Semantic Technologies and Text Analysis in Support of Scientific Knowledge Reuse

Abstract

Research objects act as a semantically rich container of all the information that lead to a scientific result, and have the potential to change how data intensive science shares and reuses methods, datasets and results. Despite a comprehensive set of vocabularies to describe semantically the aggregated resources, users often limit themselves to provide metadata at the container level, ignoring the valuable information that the aggregated resources contain. In this poster we explore how the combination of semantic technologies and natural language processing can be used to enrich research objects with structured metadata aiming at enhancing their findability as a crucial aspect towards their reuse.