  Application developers today have three choices for exploiting the knowledge
present in Wikidata: they can download the Wikidata dumps in JSON or RDF
format, they can use the Wikidata API to get data about individual entities, or
they can use the Wikidata SPARQL endpoint. None of these methods can support
complex, yet common, query use cases, such as retrieval of large amounts of
data or aggregations over large fractions of Wikidata. This paper introduces
KGTK Kypher, a query language and processor that allows users to create
personalized variants of Wikidata on a laptop. We present several use cases
that illustrate the types of analyses that Kypher enables users to run on the
full Wikidata KG on a laptop, combining data from external resources such as
DBpedia. The Kypher queries for these use cases run much faster on a laptop
than the equivalent SPARQL queries on a Wikidata clone running on a powerful
server with 24h time-out limits.
