Towards a Human-Machine Scientific Partnership Based on Semantically Rich Research Objects

A research object is a single information unit encapsulating all the knowledge relevant to a particular scientific investigation, their associated metadata and the context where such resources were produced and came into play. Aimed at enhancing the preservation, reuse and scholarly communication of data-intensive science, research objects are both technical and social artifacts that represent a partnership between scientific communities and the computational support required in nowadays science. In this paper, we explore such partnership, identifying the lack of appropriate machine-readable metadata as one of its main inhibitors, and address the semantic enrichment of research objects as one key aspect towards its establishment. Focused on the specific needs of Earth Science communities, we propose extensions to research object representation models and present novel methods and tools to enrich research object metadata through automatic means. Finally, we validate the approach through the implementation of a recommender system that exploits the resulting metadata to facilitate research object discovery and reuse, enabling humans and machines to work together and accelerate the research life cycle.