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<p>In recent decades, there has been a significant increase in the use of social networks, smart devices, and sensors that led to high-volume temporal data generation. Temporal modeling and querying of this huge data have been essential for effective querying and retrieval. However, custom temporal models have the problem of generalizability, whereas the extended temporal models require users to adapt to new querying languages. In this paper, we propose our novel <i>Cartempian</i> model by storing temporal interval as Cartesian points where the start time and the end time of an event are stored as the <i>x</i> and <i>y</i> axes of the Cartesian coordinate thus enabling spatial queries on graph data. Our model improves the retrieval of temporal data using an existing graph database system without extending with additional operators. We present how queries based on Allen’s interval relationships can be represented using our model on a Cartesian coordinate system by visualizing these queries. Temporal queries based on temporal intervals are then used to validate our model and compare with the traditional way of storing temporal intervals (i.e., as attributes of nodes). Our experimental results on a soccer graph database with around 4,&#xa0;000 games show that the spatial representation of temporal interval can provide significant performance (up to 3.5 times speedup) gains compared to a traditional model.</p>

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Cartempian model: a spatial perspective for temporal interval queries using graph databases

  • 期刊论文

  • 发表日期：

    2026年3月6日

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  • Alex Fotso,
  • Mallika Boyapati,
  • Ramazan Aygun

摘要

In recent decades, there has been a significant increase in the use of social networks, smart devices, and sensors that led to high-volume temporal data generation. Temporal modeling and querying of this huge data have been essential for effective querying and retrieval. However, custom temporal models have the problem of generalizability, whereas the extended temporal models require users to adapt to new querying languages. In this paper, we propose our novel Cartempian model by storing temporal interval as Cartesian points where the start time and the end time of an event are stored as the x and y axes of the Cartesian coordinate thus enabling spatial queries on graph data. Our model improves the retrieval of temporal data using an existing graph database system without extending with additional operators. We present how queries based on Allen’s interval relationships can be represented using our model on a Cartesian coordinate system by visualizing these queries. Temporal queries based on temporal intervals are then used to validate our model and compare with the traditional way of storing temporal intervals (i.e., as attributes of nodes). Our experimental results on a soccer graph database with around 4, 000 games show that the spatial representation of temporal interval can provide significant performance (up to 3.5 times speedup) gains compared to a traditional model.