Linked data modelling and transformation for geospatial and time-series data

The majority of open data published online nowadays are tabular and thus publishing RDF typically involves transforming data from tabular formats into graphs using mappings. Current approaches for mapping of data are designed to be generic in order to support arbitrary representations. In the case of geospatial and time series data this approach, although flexible, results in overly complicated  graph patterns, which are difficult to understand, prone to error, and non-intuitive. The mapping process can be significantly improved and streamlined by taking advantage of the well-established standards for expressing geospatial data, and the consistent structure of time series data. The thesis will involve inventing a simplified approach to represent time-series/geospatial data "to-RDF" mapping approach and implement a practical user interface to support the representation.