processes of gathering, recording and later analysis of data on the finds and artefacts discovered. The researchers involved in the project have a mix of skills, ranging from those related to archaeology, and computer science, though to ones involving usability and user assessment. This paper reports on the status of the research and development work undertaken in the project so far; this includes addressing various programming hurdles, on-site experiments and experiences, and the outcomes of usability and assessment studies.

The VERA information environment

We present three components of a virtual research environment developed for the ongoing Roman excavation at Silchester. These components — Recycle Bridge, XDB cross-database search, and Arch3D — provide additional services around the existing core of the system, run on the Integrated Archaeological Database (IADB). They provide, respectively, embedding of legacy applications into portals, cross-database searching, and 3D visualisation of stratigraphic information.

Meta-analysis of the INSIG2 association with obesity including 74,345 individuals: does heterogeneity of estimates relate to study design?

The INSIG2 rs7566605 polymorphism was identified for obesity (BMI> or =30 kg/m(2)) in one of the first genome-wide association studies, but replications were inconsistent. We collected statistics from 34 studies (n = 74,345), including general population (GP) studies, population-based studies with subjects selected for conditions related to a better health status ('healthy population', HP), and obesity studies (OB). We tested five hypotheses to explore potential sources of heterogeneity. The meta-analysis of 27 studies on Caucasian adults (n = 66,213) combining the different study designs did not support overall association of the CC-genotype with obesity, yielding an odds ratio (OR) of 1.05 (p-value = 0.27). The I(2) measure of 41% (p-value = 0.015) indicated between-study heterogeneity. Restricting to GP studies resulted in a declined I(2) measure of 11% (p-value = 0.33) and an OR of 1.10 (p-value = 0.015). Regarding the five hypotheses, our data showed (a) some difference between GP and HP studies (p-value = 0.012) and (b) an association in extreme comparisons (BMI> or =32.5, 35.0, 37.5, 40.0 kg/m(2) versus BMI<25 kg/m(2)) yielding ORs of 1.16, 1.18, 1.22, or 1.27 (p-values 0.001 to 0.003), which was also underscored by significantly increased CC-genotype frequencies across BMI categories (10.4% to 12.5%, p-value for trend = 0.0002). We did not find evidence for differential ORs (c) among studies with higher than average obesity prevalence compared to lower, (d) among studies with BMI assessment after the year 2000 compared to those before, or (e) among studies from older populations compared to younger. Analysis of non-Caucasian adults (n = 4889) or children (n = 3243) yielded ORs of 1.01 (p-value = 0.94) or 1.15 (p-value = 0.22), respectively. There was no evidence for overall association of the rs7566605 polymorphism with obesity. Our data suggested an association with extreme degrees of obesity, and consequently heterogeneous effects from different study designs may mask an underlying association when unaccounted for. The importance of study design might be under-recognized in gene discovery and association replication so far.