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 Approved for Public Release, Distribution Unlimited

2. The Challenge of Data Interoperability “Different weapons systems employ different transformation algorithms, which can induce degradation of accuracy due to rounding and approximations . . . America’s 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) Approved for Public Release, Distribution Unlimited

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  Approved for Public Release, Distribution Unlimited

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% Deployment Update Update DataOperational Readiness Conventional interoperability approaches take too long to achieve operational readiness and require too much downtime 0% Operational Timeline  Approved for Public Release, Distribution Unlimited

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  Approved for Public Release, Distribution Unlimited

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  Approved for Public Release, Distribution Unlimited

7. 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 Proposal: A Data Translation Appliance Approved for Public Release, Distribution Unlimited

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 Approved for Public Release, Distribution Unlimited