The recent big data movement resulted in a surge of activity on layering declarative
languages on top of distributed computation platforms. In the Semantic Web realm, this
surge of analytics languages was not reflected despite the significant growth in the available
RDF data. Consequently, when analysing large RDF datasets, users are left with two main
options: using SPARQL or using an existing non-RDF-specific big data language, both with
its own limitations. The pure declarative nature of SPARQL and the high cost of evaluation …

… We believe that this is applicable in more scenarios such as RDF results caching and
view management. … We believe that this is applicable in more scenarios such as RDF
results caching and view management. … We believe that this is applicable in more
scenarios such as RDF results caching and view management. …