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EnsMart: A Generic System for Fast and Flexible Access to Biological Data

EnsMart: A Generic System for Fast and Flexible Access to Biological Data. Arek Kasprzyk et al (2004) 14:160-169, Genome research EBI, Wellcome Trust. Objectives. Understand the idea of a “Data Mart” Understand why this idea is useful to biology Have an idea of how Ens Mart works.

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EnsMart: A Generic System for Fast and Flexible Access to Biological Data

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  1. EnsMart: A Generic System for Fast and Flexible Access to Biological Data Arek Kasprzyk et al (2004) 14:160-169, Genome research EBI, Wellcome Trust

  2. Objectives • Understand the idea of a “Data Mart” • Understand why this idea is useful to biology • Have an idea of how EnsMart works. • Assess the significance of the EnsMart system. Will it last?

  3. Data Mart defined • A database that is potentially derived from many other databases whose primary purpose is query processing and report generation for non-technical users. • Similar to a “Data Warehouse” • Marts/warehouses important components in “decision support systems” in business.

  4. Data Mart in EnsMart • Data collected • Standardized • Query Optimized • Presented to Users

  5. Marts – benefits • Allows good division of labor • Computers for transactions separate from computers for queries • Interface development separate from database development. • Biologists (can be) separated from computer scientists as a result of good interface design. • Produces faster more stable system for users

  6. Costs • Construction of the Mart is a challenging and continuous process. • New sources of data need to be incorporated and validated constantly • Trust

  7. The case for EnsMart, why now? • Growing number of different databases and opportunities. Genomes, expression, protein, disease… • Assembled, high quality genomes available. • “finished” genomes can be used as references to link data from different databases consistently. • EnsMart built to take advantage of the opportunities for cross-database queries.

  8. Inside EnsMart • 9 organisms • At least 17 different primary sources of data, many with multiple databases. • 2 kinds of “Foci” • Genes • Ensemble • EST • Vega • SNPs

  9. EnsMart schema Many Many One Focus 1 Many Many

  10. EnsMart schema: another focus

  11. Schema -> Query Speed • “Central” tables or foci contain binary values for each satellite indicating existence. First step in query generation limits the range of satellite tables accessed. • These values are only useful in the query process (take extra space and time for transactions). • Many queries may not require access to satellite tables as a result.

  12. User Interfaces • Supposedly Confucian quote • "What I hear I forget. • What I see I remember. • What I do I understand."

  13. User Interfaces • MartView: website, “wizard” query construction. • MartExplorer: Stand alone tool, tree-based query construction. • MartShell: text-based application that utilizes an SQL-like query language. Can be used interactively or in batch processes. • Write your own! – using MartLib java library

  14. MartView 1 Mart View 1 Choose org and focus

  15. MartView 2 Design query

  16. MartView 3 Specify Output

  17. MartExplorer

  18. MartShell

  19. Conclusions • Powerful query system for biologists. • Useful framework for software engineers. • All open source! • What about other loci such as repetitive elements? • Data validation? • Annotation updates?

  20. EnsMart Discussion • What, if any, are the problems with the foci system? • What alternatives to this system exist? • Describe a task that EnsMart could be used to accomplish. • Describe any personal experiences with EnsMart.

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