Uppsala DataBase Laboratory

Welcome to Uppsala DataBase Laboratory (UDBL). We are a research group in the Department of Information Technology at Uppsala University, Sweden.

New: Run the Linear Road Benchmark simulation of a toll expressway system on your notebook: SCSQ-LR. Our massively parallel implemenation of the Linear Road Benchmark SCSQL-PLR scales orders of magnitude better than other implementations.

We are responsible for the Doctoral study subject area on Computer Science with specialization in Database Technology, TNDAVE04. There is a doctoral study plan in Swedish or English. We are teaching doctoral student level courses on modern database technology within the programme. We are periodically giving a course on Principles of Modern Database Systems.

For the undergraduate education we are responsible for courses in Database Design and Data Mining. We have co-authored the Swedish textbook on database technology: Databasteknik

Research

UDBL conducts research on methods and techniques for data and information management. Our research emphasis is on investigating how modern query processing can be used for querying and integrating information from heterogeneous databases, storage managers, and other information sources in a distributed environment.

The research direction of the group concentrates on developing methods for processing queries over distributed information in terms of i) semi-structured semantic web based representations and ii) high volume parallel data streams. A challenge in both cases is to provide scalable search as the data volume increases and the queries become complicated. Our approach is to develop smart data query transformation techniques and distributed query execution strategies.

Projects

New: We participate in SMART VORTEX, a Large Integrated Project co-financed by the European Union within the Seventh Framework Programme. The goal of the project is to provide a technological infrastructure consisting of a comprehensive suite of interoperable tools, services, and methods for intelligent management and analysis of massive data streams to achieve better collaboration and decision making in industrial product life cycles. The project is a collaboration between a number of European universities and industrial partners.

We participate in eSSENCE, a Swedish e-science research collaboration funded by VR to create a research environment where the interplay between different e-science competences will open up the field for novel applications, more realistic simulations, and new scientific solutions, models and methods.

In collaboration with Luleå University of Technology the iStreams project develops a distributed Data Stream Management System (DSMS) to efficiently monitor, filter, mine, and analyze large volume data streams originating in many vehicles or industrial products and equipments.

The goal of the project Scalable search of product life cycle information (SSPI) with support from SSF is to develop software systems for efficient and scalable search of product data and meta-knowledge produced during the entire product life cycle.
The project aims to produce (1) novel methods for scalable search in high volume data streams, (2) novel scalable methods to verify systems based on data stream management system (DSMS) technology, (3) novel searchable semantic web based models to preserve product data, and (4) novel ways to verify the functioning of products in use.

With support from Vinnova and ASTRON we have developed SCSQ (SuperComputer Stream Query processor), a Data Stream Management System (DSMS) to process very high volume scientific data streams. SCSQ runs in a massively parallel and heterogeneous computing environment containing Linux clusters and an IBM BlueGene computer. SCSQ executes data stream queries that filter, transform, and join data from receivers of low frequence space radio signals.

Finished projects

We organized EDBT: 14th International Conference on Extending Database Technology, and ICDT: 14th International Conference on Database Theory, March 21-25, 2011.

Within the EU project Advanced eGovernment Information Service Bus we developed scalable methods to search wrapped eGovernment virtual repositories in terms of semantic web representations and queries. The RDFViewer system enables encapsulating (wrapping) different kinds of data sources to make them available for semantic web tools to query using the query languages SparQL, RDQL, or SQL.The SWARD (Semantic Web Abridged Relational Databases) subsystem wraps relational databases according to some ontology and SWATM (Semantic Web Abridged Topic Maps) wraps Topic Map data.

In the POQSEC Project (supported by VR) we devlop a scalable and distributed query processor utilizing the peer-oriented GRID infrastructure NorduGRID. This project is an UPPMAX project.

In the GSDM project (supported by Vinnova) we developed a stream database query manager for high volume queries. This project was in cooperation with IRFU and ASTRON.

We participated in the project Personalized Access to Distributed Learning Repositories (PADLR) which was part of the Wallenberg global learning network research program on distributed collaborative learning innovations. Within PADLR we developed PSELO, a semantic web based query processing system for searching learning material from a peer-to-peer based educational infrastructure.

We collaborated with formerly Alzato Inc. in the development leading to the product MySQL Cluster, which is based on the PhD Thesis here.