CEDAR: The Dutch Historical Censuses as Linked Open Data

In this document we describe the CEDAR dataset, a five-star Linked Open Data representation of the Dutch historical censuses, conducted in the Netherlands once every 10 years from 1795 to 1971. We produce a linked dataset from a digitized sample of 2,288 tables. The dataset contains more than 6.8 million statistical observations about the demography, labour and housing of the Dutch society in the 18th, 19th and 20th centuries. The dataset is modeled using the RDF Data Cube vocabulary for multidimensional data, uses Open Annotation to express rules of data harmonization, and keeps track of the provenance of every single data point and its transformations using PROV. We link these observations to well known standard classification systems in social history, such as the Historical International Standard Classification of Occupations (HISCO) and the Amsterdamse Code (AC), which in turn link to DBpedia and GeoNames. The two main contributions of the dataset are the improvement of data integration and access for historical research, and the emergence of new historical data hubs, like classifications of historical religions and historical house types, in the Linked Open Data cloud

The Aggregate Dutch Historical Censuses

Historical censuses have an enormous potential for research. In order to fully use this potential, harmonization of these censuses is essential. During the last decades, enormous efforts have been undertaken in digitizing the published aggregated outcomes of the Dutch historical censuses (1795-1971). Although the accessibility has been improved enormously, researchers must cope with hundreds of heterogeneous and disconnected Excel tables. As a result, the census is still for the most part an untapped source of information. The authors describe the main harmonization challenges of the census and how they work toward one harmonized dataset. They propose a specific approach and model in creating an interlinked census dataset in the Semantic Web using the Resource Description Framework technology

Linking past and present: augmenting historical municipality characteristics through harmonization and linkage with contemporary data

Goal: Setting up a pipeline for extending, improving and visualizing time series of municipality characteristics by means of data harmonization and linkage of historical and contemporary dataseries using Linked Data technologies (RDF). This project focused on increasing the data availability, data quality and visualization of characteristics of Dutch municipalities for the period 1795-2010. We did so by (1) combining data from historical and contemporary time series, (2) evaluating and improving on the quality of these time series, and (3) extending the availability of NLGIS maps for the last two decades in order to visualize municipality characteristics for two centuries