Editorial

Abstract

Introduction

Visualising Mobility

Visualising transitions

Visualising trajectories

Discussion

Conclusions

Acknowledgements

References

Case Studies Index

Mapping the Life Course:
Visualising Migrations, Transitions & Trajectories

Humphrey Southall & Ben White

Email
Web page: http://www.lifeline.qmw.ac.uk/

Abstract

This case study explores alternative approaches to the visualisation of longitudinal datasets derived primarily from life histories for large numbers of individual people. Recent years have seen a large expansion of social science research based on such data, and an associated development of tools for statistical analysis: survival analysis, logit and probit modeling, and so on. However, visualisation tools are far less well developed. The study suggests that useful ideas can be borrowed from the work of time geographers active in the late 1970s and early 1980s, and focuses particularly on lifeline diagrams, in which individual lives are represented as horizontal lines on which events are marked by point symbols and states are shown by styles or colours of line.

The Case Study begins by discussing how best to visualise an individual's history of geographical movement, via a conventional map annotated with dates or possibly by a three-dimensional plot in which the vertical axis is time. It moves on to consider geographical movement by a large group of individuals, introducing both the lifeline diagram and an extended example, a large database constructed from the membership and benefit records of a 19th century trade union, the Steam Engine Makers' Society. Via this example, the Study moves on from geographical mobility to other transitions within individual lives, particularly the movements between being in work and being in receipt of various welfare benefits. The use of similar graphics to present transitions in the lives of other entities of interest to social scientists, such as regions and nations, is briefly discussed.

The remainder of the Case Study explores the potential application of computers for visualizaton. The size and complexity of longitudinal datasets makes fully interactive graphics currently hard to achieve without using exotic hardware. However, an interactive `lifeline viewer' could greatly assist researchers in exploring and interpreting lifelines for large numbers of individuals generated non-interactively. The essay reports on a range of contacts with researchers in the field, noting the fragmented pattern of activity and lack of specialised tools, but also the great interest and enthusiasm. It concludes by suggesting that if there are to be any new resources to develop visualisation methodologies within the social sciences, longitudinal research might benefit more than better developed fields such as Geographical Information Systems.