Currently, Europe is confronted with industrial restructuring, migration, aging of population and financial crisis in a world of accelerated change. Learning from (social-economic) history helps to understand the interrelation between macro-economic change and individual lifestyles, policy regimes, labour markets, communities and national wealth. However, sources of historical information about the lives of individuals, communities, and nations are still scattered.
This project takes Dutch census data as a starting point to build a semantic data-web of historical information. With such a web we will answer questions such as:
- What kind of patterns can we identify and interpret in expressions of regional identity?
- How to relate patterns of changes in skills and labour to technological progress and patterns of geographical migration?
- How to trace changes of local and national policies in the structure of communities and individual lives?
Census data alone are not sufficient to answer these questions. This project applies a specific web-based data-model – exploiting the Resource Description Framework (RDF) technology– to make census data inter-linkable with other hubs of historical socio-economic and demographic data and beyond. Pattern recognition appears on two levels: first to enable the integration of hitherto isolated datasets, and second to apply integrated querying and analysis across this new, enriched information space. Data analysis interfaces, visual inventories of historical data and reports on open-linked data strategies for digital collections are results of this project. The project will result in generic methods and tools to weave historical and socio-economic datasets into an interlinked semantic data-web.