In July of 2011, we published a series of articles, “From Business as Usual to Knowledge-Driven Architecture” by Yefim “Jeff” Zhuk. The series outlined enterprise IT of the future with integrated software and knowledge engineering, further expanding on ideas originally described in the book “Integration-ready Architecture and Design.”

Image of the paper cover - I.T. of the Future: Semantic Cloud ArchitectureToday, we are pleased to offer Jeff’s latest article as a 27-page PDF file. In this new article, he focuses on the process of transitioning from IT architectures of today to Semantic Cloud Architecture with very practical “baby steps” — steps which require minimum upfront investment. The emphasis of this article is on collaborative work of business and enterprise architects with the Business Architecture Sandbox for Enterprise, (BASE) that was demonstrated at the 2012 Semantic Tech and Business Conference –San Francisco.

Zhuk says, “The discussed approach is gradually shifting the focus of IT from technology to information by standardizing business event processing, placing the seeds of semantic technology in the current business ground, and establishing a self-sustaining process of transformation to semantic cloud architecture. The article provides the context and speaks technical details for this transition.”

Read/Download the full paper (registration required)

As a teaser, here is the beginning of the article and Section Headings…

Transitioning from IT as we know today to Semantic Cloud Architecture

Enterprise IT as we know today is slowly disappearing. Some companies are transitioning their IT to a cloud. But even a bigger transformation is on the way. The transformation from complex reality of multiple integrated systems to a much simpler semantic architecture, which is more focused on the information itself than on the systems supporting information.

Graphic depiction of Linked Data plus Conversational Semantic Decision Support
Yes, Enterprise IT can be and will be very simple. And IT will come back to its original meaning, where Information comes first.
More than 50% of IT budget is currently dedicated to managing technical systems, not managing information.
Why? – Different types of information were historically present by different systems.

Semantic Technologies will change this forever by offering a unified landscape for all types of information.

Wait a minute! Specific data tables in specific applications make specific SQL queries perform faster. True! But in the increasingly interconnected business, integration efforts outweigh the benefits of specific approaches to specific data. Plus, a growing art and science of Big Data helps us absorbing a full story, not just small pieces of the story.

Just imagine that all enterprise information is collected in a single component, a cloud of Linked Data. Another component is Conversational Semantic Decision Support, a flexible mechanism, which can handle information for us and keep technical pieces, like SPARQL, behind the scenes. (SPARQL is a logical query language, similar to, but simpler than SQL.)

Collecting a complete set of enterprise information about business events, processes, and their relationships is a very challenging task. About 80% of this information is “tribal knowledge”, not captured properly or not captured at all. People constantly fill in the informational gaps with multiple meetings and phone calls. This is our “usual business” routine.

Computer programs have even less tolerance to informational gaps. So, we need to allow them, computer programs, to call us, subject matter experts (SME). In other words we need to establish conversational approach to the process of collecting data and resolving uncertainties. There are two key figures in this process: a SME who can answer the questions related to missing information, and a system architect who can structure right questions by modeling a domain of the business events and processes.

Transitioning from multiple systems into semantic enterprise architecture is an extra process, which is a hard sell in the current economic stage, when a lot of companies are struggling “just to keep the lights on”. To engage SMEs and architects in the process, they must get an easy entrance into the semantic world with immediate benefits, which would grow with every step in the semantic direction. The discussed approach requires minimum investment and expands the current process of standardization. At the same time it increases the role of business and IT collaboration and respectfully focuses on Business Architecture Sandbox for Enterprise (BASE). BASE offers to business an easy entrance and a playground to collaborate with IT, while placing the seeds of semantic technology in the current business ground and transitioning to a Semantic Cloud Architecture.

Section Headings

  • Transitioning from IT as we know today to Semantic Cloud Architecture
  • Business Architecture Sandbox for Enterprise (BASE)
  • Standard event processing with the BASE, ESB/Mule, and ActiveMQ
  • Integration strategy and Cluster Topology for high availability and fail-over
  • A semantic approach improves development and prevents duplication
  • Managing Enterprise Resources with the Semantic SOA Model
  • Development of Workflow Components within the semantic model
  • Establish the rules of the game with Decision Tables
  • “Data know how to handle data”
  • Collecting alert stories into critical situational descriptions
  • Prepare for multiple partners and business dialects
  • Semantically rich enterprise environment
  • Semantic Technology is the only Promised Land to surviving data storms

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About the Author

Photo of Jeff ZhukChief Architect at ITS, Inc., Yefim (Jeff) Zhuk, was leading Information Architecture at Sallie Mae, consulted government agencies and corporations in SOA and knowledge engineering, shared his expertise at Java One, Wireless One, and Boeing Conferences. Cambridge University Press published his book “Integration-Ready Architecture and Design”. In the book and several patents Yefim described a new field of Integrated Software and Knowledge Engineering.