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Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
09:43

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

Performance database: capturing data for optimizing distributed streaming workflows.

Chee Sun Liew1, Malcolm P Atkinson, Radoslaw Ostrowski

  • 1School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh EH8 9AB, UK. c.s.liew@sms.ed.ac.uk

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
|July 20, 2011
PubMed
Summary
This summary is machine-generated.

A new performance database (PDB) collects workflow enactment data. Analyzing this data can significantly enhance workflow efficiency and performance.

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Area of Science:

  • Computer Science
  • Data Management
  • Workflow Optimization

Background:

  • Workflow enactment generates substantial performance data.
  • Existing data management strategies may not fully leverage this information for optimization.
  • The Advanced Data Mining and Integration Research for Europe project identified a need for specialized performance data handling.

Purpose of the Study:

  • To introduce and justify the concept of a Performance Database (PDB).
  • To propose a systematic implementation approach for the PDB.
  • To demonstrate the practical application and benefits of the PDB using real-world workflow data.

Main Methods:

  • Design and development of a prototype Performance Database.
  • Collection of performance-related data during workflow enactment.
  • Analysis and manipulation of PDB data to identify optimization opportunities.
  • Validation using real-world experimental workflows.

Main Results:

  • The PDB effectively stores and organizes performance data from workflow enactments.
  • Analysis of PDB data reveals potential avenues for improving workflow efficiency.
  • Demonstrated practical usage of the PDB in optimizing real-world workflows.

Conclusions:

  • A systematic approach to performance data management via a PDB can lead to enhanced workflow efficiency.
  • The PDB serves as a valuable tool for understanding and optimizing complex computational processes.
  • Further development and adoption of PDBs can benefit scientific research and data integration efforts.