Progressive Data Integration and Semantic Enrichment Based on LinkedScales and Trails

The integration of data elements scattered along different resources, with heterogeneous formats, can take advantage of an approach with progressive and lightweight steps, instead of pursuing costly upfront mappings. To support such approach, we defined a multiscale-based dataspace architecture, called LinkedScales, which carries an integration process via graph-based transformations over a graph database. A series of scales in the dataspace systematizes an integration and enrichment chain of steps to leverage transformation processes, which incrementally go from raw representations towards ontology-like structures. However, how to record and keep track of the intermediary outcomes in the integration chain remains an open research challenge. This article proposes combining the concept of scales with trails – lightweight, scale-specialized semantic annotations to enable progressive integration towards a semantic representation. We conduct experiments involving organism-centric analysis in life science to show the benefits of trails for transformation between scales.