The objective of this work is to discuss how vocabularies can contribute to assigning computational semantics to digital research data within the context of Big Data, so that computers can process them, allowing their reuse on large scale. A conceptualization of data is developed in an attempt to make it clearer what would be data, as an essential element of the Big Data phenomenon, and in particular, digital research data. It then proceeds to analyse digital research data uses and cases and their relation to semantics and vocabularies. Data is conceptualized as an artificial, intentional construction that represents a property of an entity within a specific domain and serves as the essential component of Big Data. The concept of semantic expressivity is discussed, and is used to classify the different vocabularies; within such a classification ontologies, are shown to be a type of knowledge organization system with a higher degree of semantic expressivity. Features of vocabularies that may be used within the context of the Semantic Web and the Linked Open Data to assign machine-processable semantics to Big Data are suggested. It is shown that semantics may be assigned at different data aggregation levels.