Knowledge Architect/Operation/Management/Pipelines

Parallel Transformation Pipelines

While there may be different ways to effectively support and satisfy the processing-infrastructure requirements, streaming-content parallel transformation-pipelines, with XML-based knowledge resource representation, has been successfully implemented.

Universal content language, effectively combining data and meta-data, tightly integrated with a wide range of standards-based complementary technologies, XML can be efficiently streamed (e.g. STAX), stored, queried (e.g. Xpath, XQuery), referenced, transformed (e.g. XSLT), laid-out (e.g. XSL), styled (e.g. CSS), as well as loosely and/or strongly typed and structured (e.g. XSD).

With adaptive input and output content handling plug-ins, dynamic parallel (e.g. scalability) and chained (e.g. pipelined) streaming content transformation pipelines can be articulated and modulated by dynamic transformations that trigger on content nature and structure, to offer optimal processing generalization, specialization, flexibility, modularity, and performance.

Pipeline management engines, connect directly to systems, platforms, networks, and environments, dynamically integrate legacy systems, information, and data, stream and route information, as well as instantiate, orchestrate, and recursively invoke streaming-content transformation pipelines, to provide optimal interface and support for knowledge-aware applications.

Powerful processing generalization pattern, parallel transformation pipelines for streaming content combine the high performance and scalability of parallelization, the no-delay continuous dynamic processing of streaming content, the generalized model of meta-data and content-based modular transformations, with the logical granular structuring of flexible and dynamically interrelated pipelines.

The dynamic streaming nature of parallel transformation pipepines is also key to work-flow management, as well as for tracking content, contexts, access, and operations.