Keys for graphs incorporate the topology and value constraints needed to uniquely identify
entities in a graph. They have been studied to support object identification, knowledge …

Linked data aims at publishing data expressed in RDF (Resource Description Framework) at
the scale of the worldwide web. These datasets interoperate by publishing links which …

Exploiting identity links among RDF resources allows applications to efficiently integrate
data. Keys can be very useful to discover these identity links. A set of properties is …

A conditional key is a key constraint that is valid in only a part of the data. In this paper, we
show how such keys can be mined automatically on large knowledge bases (KBs). For this …

Data linking in knowledge graphs is a crucial and long-standing problem; it involves finding
identity links between different descriptions that refer to the same real-world entity. Keys …

Keys allow us to uniquely identify entities in a graph database. They have applications in
object identification, entity resolution, knowledge fusion, and social network reconciliation …

Keys for graphs uses the topology and value constraints needed to uniquely identify entities
in a graph database. They have been studied to support object identification, knowledge …

Links between heterogeneous data sets may be found by using a generalisation of keys in
databases, called linkkeys, which apply across data sets. This paper considers the question …

Link keys allow for generating links across data sets expressed in different ontologies. But
they can also be thought of as axioms in a description logic. As such, they can contribute to …

Keys for graphs are a class of data quality rules that use topological and value constraints to
uniquely identify entities in a data graph. They have been studied to support object …