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  \subsection{Academic Knowledge Graphs}  The Gene Ontology (GO), can (GO) may  be considered more of a knowledge graph than an ontology \cite{Ashburner_2000}. It has created embodies  a hierarchy of biological processes, cellular locations, and molecular functions into which a number of genes and proteins have been classified. classified or annotated.  These annotations have been curated by domain experts, and the provenance of each is recorded using a GO-specific provenance encoding.  YAGO (Yet Another Great Ontology) \cite{Suchanek_2007} and YAGO 2 \cite{Hoffart_2013} have been are  considered by some researchers to be knowledge graphs, although they started each originated  as a large, general-purpose ontology. While it aggregates they aggregate  knowledge from many sources, there are no published descriptions of if whether  or how provenance is tracked. tracked in YAGO and YAGO2.  The XLore system claims to be a fully bilingual (Chinese and English) knowledge graph that focuses on extracting \emph{subClassOf} and \emph{instanceOf} relations from free text \cite{wang2013xlore}.  SEKI@home is a crowd-sourced knowledge graph that is aggregated aggregates  from multiple sources \cite{steiner2012seki}.  This project maintains \cite{steiner2012seki}, maintaining  entity-level provenance using the PROV Ontology \cite{Moreau_2015}. The This  projecthas  also incorporated incorporates  real-time matching against news articles \cite{steiner_iswc_2012}. The Knowledge Vault handles knowledge graph uncertainty as a result of automated fact extraction from Web pages \cite{Dong_2014}.  DBPedia is a large-scale transformation of Wikipedia into a knowledge graph \cite{Bizer_2009}.  It uses a mostly fixed schema and provides provenance of which Wikipedia pages each entity was derived from.