WikiData is a famous knowledge base that aims at representing facts.
But, what if facts are disputed?
For example, in spite of Ukraine and the United Nations stating that the Crimean Peninsula belongs to Ukraine, Russia claims otherwise. Even if Wikidata editors may favor one option over the other, they do not decide upon what constitutes the truth. As long as there is an official publication that acts as a source, they represent a fact and that it is stated by this source.
Thus, Wikidata constitutes an Epistemic Knowledge Graph, i.e. a knowledge graph where the epistemological status of a fact is expressed, e.g. who states it.
In general, epistemology goes beyond attributing a source. Indeed, a source could also refute a fact, believe a fact, or express that it is unsure about a fact. In our paper, we propose a mechanism to represent and query Epistemological Knowledge Graphs - a task that is hard to do in Wikidata,but becomes much more natural with novel epistemic operators. Check out the full paper and learn how agnostic and atheistic beliefs can be reconciled in our epistemological approach.
eSPARQL: Representing and Reconciling Agnostic and Atheistic Beliefs in RDF-star Knowledge Graphs
Authors: Xinyi Pan, Daniel Hernández, Philipp Seifer, Ralf Lämmel, Steffen Staab.
Abstract: Over the past few years, we have seen the emergence of large knowledge graphs combining information from multiple sources. Sometimes, this information is provided in the form of assertions about other assertions, defining contexts where assertions are valid. A recent extension to RDF which admits statements over statements, called RDF-star, is in revision to become a W3C standard. However, there is no proposal for a semantics of these RDF-star statements nor a built-in facility to operate over them. In this paper, we propose a query language for epistemic RDF-star metadata based on a four-valued logic, called eSPARQL. Our proposed query language extends SPARQL-star, the query language for RDF-star, with a new type of FROM clause to facilitate operating with multiple and sometimes conflicting beliefs. We show that the proposed query language can express four use case queries, including the following features: (i) querying the belief of an individual, (ii) the aggregating of beliefs, (iii) querying who is conflicting with somebody, and (iv) beliefs about beliefs (i.e., nesting of beliefs).