CORDIS
EU research results

CORDIS

English EN

HeisenData - Towards a Next-Generation Uncertain-Data Management System

Project information

Grant agreement ID: 249217

Status

Closed project

  • Start date

    1 March 2010

  • End date

    28 February 2014

Funded under:

FP7-PEOPLE

  • Overall budget:

    € 100 000

  • EU contribution

    € 100 000

Coordinated by:

POLYTECHNEIO KRITIS

Greece

Objective

Several real-world applications need to manage and reason about large amounts of data that are inherently uncertain. For instance, pervasive computing applications must constantly reason about volumes of noisy sensory readings, e.g., for motion prediction and human behavior modeling; information-extraction tools can assign different possible labels with varying degrees of confidence to segments of text, due to the uncertainties and noise present in free-text data. Such probabilistic data analyses require sophisticated machine-learning tools that can effectively model the complex correlation patterns present in real-life data. Unfortunately, to date, approaches to Probabilistic Database Systems (PDBSs) have relied on somewhat simplistic models of uncertainty that can be easily mapped onto existing relational architectures: Probabilities are typically associated with individual data tuples, with little or no support for capturing data correlations. This research proposal aims to design and build a novel, extensible PDBS that supports a broad class of statistical models and probabilistic-reasoning tools as first-class system objects, alongside a traditional relational-table store. Our proposed architecture will employ statistical models to effectively encode data-correlation patterns, and promote probabilistic inference as part of the standard database operator repertoire to support efficient and sound query processing. This tight coupling of relational databases and statistical models represents a major departure from conventional database systems, and many of the core system components need to be revisited and fundamentally re-thought. The proposed research will attack several of the key challenges arising in this novel PDBS paradigm (including, query processing, query optimization, data summarization, extensibility, and model learning and evolution), build usable prototypes, and investigate key application domains (e.g., information extraction).

Coordinator

POLYTECHNEIO KRITIS

Address

Building E4, Technical University Campus Counoupidiana
731 00 Chania

Greece

Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 100 000

Administrative Contact

Nikolaos Varotsis (Prof.)

Project information

Grant agreement ID: 249217

Status

Closed project

  • Start date

    1 March 2010

  • End date

    28 February 2014

Funded under:

FP7-PEOPLE

  • Overall budget:

    € 100 000

  • EU contribution

    € 100 000

Coordinated by:

POLYTECHNEIO KRITIS

Greece

This project is featured in...