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Data interpretation is an important process in scientific investigations. It results in information and gives data meaning. As a case in point, earth and environmental scientists interpret data - increasingly often collected in large-scale environmental research infrastructures - to gain information about the studied environment. Information is typically represented to suit human consumption - in natural language text, figures and tables designed for expert processing. Building on a case study in aerosol science, we discuss how information resulting in data interpretation can be represented as machine readable information objects, here of type Interpretation. As the main contribution, we present the aggregation of interpretations in Research Objects. Together with data, metadata, workflows, software, and articles, interpretations are contextual resources of scientific investigations. The explicit aggregation of interpretations in Research Objects is arguably a further step toward a more complete representation of the context of scientific investigations. [ABSTRACT FROM AUTHOR]