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Model-Based Data Engineering for Web Services

This article discusses the concepts and techniques of model-based data engineering for web services, including data management, data alignment, and data transformation. It also explores the challenges of conflicts in data engineering and proposes solutions using open standard web-based approaches. The potential for automation of data administration, alignment, and translation based on data management is also highlighted. The article concludes with a case study on integrating XML-based services into military systems using web-based standards.

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Model-Based Data Engineering for Web Services

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  1. Model-Based Data Engineering for Web Services Charles Turnitsa Virginia Modeling Analysis and Simulation Center Old Dominion University

  2. Data Engineering

  3. Data Administration Managing the information exchange needs incl. source, format, context of validity, fidelity, and credibility Data Management Planning, organizing and managing of data, define and standardize the meaning of data as of their relations Data Alignment Ensuring that data to be exchanged exist in all participating systems Data Transformation Technical process of mapping information elements to each other (often implemented in gateways and interfaces) Components of Data Engineering

  4. Conflicts to be solved by Data Engineering • Heterogeneous Conflicts • Methods used to describe data are substantially different (such as UML and IDEF1X) • Structural Conflicts • Different structures used to describe same data (such as lists and vectors) • Descriptive Conflicts • Homonyms, synonyms, etc. describing the same data • Semantic Conflicts • Concepts do not match exactly, (dis-)aggregation, partial overlap, etc.

  5. Conflicts solved by open standard web-based Data Engineering • Heterogeneous Conflicts • Common XML descriptions avoid heterogeneous conflicts • Structural Conflicts • Use of common reference model represented in XML map structural conflict areas to the same elements • Descriptive Conflicts • Standardized XML tag sets avoid homo- and synonyms, etc. • Semantic Conflicts • MAIN REMAINING INTELLECTUAL CHALLENGE

  6. Model BasedData Management

  7. General Idea of Model Based Data Management • The Reference Model is the standard capturing the meaning of the data • Reference model sets the standard in ambiguous situation • Information of general value must be captured by the reference model • The reference model must provide information to all participating system, that means, the reference model must have the highest resolution (as aggregation always introduces information loss = ambiguity)

  8. Using Model Based Data Managementto integrate XML based Servicesinto Military Systems

  9. Web-based Standards supporting Data Engineering • XML as the common syntax and format of all components • Data source registers data description following the idea of Universal description, discovery, and integration registries (UDDI) • Mapping of data will be management of tag sets • After data management using tag set, data alignment becomes one-to-one comparison • Data management can lead to XSLT schema for data translation Potential for Automation of Data Administration, Data Alignment and Data Translation based on Data Management

  10. 2 (1) Data Modeling and Data Documentation- XML Document 1 XML C2IEDM (2) Data Administration 1 • Data Management- Mapping to C2IEDM- Extending C2IEDM- Enhancing C2IEDM 3 1 4 (4) Data Alignment ! (5) Data Transformation- Generate XSLT (+) XSLT 5 XSLT XSLT (+) Bringing in all together – XML Data Mediation Services based on the C2IEDM

  11. C2IEDM Bringing in all together – XML Data Mediation Services based on the C2IEDM (1) Data Modeling and Data Documentation- XML Document International C2IEDM/MIP 1 (2) Data Administration 1 XML XSLT (+) • Data Management- Mapping to C2IEDM- Extending C2IEDM- Enhancing C2IEDM XML XSLT (+) 1 XSLT (+) XML (4) Data Alignment (5) Data Transformation- Generate XSLT (+)

  12. Questions http://www.vmasc.odu.edu

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