UCR Database Lab

Some of the key research areas of the UCR DBLab are:
  1. Spatio-temporal queries: Indexing techniques for moving points and complex spatio-temporal pattern queries.
  2. Time series: Similarity searching in sequence databases, medical time series, and approximating range queries.
  3. Core data mining: Tools for visualizing and data mining, and adaptive classification techniques.
  4. Network data: Information retrieval in peer-to-peer systems, and analysis of sensor data.
  5. Search in databases: Information discovery in (semi)structured data, and results navigation.
  6. Data entry: Capturing and querying mixtures of structured and unstructured data.

We put emphasis on interdisciplinary projects, which have involved healthcare, entomology, disaster management, anthropology, and social networks.


  • Eamonn Keogh has created a time series repository for the data mining/machine learning community, to encourage reproducible research for time series classification and clustering. Webpage
  • Marios Hadjieleftheriou has created a Spatial Index Library which provides a general framework for developing spatial indices. Currently it defines generic interfaces, provides simple main memory and disk based storage managers and a robust implementation of an R*-tree, an MVR-tree and a TPR-tree. Webpage