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Distributed Data Management and Integration The Mobius Project

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Department of Biomedical Informatics. The Ohio State University. Outline. Motivation ... Integration of multi-institutional data sets across modalities. ... – PowerPoint PPT presentation

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Title: Distributed Data Management and Integration The Mobius Project


1
Distributed Data Management and Integration The
Mobius Project
  • Shannon Hastings and Stephen Langella,
  • Scott Oster, Joel Saltz
  • Department of Biomedical Informatics
  • The Ohio State University

2
Outline
  • Motivation
  • Use case
  • Mobius Overview
  • Mako Service
  • Virtual Mako
  • Grid PACS
  • Questions

3
Motivation
  • Integration of multi-institutional data sets
    across modalities.
  • Expose existing data resources with minimal
    effort
  • Provide methods for automatically creating
    databases to model new datasets.
  • Ability to execute distributed queries across all
    exposed data resources.
  • Provide methods for translating between data
    types
  • System should support any data type but promote
    the convergence and standardization of similar
    types.

4
Use Case
5
Mobius
  • The Mobius project attempts to define and build a
    set of services and protocols enabling the
    management and integration of both data and
    metadata.
  • Mobius Core Services
  • Global Model Exchange (GME)
  • Data Storage and Retrieval (Mako)
  • Data Integration and Translation (DTS)
  • Mobius Extension Services
  • Higher level query services, Adhoc federation
    services, Metadata Transportation Services.

6
Mako
  • Service framework that exposes data resources as
    XML data services through a set of well-defined
    interfaces based on the Mako protocol.
  • Interfaces based on the GGF DAIS working groups
    XML realization specification.
  • Example Operations
  • Insertion
  • Retrieval
  • XPath
  • XUpdate
  • Deletion

7
Mako Architecture
  • Abstract Communication Layer
  • Configurable Protocol Handling
  • Abstracts Mako Infrastructure from the underlying
    data resource
  • Protocol Handlers Specified at run time.
  • Abstract Handlers are extended to expose a
    particular data resource
  • Handlers are easy to write and deploy.

8
Mako Current Support
  • MakoDB
  • In house XML database, optimized for supporting
    specialized Mako features.
  • XML Databases
  • Handler implementation for the XMLDB API
  • Tested using Xindice and Exist
  • Relational Databases
  • Handler implementation for exposing relational
    databases using XBridge.
  • Requires the creation of a XBridge Map file.

9
Mako Features
  • Partial Retrieval
  • Distributed Document Object Model (DOM)
  • Binary Object Support
  • Mako protocol supports attaching binary objects
    to XML files.
  • Data Referencing

10
Virtual Mako
  • Simplifies client-side complexity of interfacing
    with multiple Makos by presenting a single
    virtualized interface to a collection of
    federated Makos
  • Acts as a data integration point for distributed
    queries
  • Pluggable algorithms for XML instance
    ingestion/distribution
  • Protocol request broadcast and response
    aggregation
  • Supports all services a standard Mako supports
  • Maps a Virtual Collection to a number of remote
    standard Collections

11
Grid PACS
  • Designed to address the storage, querying, and
    processing requirements of large-scale image
    databases in a grid wide environment.
  • Model-centric application, majority of backend
    implemented by simply submitting schemas to a
    number of Makos
  • Enables modeling and execution of image
    processing workflows

12
Grid PACS
  • Relies heavily on the Mobius Infrastructure
  • Data Referencing metadata and chunks of data
    distributed across grid via references
  • Partial Retrieval data retrieved on demand
  • Distributed DOM emulates local data environment
  • VMako query broadcast and aggregation
  • Model-driven data storage On demand creation of
    schema-based metadata and image storage
    collections on Makos

13
Mobius Team
  • David Ervin
  • Daniel Hall
  • Shannon Hastings
  • Stephen Langella
  • Scott Oster
  • Tony Pan
  • Joel Saltz
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