An infrastructure that encompasses geo-positioning capabilities and Internet-worked mobile computing devices is rapidly becoming available to increasing numbers of users. In anticipation of this development, the research community has been hard at work inventing foundations that enable location-based services that exploit this infrastructure. Such services may concern emergency management, transportation, information and social needs, and games, to name but a few uses.

This course aims to present an overview of key concepts in data management for services that involve location. The movement of a mobile object is captured by a trajectory, which is a function from time to points in the Euclidean, spatial-network, or indoor space in which the movement occurs. Tracking denotes the process of using a positioning system for continuously maintaining an up-to-date representation of a (partial) trajectory of an object. Prediction relates to aspects of the future trajectories of objects. Trajectory representations are inherently inaccurate. Further, location privacy may be an important concern.

Systems underlying location-based services may be subject to workloads that involve frequent updates as well as queries. This calls for efficient update as well as query processing techniques. Much attention has been given to offering efficient support for fundamental and an expanding range of novel query types, including one-time and continuous queries, queries that assume different underlying spaces and queries that concern the current locations of objects or their trajectories.

To support efficient querying of spatio-temporal data, including current locations and evolving or static trajectories, a number of indexing techniques have been proposed that are typically based on the R-tree or the B-tree. These techniques differ in how they contend with skew and other properties of the problem domain.

The following topics are planned for the course:

1. Motivation and infrastructure
Route prediction

2. Query Processing and indexing

Overview of indexing problems and approaches
Bottom-up updates in R-trees
The TPR-tree family
Query processing techniques
The Bx-tree family

3. Indoor data management techniques

Modeling of indoor space
Indexing and query processing


Lectures with exercises


A Master’s degree in computer science or similar and general familiarity with database management, as can be achieved through an undergraduate database course, is expected. Participants who have taken a graduate database course will benefit from this additional background.

Learning objectives:

To offer the participants insight into data management techniques related to outdoor and indoor location-based services.

Lecturer bio:

Christian S. Jensen is a Professor of Computer Science at Aarhus University, Denmark, and he was previously at Aalborg University for two decades. He recently spent a 1-year sabbatical at Google Inc., Mountain View. His research concerns data management and data-intensive systems, and its focus is on temporal and spatio-temporal data management. Christian is an ACM and an IEEE fellow, and he is a member of the Royal Danish Academy of Sciences and Letters and the Danish Academy of Technical Sciences. He has received several national and international awards for his research. He is currently vice-chair of ACM SIGMOD and an editor-in-chief of The VLDB Journal.


Professor Torben Bach Pedersen, email:


Professor Christian S. Jensen, email:




February 27, 13.00-17.00, February 28, 9.00-17.00, March 1, 9.00-17.00


Aalborg University
Selma Lagerlöfs Vej 300
February 27: room 02.11
February 28: room 02.90
March 1: room 02.90

Zip code:


Number of seats:

February 13, 2013

Important information concerning PhD courses

We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.