This book describes the next step of software evolution which could likely offer a solution to many problems. According to an ambitious author’s claim, this technology can even help fixing education and corporation. The goal of the book is to answer a million dollar question "how can we get there".

The gap between the realities of the current enterprise and Semantic Cloud Architecture seems so huge that most companies are very cautious in approaching this cliff. But in order for a company to benefit from new technologies a critical mass of linked knowledge must be collected through the transitioning of many different companies and industries to said new technologies. While this "catch-22" may seem inescapable, this book offers a transitioning process with practical "baby steps" and minimum investment. The book shares the methods and tools needed to plant the seeds of Big Data and Semantic technology in the current business ground, enabling the next technology revolution.
Background: The author developed, patented, and promoted new methods to simplify IT while providing unprecedented power of knowledge understood by people and machines.

Cambridge University Press published his first book sharing initial ideas on Integrated Software and Knowledge Engineering.

From Book Reviews: "This is the new road map for a new generation of students and specialists dedicated to the field of IT and information systems"
- Dr. V. Genin, International Academy of Higher Education, the UN

"An impressive attempt to re-define software and knowledge engineering for the post-dotcom era."

– V. Kaptelinin, Ph. D., Ume University, Sweden

"The book is a brilliant synergy of theory and experience."

– A. Nozik, General Director, SZMA International

From the Editor:

We are pleased to present this unusual book to our readers from business, IT management, architecture, and development circles.

IT of the future: Big Data and Cognitive Computing; Semantic Cloud Architecture and Artificial Intelligence components promise to save more than 50% of the current IT budget for big companies, while unleashing the power of knowledge.

The book starts with the fundamentals and provides the conceptual ground for the audience, then continues with the practical transitioning steps, including the architecture and code samples. The readers will be pleasantly surprised by The Message from 2040, a science-fiction story built-in the book. This projection of the nearest future shows unexpected turns of evolving economy and society with their conflicts between competitive and collaborative forces. The book ends with "the key to the future", providing access to Business Architecture Sandbox for Enterprise (BASE) and enabling learning and doing business with new revolutionary approaches.

About the author: Jeff (Yefim) Zhuk worked for Boeing, Intelligent Software Solutions, and Sallie Mae; consulted government agencies and corporations in SOA and knowledge engineering; shared his expertise at Java One, Semantic Technologies, Oracle and Boeing Conferences. In the publications and multiple patents he described a new field of Integrated Software and Knowledge Engineering. Through his work and in this new book he promoted the ideas and practical steps towards semantic enterprise with greatly simplified and efficient IT.
Hobby: Mountaineering
Contents: chapter samples
Part 1: Knowledge Driven Architecture

Part 2: Transitioning to Semantic Cloud

Part 3: Software Semantic Evolution with SOA, Microservices, RAML, DataSense by Mule and the Next Step

Part 4: Big Data and Semantic Tools at work

Part 5: Semantic Toolbox and its Magic for Validation of Development

Discussions with the first readers

The message from 2040 | Buy the book

If you like the magic of Artificial Intelligence with web and mobile applications and would like to become a magician - Join us at ITU

Introduction: Fixing Education and Corporation

A problem: education inequity

Job market in the US is changing much faster than in the most countries. Simpler jobs disappear while new and exciting opportunities appear on the horizon. Unfortunately, it is much easier to lose an existing job that to jump on a new fast moving wagon. The jumpers, who can catch up with the changes, are our educational elite.

There are many reasons for education inequity. Here is just one story.

When I was training a small team of DoD software architects and developers, one of the men stood out the most to me because he was always able to expand on any subject and had great questions. However, when he told me his story, I was surprised to learn that his elementary, middle and high schools considered him retarded, a "lost case". Just before college, he developed his own way of learning and later became a successful student in college and then a team-lead at work.

How many "lost cases" do we have in schools, colleges or in the workplace? How many students have trouble following along with the mainstream methods of education and vocational training? What is the percentage of students with learning differences or detrimental gaps in their education?

I was a corporate trainer, university and college instructor, taught in public and private schools, consulted and mentored business and technical teams. Usually less than half of the group can sync with the basic flow of materials and can understand a bigger picture of the developmental process. Going above and beyond, the best mentors can recognize those who are ready for advanced material and those that need more time or special attention. The most effective teachers develop ways to approach individual learning differences, fill in the gaps in their knowledge, keep the students engaged, and minimize the "lost cases".

We can enormously increase these efforts by utilizing the latest technology. By focusing on ending education inequity we will also solve the related program of the growing economic inequity in our society. "We" does not necessary mean the government or only the government. Private companies would also see a great payoff from an investment in resolving education inequity by enlarging the pool of skilled workers available. Furthermore, publicity of a company’s efforts in education would also serve to build up the company’s public image. And from a moral point of view, what could be a better payoff than fixing society’s problems?

Disconnect between Academia and Job Market

Here are just three of the major problems with mainstream education:
1. Colleges and Universities are enormously expensive, although considered to be the main channel for access to education.
This is no longer true. There are many ways to learn, and spending four to six years in school is just one of them. There are students who prefer a classroom, live instruction and dorm life. There are many others who are looking for the shortest path to a job. In all cases, learning is a lifelong process, and is not limited to the school years.

2. The Academic Curriculum is several years behind industry practice, even in the best of schools.
Academia is slow to change, partially due to the fact that accreditation takes years. Technology constantly accelerates, and each year the gap between industry practice and academic curriculum is growing.

3. After graduation from most schools, students have a significant loan to repay and a hard time finding their first career employment.
This is a direct consequence of the existing disconnect between academia and the job market.

Industry investments in technology are much greater than the investments in curricula, so it is not a surprise that affordable investments within the current approach to technical education cannot fix the problem.

Fixing the problem requires resolving two major disconnects:

- The disconnect between the job market and the education being provided by Academia.
- The disconnect between the mainstream approach and the capabilities of individual learners.
This second problem is well known to any teacher.
Usually less than half of the group can sync with the basic flow of material. The majority are behind, while a few individuals are bored and looking for the next step. Good mentors can recognize those who are ready for advanced material and those that need more time or special attention. Unfortunately, a teacher has to focus on the mainstream group. No extra resources are available to help the stragglers or to challenge top students to optimal achievement.

Changing the formula of education
The first thing is to expand professional education beyond Academia by establishing a direct link (the orange dashed line below) between students and the job market.

The current curriculum in colleges and universities is far behind industry practice.
For example, we still teach C and C++ to Information Technology students, but industry is looking for artificial intelligence (AI) programming skills [1, 2, and 3].
Academia, with its four-year colleges or six-year universities is no longer the only channel to professional education.
Educational material can be delivered over the Internet to any place and to almost any device. No one knows better what skills are needed today than subject matter experts (SMEs), and some of them (actually many of them) are willing to share.
Just imagine that a consulting company which is specialized in AI directly shares its knowledge in Java and AI, and, after several months of study, offers students consulting projects. With a well-focused curriculum, it is feasible to prepare students for professional work in several months (see [4]) instead of it taking several years.

This is not about Coding Schools, which miss a business side of the story.
Subject Matter Expert is not just a code expert. SME knows business goals of a company, business practices and business processes, all these extremely important components that are often lost in translation.
This is a great opportunity to expand education beyond Academia and directly connect students to the job market!

A solution to the problem: Creating educational materials is difficult. Subject matter experts will often miss the structure, format or sequence needed to convert their knowledge into high-quality educational materials.

I know this from my personal experience.
I am an IT consultant and a corporate trainer, university and college instructor. I have taught part-time in public and private schools, and also consulted and mentored businesses and technical teams.
Many times, I have had this funny feeling that concepts which looked absolutely straightforward and clear in my head appeared as spaghetti in class materials. A lot of work has been done, and inventions [Patents 1-6] produced, while looking for better ways to consistently create and deliver knowledge in appropriate structures.
I will describe several components of this work, including the conversational approach and Semantic Technology. It is not an artificial intelligence (AI) framework, although this approach and system is also used to teach AI fundamentals.

For a long period, AI lived on the bottom of the lake of opportunities. Recent years turned the lake into an ocean and the underwater current brought AI back to the surface. Nothing else is growing so quickly, with increasing demands for new skills and talents. Artificial intelligence can mean many things. I will focus on just one. Computer programs are becoming more helpful. They start working for us not just as stupid machines, but almost as partners. Partners usually talk to each other and good ideas are polished and clarified in brainstorming conversations.

The conversational approach to knowledge acquisition combines the power of Big Data and Semantic Technologies with human intuition. This combination has proved to be extremely helpful in converting knowledge into well-structured, properly formatted data. The Conversational Semantic Decision Support (CSDS) system, described in the book, IT of the future [1], helps SMEs to overcome this difficulty and produce course content.

How does it work? The magic is done in several steps:
- First, a system would ask (prompt) a SME about specific educational goals and help in creating a conceptual graph based on the goals.
- Then, CSDS will automatically build a decision tree/script to help prompt the SMEs in providing related information.
- Then the decision tree is used by a system to converse with a SME while retrieving the information and building a proper structure of correctly formatted educational materials based on the conceptual graph.
- The system also generates test questions for each subject of the conceptual graph in a semi-automated process.
The questions help to evaluate the student progress as well as the student perception of the materials from both quality and difficulty perspectives. Helping SMEs to become instructors will not only increase educational channels beyond Academia. This will directly connect students with the job market and significantly improve employment opportunities, especially for young people looking for their first job. Colleges and universities will survive. There are many students that need classrooms, friendly teamwork, and exciting social life outside of home. But new educational channels will compete with traditional schools and will impact school prices.

My personal 30-year experience of teaching in class and online, including challenging and exciting work with inner city students in Detroit, confirms: it is feasible during several months (not several years!) to develop a set of skills that opens the door to a profession. Regardless of the course major, I always start with introduction to Critical Thinking and Skills to Learn. These two subjects must be included in any course of study.

The end of the coursework is not the end of education; quite the opposite!

From this point, a person is getting a real job with real pay and has acquired a taste for continued learning.

The second major problem of current education is the disconnect between the mainstream approach and individual learning differences. In the future, I envision robots performing as teaching assistants. They will introduce better evaluation instruments, which will look more like games than tests. These games/tests will help to precisely measure a student engagement at each point of study. Robots will be especially successful with children. Not only due to enormous memory and quick thinking, and the ability to replicate custom copies while gaming simultaneously with multiple participants, but most importantly due to lack of emotional reactions. Robots can keep their cool in the situations that would drive a human teacher crazy. (2040, [5])

Teaching with regard to each student individual ability is the hardest part of being a teacher. One would like to do exactly that, but trying to focus on stragglers can result in the failure to complete the coursework for the majority of students.
Can technology help here?

While preparing the course, the Conversational Semantic Decision Support (CSDS) system focuses on building a conceptual graph of the course.
A conceptual graph usually includes dependent subjects, which can be found in publicly available sources. The system can help by collecting a variety of materials for each of such subjects, effectively creating a set of choices which can be used during the learning process. To optimize the learning process, the system gives hints to the teacher to adjust both the style and type of suggested content based on tests/evaluations of individual differences in student learning style and pace. Some students benefit from Test-Driven Learning, some need more samples and more SME time. The system is not (and should not be) completely automatic, but provides significant help to a SME working with students.
The system is not a dream or just a set of good ideas, but is more like a work in progress [4].

For example, Internet Technology University,, provides a platform for SMEs to post educational materials and teach students online. It is up to a SME to offer a price tag or free access.
By expanding the learning process beyond Academia, we establish a new paradigm, where companies can better fulfil their needs and students have a much better outcome from the learning process – the job!

Who will benefit from these changes?

1. First of all, those searching for their first job can follow job market trends.

Here are some statistics on starting salaries: For humanities and social sciences, the first job average salary is $35k-$40k. Information Technology is more generous. IT is awarding the first job with $60k-$70k salaries.

Let trust the free market. (This is especially easy for someone who lived at least several years in a government-regulated country.)

To get a job in a high-demand field, it is more important to have the skills to do the job than it is to have a degree!
Here I am admittedly on thin ice. We traditionally think that a degree means an education.

This is not true! We never stop learning... after we have a good start, and that starting point should not be as hard and expensive as it is today.

2. The same mechanism which helps a SME express her/his knowledge can help in unlocking and capturing tribal knowledge to benefit corporations. Corporate knowledge or know-how can be split into three categories:
- Structured data – in relational databases
- Unstructured data – text documents: regulations, business policies and instructions in folders and web sites
- And the biggest portion of information, which is used daily in business routine, but has never been captured.
It is so-called Tribal Knowledge [1].
My conservative estimate of the percentages of structured, unstructured and tribal knowledge is 10%, 20% and 70%.
By retiring baby boomers or replacing experienced and expensive with young and cheap workers, corporations actively lose huge portions of tribal knowledge.
Not only retirees, but other people leave the company for various reasons, expanding the void in corporate knowledge.
Sooner or later the business feels the pain, especially companies dealing with long-life products surrounded by an enormous volume of related rules and regulations.
The experienced and expensive would love to share their knowledge, but capturing tribal knowledge is tricky, and formalizing this information is even more difficult.

The Conversational Semantic Decision Support (CSDS) system helps to make this challenging task feasible. CSDS will transform the concept of a Corporate Knowledge Warehouse (CKW) into a working system.

What is a Corporate Knowledge Warehouse?
The CKW is a collection of electronic materials which describe enterprise processes, not only for people but also for a machine. Formalized as the integrated ontology of connected knowledge domains, CKW can be converted into specific formats for specific purposes.
For example, they can be converted into business rules and scenarios to drive business applications, as described in the Knowledge-driven architecture patent [1].
They can also be converted into educational and training materials for specific audiences. CSDS will prompt a SME for an initial structure and will help to build a conceptual graph. Then walking over the graph, it will help to create branches, while asking for examples and user stories and creating tests for each branch.
People will still be involved in the processes, but they will not need to repeat boring work, which can be done by the system. The system would engage a SME in conversations, asking to confirm a decision, fill in the knowledge gap in unexpected situations. Becoming part of daily routine, these conversations will effectively grow CKW, improving automation and productivity.
Enabling a SME as a great mentor and a wonderful teacher not only makes her or him a more valuable employee, but also a happier person.

Accelerating learning processes and keeping pace with changes in technology will address the imbalance between demand and supply.
Job stability does not lie in limiting global collaborative engineering, but in improving the ability to innovate, to learn quickly and change directions -- even run ahead of the game.

Developing personal and social mechanisms for quick adaptation to changes is a very natural and rewarding alternative to regulatory barriers. Technology is on our side today as a friend and a partner helping us to succeed.

We will reduce the necessity for brokerage between a student and a profession.
This is done in other industries. Smart applications such as Uber remove the necessity for brokers - receptionists at taxi stations. Smart applications directly connect consumers and producers.
Professional education will become less dependent on brokers, such as Academia and job agencies. Smart applications with CSDS will streamline professional education, directly connecting students and jobs.
These methods might also be used in regular schools!
The difference between high school and college could be less dramatic if middle and high schools included advanced subjects taught directly by SMEs from local companies.
This connection might also bring some social benefits for both parties.

3. Educational publishers will finally be in a position to offer templates (conversational scripts) helping authors, first of all the SMEs, to share their unique knowledge.

4. Consulting agencies, which often have the best SMEs in a specific knowledge domain, will become invaluable knowledge resources.
The system/platform helps SMEs sharing their unique knowledge in multiple ways, including Teaching-by-samples, Test-driven-study, and more. Some of these ways, such as Test-driven-study can be used for screening potential candidates.
There is an opportunity to grow a Knowledge Tree into a Global Knowledge Marketplace by collecting the tribal knowledge of individuals, their experience, stories, scientific and emotional context.

Frequently Asked questions from reader comments and email messages:
- Why it is different from Google and Wikipedia?
- Do you really think that a computer program can replace a good teacher?
These and other questions are discussed here...

While the book is about WHAT and HOW, this is WHY it was written. | Read more in the book
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