arXiv subjects

John Samuel

Publications and source records attributed to John Samuel.

5 recordsLinked to original sources

arXiv2026

QuaQue: Design and SQL Implementation of Condensed Algebra for Concurrent Versioning of Knowledge Graphs

The management of versioned knowledge graphs presents significant challenges, particularly in querying data across multiple versions efficiently. This paper introduces QuaQue, a key component of the ConVer-G system, which addresses this challenge by translating SPARQL (SPARQL Protocol and RDF Query Language) queries into SQL (Structured Query Language). QuaQue leverages a novel condensed algebra to operate on a relational model where versioning information is compactly stored using bitstrings. This approach allows for efficient querying of concurrent versions of knowledge graphs within a standard relational database system. We present the key concepts of our condensed algebra, detail the translation process from SPARQL algebra to SQL, and provide a comparative benchmark against a native RDF (Resource Description Framework) triple store, demonstrating the viability and performance benefits of our approach.

cs.DB↗

arXiv2025

Condensed Representation for Snapshot-Based RDF Graphs

Evolving phenomena, often complex, can be represented using knowledge graphs, which have the capability to model heterogeneous data from multiple sources. Nowadays, a considerable amount of sources delivering periodic updates to knowledge graphs in various domains is openly available. The evolution of data is of interest to knowledge graph management systems, and therefore it is crucial to organize these constantly evolving data to make them easily accessible and exploitable for analysis. In this article, we will present and formalize the condensed representation of these evolving graphs and propose a new solution called QuaQue that allows querying across multiple versions of graphs and we also present the results of our benchmark comparing our solution against existing approaches.

cs.DB↗

arXiv2024

Graph versioning for evolving urban data

The continuous evolution of cities poses significant challenges in terms of managing and understanding their complex dynamics. With the increasing demand for transparency and the growing availability of open urban data, it has become important to ensure the reproducibility of scientific research and computations in urban planning. To understand past decisions and other possible scenarios, we require solutions that go beyond the management of urban knowledge graphs. In this work, we explore existing solutions and their limits and explain the need and possible approaches for querying across multiple graph versions.

cs.DB↗

arXiv2024

ConVer-G: Concurrent versioning of knowledge graphs

The multiplication of platforms offering open data has facilitated access to information that can be used for research, innovation, and decision-making. Providing transparency and availability, open data is regularly updated, allowing us to observe their evolution over time. We are particularly interested in the evolution of urban data that allows stakeholders to better understand dynamics and propose solutions to improve the quality of life of citizens. In this context, we are interested in the management of evolving data, especially urban data and the ability to query these data across the available versions. In order to have the ability to understand our urban heritage and propose new scenarios, we must be able to search for knowledge through concurrent versions of urban knowledge graphs. In this work, we present the ConVer-G (Concurrent Versioning of knowledge Graphs) system for storage and querying through multiple concurrent versions of graphs.

cs.DB↗

arXiv2004

A Simple Cellular Automaton Model for Influenza A Viral Infections

Viral kinetics have been extensively studied in the past through the use of spatially homogeneous ordinary differential equations describing the time evolution of the diseased state. However, spatial characteristics such as localized populations of dead cells might adversely affect the spread of infection, similar to the manner in which a counter-fire can stop a forest fire from spreading. In order to investigate the influence of spatial heterogeneities on viral spread, a simple 2-D cellular automaton (CA) model of a viral infection has been developed. In this initial phase of the investigation, the CA model is validated against clinical immunological data for uncomplicated influenza A infections. Our results will be shown and discussed.

q-bio.CB↗