Time Travel with the BiTemporal RDF Model
The Internet is not just used for communication, transactions, and cloud storage; it also serves as a massive knowledge store where both people and machines can create, analyze, and use data and information. The Semantic Web was designed to enable machines to interpret the meaning of data, facilitat...
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Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-06-01
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Series: | Mathematics |
Subjects: | |
Online Access: | https://www.mdpi.com/2227-7390/13/13/2109 |
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Summary: | The Internet is not just used for communication, transactions, and cloud storage; it also serves as a massive knowledge store where both people and machines can create, analyze, and use data and information. The Semantic Web was designed to enable machines to interpret the meaning of data, facilitating more informed and autonomous decision-making. The foundation of the Semantic Web is the Resource Description Framework (RDF). The standard RDF is limited to representing simple binary relationships in the form of the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo><</mo><mi>s</mi><mi>u</mi><mi>b</mi><mi>j</mi><mi>e</mi><mi>c</mi><mi>t</mi><mspace width="4pt"></mspace><mi>p</mi><mi>r</mi><mi>e</mi><mi>d</mi><mi>i</mi><mi>c</mi><mi>a</mi><mi>t</mi><mi>e</mi><mspace width="4pt"></mspace><mi>o</mi><mi>b</mi><mi>j</mi><mi>e</mi><mi>c</mi><mi>t</mi><mo>></mo></mrow></semantics></math></inline-formula> triple. In this paper, we present a new data model called BiTemporal RDF (BiTRDF), which adds valid time and transaction time to the standard RDF. Our approach treats temporal information as references instead of attributes, simplifying the semantics while enhancing the model’s expressiveness and consistency. BiTRDF treats all resources and relationships as inherently bitemporal, enabling the representation and reasoning of complex temporal relationships in RDF. Illustrative examples demonstrate the model’s support for type propagation, domain-range inference, and transitive relationships in a temporal setting. While this work lays a theoretical foundation, future research will address implementation, query language support, and compatibility with RDF streams and legacy systems. |
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ISSN: | 2227-7390 |