Ontology evolution aims at maintaining an ontology up to date with respect to changes in the
domain that it models or novel requirements of information systems that it enables. The …

Over the years, a large amount of temporal data needs to be shared and exchanged on the
Web. Resource Description Framework (RDF) has been widely accepted and has rapidly …

In this paper, we present a temporal extension of the SPARQL query language for RDF
graphs. The new language is based on a temporal RDF database model employing triple …

Abstract RDF (Resource Description Framework), a standard resource description model, is
popularized and applied in many application scenarios for its explicit representation of …

With the explosive growth of temporal data, how to query and manage temporal data has
become an important research issue. Resource description framework (RDF), as the …

The Internet serves not only as a platform for communication, transactions, and cloud
storage, but also as a vast knowledge store where both people and machines can create …

Temporal ontologies allow to represent not only concepts, their properties, and their
relationships, but also time-varying information through explicit versioning of definitions or …

Modern data-intensive applications have to manage huge quantities of streaming/relational
data and need advanced query capabilities involving combinations of continuous queries …

Event data is increasingly being represented according to the Linked Data principles. The
need for large-scale machine learning on data represented in this format has thus led to the …

The complex query is an essential type of knowledge graph query, which aims to deal with
the complex relationships among multiple triples involved in query problems. However, the …