Data Mining of Online Genealogy Datasets for Revealing Lifespan Patterns in Human Population

Online genealogy datasets contain extensive information about millions of people and their past and present family connections. This vast amount of data can assist in identifying various patterns in human population. In this study, we present methods and algorithms which can assist in identifying variations in lifespan distributions of human population in the past centuries, in detecting social and genetic features which correlate with human lifespan, and in constructing predictive models of human lifespan based on various features which can easily be extracted from genealogy datasets. We have evaluated the presented methods and algorithms on a large online genealogy dataset with over a million profiles and over 9 million connections, all of which were collected from the WikiTree website. Our findings indicate that significant but small positive correlations exist between the parents' lifespan and their children's lifespan. Additionally, we found slightly higher and significant correlations between the lifespans of spouses. We also discovered a very small positive and significant correlation between longevity and reproductive success in males, and a small and significant negative correlation between longevity and reproductive success in females. Moreover, our machine learning algorithms presented better than random classification results in predicting which people who outlive the age of 50 will also outlive the age of 80. We believe that this study will be the first of many studies which utilize the wealth of data on human populations, existing in online genealogy datasets, to better understand factors which influence human lifespan. Understanding these factors can assist scientists in providing solutions for successful aging

Quantitative Analysis of Genealogy Using Digitised Family Trees

Driven by the popularity of television shows such as Who Do You Think You Are? many millions of users have uploaded their family tree to web projects such as WikiTree. Analysis of this corpus enables us to investigate genealogy computationally. The study of heritage in the social sciences has led to an increased understanding of ancestry and descent but such efforts are hampered by difficult to access data. Genealogical research is typically a tedious process involving trawling through sources such as birth and death certificates, wills, letters and land deeds. Decades of research have developed and examined hypotheses on population sex ratios, marriage trends, fertility, lifespan, and the frequency of twins and triplets. These can now be tested on vast datasets containing many billions of entries using machine learning tools. Here we survey the use of genealogy data mining using family trees dating back centuries and featuring profiles on nearly 7 million individuals based in over 160 countries. These data are not typically created by trained genealogists and so we verify them with reference to third party censuses. We present results on a range of aspects of population dynamics. Our approach extends the boundaries of genealogy inquiry to precise measurement of underlying human phenomena

The provision of fire services in rural areas

Fire services have been neglected in discussions of public service provision in rural areas. The way in which they are provided has a broader significance in terms of current debates about risk management. Fire service policy was transferred away from the Home Office, but the Bain Report provided the major stimulus to change. Early central government attempts to stimulate fire service provision in rural area were hampered by a lack of cooperation between local authorities. Rates of death from fire are influenced by attendance times and are particularly high in remote rural areas. The development of national standards of fire cover was focused on protecting property rather than saving lives with disproportionate funding being provided for urban areas. Social changes in rural areas have made it more difficult to secure sufficient numbers of retained fire fighters. It has proved particularly difficult to provide an adequate service in remote rural areas such as the Highlands and Islands of Scotland, despite recent policy initiatives there. Problems of providing fire cover are particularly acute on isolated islands. The development of integrated risk management plans should offer a more fine grained approach to providing fire cover. However, they may be too sophisticated for the task in rural areas and more traditional democratic mechanisms for expressing perceived community needs may have a greater relevance