Semantically Interoperable Census Data: Unlocking the Semantics of Census Data Using Ontologies and Linked Data

Abstract

The Canadian Census of Population is a survey that collects statistical information on the Canadian population. These censuses contain valuable socioeconomic data that is often used by both the public and private sectors for project planning and decision-making. However, there are a few issues that may arise when using census data. Firstly, data wrangling, which is often a time-consuming process, needs to be conducted in order to clean and prepare the data for integration and use. Secondly, different datasets across different census years may be using different terms to describe the same concept/entity, hence creating a problem of referential equivalence (i.e., how do we know whether two different datasets are referring to the same concepts/entities?). Lastly, the data found in a census is often described using natural language that isn't easily interpreted by machines and can be difficult to break down or deconstruct. In this paper, we develop and propose the use of an ontology for representing the data from the Canadian Census of Population as linked data in order to address the aforementioned issues, evaluate the ontology using competency questions based on real world use cases, and discuss the advantages of census linked data for integration and visualisation uses.