Recent years have witnessed the increase of openly available knowledge graphs online. These graphs are often structured according to the W3C semantic web standard RDF. With this availability of information comes the challenge of coping with dataset versions as information may change in time and therefore deprecates the former knowledge graph. Several solutions have been proposed to deal with data versioning, mainly based on computing data deltas and having an incremental approach to keep track of the version history. In this article, we describe a novel method that relies on aggregating graph versions to obtain one single complete graph. Our solution semantically compresses similar and common edges together to obtain a final graph smaller than the sum of the distinct versioned ones. Technically, our method takes advantage of FCA to match graph elements together. We also describe how this compressed graph can be queried without being unzipped, using standard methods.