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Christian S. Jensen

Researcher at Aalborg University

Publications -  541
Citations -  26166

Christian S. Jensen is an academic researcher from Aalborg University. The author has contributed to research in topics: Temporal database & Query language. The author has an hindex of 80, co-authored 507 publications receiving 24234 citations. Previous affiliations of Christian S. Jensen include University of Maryland, College Park & Zhejiang University.

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Transitioning Temporal Support in TSQL2 to SQL3.

TL;DR: This document summarizes the proposals before the SQL3 committees to allow the addition of tables with valid-time and transactiontime support into SQL/Temporal, and explains how to use these facilities to migrate smoothly from a conventional relational system to one encompassing temporal support.
Journal ArticleDOI

Extending existing dependency theory to temporal databases

TL;DR: This paper defines a consistent framework of temporal equivalents of the important conventional database design concepts: functional dependencies, primary keys, and third and Boyce-Codd normal forms, which apply equally well to all temporal data models that have timeslice operators.
Proceedings ArticleDOI

Building Accurate 3D Spatial Networks to Enable Next Generation Intelligent Transportation Systems

TL;DR: A novel filtering and lifting framework is proposed that augments a standard 2D spatial network model with elevation information extracted from massive aerial laser scan data and thus yields an accurate 3D model.
Book ChapterDOI

The islands approach to nearest neighbor querying in spatial networks

TL;DR: A versatile approach to k nearest neighbor computation in spatial networks, termed the Islands approach, able to manage the trade-off between query and update performance and obviates the need for using several k nearest neighbors approaches for supporting a single service scenario.
Proceedings ArticleDOI

Efficient indexing of the historical, present, and future positions of moving objects

TL;DR: The BBx -index structure is proposed, which indexes the positions of moving objects, given as linear functions of time, at any time, and supports queries that select objects based on temporal and spatial constraints.