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The Challenge of Data Interoperability from an Operational Perspective

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Title: The Challenge of Data Interoperability from an Operational Perspective


1
The Challenge of Data Interoperability from an
Operational Perspective
  • Workshop on Information Integration
  • Todd Hughes
  • DARPA/IXO

2
The Challenge of Data Interoperability
  • Different weapons systems employ different
    transformation algorithms, which can induce
    degradation of accuracy due to rounding and
    approximations . . . Americas warriors are not
    fighting with a common positional picture,
    despite technological advances. (JP 3-09.3)
  • Different Services, and even different weapons
    platforms within the same Service, use a variety
    of coordinate formats. A working knowledge of
    different formats is often lacking between
    Services, which may induce error and/or delays to
    mission accomplishment. (Gruetzmacher et al
    2002)
  • In addition to the major combat units, OEF/OIF 4
    required specific capabilities supplemented
    within the theater . . . As these additional
    capabilities were added, the tracking of
    decomposed unit level organizations throughout
    the process became unmanageable . . . Although
    most of this information is available somewhere,
    it cannot be easily discovered or accessed in a
    timely manner, and does not render itself for
    easy manipulation by computers. (Chamberlain et
    al 2005)

3
Data Interoperability In Illustration
  • Data interoperability is rightly regarded as a
    pervasive, longstanding, and costly problem
  • Why has data interoperability research not
    enjoyed support commensurate with the severity of
    the problem?
  • It may help to consider data interoperability
    technology from a general operational perspective

Full Interoperability
100
Serviceable Interoperability
Non-interoperability
DataOperational Readiness
0
Operational Timeline ?
4
Data Interoperability Conventional
  • Data management systems do work well at the
    enterprise level
  • Certain aspects make them not a good fit for
    agile, dynamic organizations . . . such as the
    military in times of conflict
  • In times of conflict, operational timelines are
    to far too short for the enterprise acquisition
    model

100
Update
Update
Deployment
DataOperational Readiness
Conventional interoperability approaches take too
long to achieve operational readiness and require
too much downtime
0
Operational Timeline ?
5
Data Interoperability Semantic Web
  • The Semantic Web offers a better value
    proposition by enabling interoperability on an
    open scale
  • Price of admission is still high Semantic Web
    services, ontology engineering, client
    applications, service oriented architectures,
    etc.
  • Downstream benefit of new semantic capabilities
    are difficult to quantify

100
DataOperational Readiness
The Semantic Web promises greater extensibility
and robustness, but the startup costs are still
enormous.
0
Operational Timeline ?
6
Data Interoperability An Alternative
  • Future joint and multinational military
    operations will need to integrate in days, not
    months
  • Data interoperability technology must support ad
    hoc communities of interest with their respective
    legacy data sources
  • If the technology enabling the integration is
    fully assured, a serviceable level of integration
    may be sufficient
  • What technology framework would make this
    possible?

100
DataOperational Readiness
An Alternative Approach Achieve serviceable
interoperability rapidly Evolve toward full
interoperability Learn to update more efficiently
the next time
0
Operational Timeline ?
7
Proposal A Data Translation Appliance
  • Delivers transparent interoperability
  • Intercepts content from a data sources or their
    applications
  • Transforms content into syntactically well-formed
    and semantically equivalent messages
  • Sends messages to other sources or their
    applications
  • Field configurable by data users, not database
    administrators
  • Onboard intelligence, learning, and interface
    capabilities
  • Enables users to encode information
    transformation routines in a timely manner
  • Modular domain knowledge
  • Pluggable Community of Interest Ontologies
  • Supports operational integrated information
    exploitation
  • High data throughput
  • Ruggedizable
  • Certifiable
  • Forward-deployable
  • Semantic Technology Embedded in Translation
    Device
  • Data indexing and taxonomization
  • Data model extraction and enrichment
  • Data model alignment
  • Data translation and transformation

8
Prospects for a Data Translation Appliance
  • Appliance model of integration is not without
    challenges, both technical and operational
  • However, it may be a useful framework for
    discussion about the elements a successful
    research program in this area
  • Technical barriers
  • Metrics
  • Evaluation scenarios
  • Deployment strategies
  • Operational Impact
  • Return on investment
  • Such a device would provide a tangible means for
    data users to be directly involved in meeting
    their operational objectives
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