Foundation concept: Cables and connectors.

Definition: Data encoded as pulses of light conducted along flexible transparent wires as a replacement for data sent as electrical pulses along a flexible metal wire.

Overview

The most familiar means for transmitting signals or data is by sending electrical impulses along a flexible metal (nearly always copper) wire. This has many advantages: electrical signals are the native internal infrastructure of all computing devices, so very little signal conversion is required; wires can easily be insulated to prevent cross-over with other signals; electronic signals travel along wire at the speed of light, so speed is maximized. There is also one major disadvantage: when electric currents pass through metal wires they generate magnetic fields, and when metal wires pass through varying magnetic fields, they pick up induced electric currents. This means that, whenever two signal wires run close together, they will interfere with each other, and whenever a wire passes near to any electronic device, it will pick up interference from it. Heavy-duty electro-mechanical devices, such as large electric motors, can easily generate enough interference to swamp any real signal, and even enough to damage connected electronic equipment.

Common alternatives, such as transmitting signals by radio or microwave, suffer from similar problems. Radio and microwave signals can not be insulated and can not be channeled along a “wire,” so multiple signals have to use significantly different wavelengths in order to avoid complete interference; electrically generated interference is still a problem for radio, and microwave signals need a straight “line-of-sight” unobstructed path to follow; and there may be significant environmental dangers associated with some wireless signals (there is some controversy, but microwave radiation in the environment is a major concern for many).

Definition: Also known as Navstar GPS, an electronic device that may rapidly and accurately determine its own geographical location by receiving signals from a network of orbiting satellites.

Overview

There are a few dozen special-purpose satellites, launched and maintained by the US military, in constant Earth orbit. They contain extremely accurate clocks, programmed knowledge of their own orbits (which is constantly corrected by signals from ground stations), and high-frequency radio transmitters. These satellites transmit a constant stream of data, which describes the exact time and their position, and can easily be picked up by terrestrial receivers.

A GPS receiver listens to the stream of data from a number of these satellites, and from it, using relatively simple geometry, can calculate its own exact position (longitude, latitude, and elevation) to an accuracy of just a few feet. These receivers can be made very small (around one square inch) and moderately cheaply (tens of dollars). Their primary use is as an aid to navigation (in aeroplanes, in smart guided missiles, and in hand units for use by people), but they may also be embedded into larger systems. By comparing a sequence of positions, a GPS unit may also determine its own speed and direction of movement, and the relevant portion of a digitized map may be automatically displayed.

Foundation concepts: Programming language, Algorithm.

Definition: A programming style that focuses on data objects and the operations performed on them as a whole, rather than concentrating purely on executable code and treating data as something that passively flows through it.

Overview

Object-oriented is one of the most popular bandwagons for computing professionals and organizations to jump upon. In reality it is a simple logical evolution in programming methodologies that has gradually been solidifying since the 1960s. It is certainly a Good Thing, but not necessarily the shiny bright new technology it is usually thought to be.

In the older, non-object-oriented style of programming, programmers concentrate on designing programs and algorithms that will process data. The data is viewed as a passive entity that flows through the program, and is worked on by it. Starting in a small way with Cobol in 1961, and fully taking off with the far more rational Algol-68 in 1968, programming languages provided ways of encapsulating large and complex data items, even whole databases, as single manipulable objects in a program. Programming was still viewed as producing instructions that say what to do with the data, but the data could be handled as a single well-defined object, not as an amorphous collection of binary digits.

These developments gave rise to the idea of Abstract data types (ADTs) as a tool used in the early stages of software development. With ADTs, all of the different kinds of data that a program will have to deal with are fully and formally defined, and an exact specification is provided for all of the valid operations on those data types.

Foundation concept: Programming language.

Definition: Standard, general-purpose programming languages.

Overview

The evolution of programming languages is a short but very complex story. By the mid 1970s the design of mainstream programming languages had branched in two directions: the general-purpose programming languages and the systems programming languages. General-purpose languages were strongly oriented towards supporting reliable software development; the structure of the languages corresponded closely to the structure of a good top-down design, providing programmers with a built-in framework for safe and verified construction; they were able to provide useful warnings about some of the most common things that could go wrong in a program's design before it is ever run, and they made many of the most troublesome of programmer errors impossible.

Unfortunately, what was good for general software development was not always good for low-level, or systems, programming. Implementors of operating systems, compilers, and hardware-monitoring software sometimes have to perform exactly the kind of low-level machine-oriented operations that are so strongly discouraged by the standards of good software development, and programming languages that enforce those standards are made almost unusable for such purposes.

As a result, the systems programming language branch of parallel evolution was also constructed. The essential feature of a systems programming language is that a programmer should be able to give any commands that the computer is capable of obeying, and not have to fight against builtin safety features if those commands do not satisfy some safety standard.

Foundation concepts: Storage, Information lifecycle management, Power protection.

Definition: Secondary copies of data and applications kept to guard against catastrophic loss in the event of a system failure.

Not to be confused with:BackUPS, the trade name of a variety of uninterruptible power supply.

Overview

Hardware failures do occur. They can be made less common by using only the most reliable hardware components, employing all available power protection technologies, and regularly monitoring system performance to catch problems before they occur, but nothing can prevent unexpected failure.

When a computer system suffers a hardware failure, it will sometimes leave data stored on disks undamaged, but some failures can destroy a disk drive, and some will result in damage to files: if an application is actively modifying a data file when the computer suddenly stops working, the file can be left in an intermediate state with just half of the change made (perhaps a balance transfer had credited one account but not yet debited the other), leaving the file's state invalid.

Sadly, amongst the most common forms of hardware failures are failures of the disk system itself. Damage may range anywhere from a slight degradation in performance to a complete loss of all data and the disk itself becoming unusable.

Additionally, software problems are very likely to cause loss of data. The presence of Bugs in applications is extremely wide-spread, and, if an application is “buggy,” it could do anything from occasionally failing to update files completely to accidentally deleting everything stored on the disk.

Foundation concept: Network.

Definition: A communication network provided by a third-party vendor that also provides guarantees of service quality, security, and reliable data transmission.

Overview

Value added networks (VANs) are provided by third parties such as the common carriers (telecommunications providers) which lease secure telecommunication connections to subscribers. VANs provide a variety of services together with the connection, including support of a variety of EDI standards (such as ANSI X.12, EDIFACT, and XML), data security standards (for data encryption, a Secure sockets layer, etc.), multiple levels of password authorization, and communication protocols such as X.25 and TCP/IP.

Business value proposition

VANs provide secure networks capable of high-bandwidth data transmission that range from T1 at 1.544 Mbps to OC48 at 2.4 Gbps, together with service-quality guarantees and data security services. The decision to purchase may be based upon the technical need together with the financial aspects of the lease: subscribers pay a base fee plus per-service costs. The analysis of total cost of ownership has to be based upon the use of and need for the services. VANs offer a variety of services and charges are based upon their usage: the amount of data transmitted, fees for connections to other VANs, mailbox charges, help-desk service charges, data-archiving fees, service plan fees, and user and technical training fees.

Summary of positive issues

VANs provide a secure, high-quality, professionally managed and maintained mechanism for connecting with other organizations and entities.

Foundation concepts: Internet, World Wide Web.

Definition: In their own words, “The World Wide Web Consortium (W3C) is an international consortium where member organizations, a full-time staff, and the public work together to develop web standards” (http://www.w3.org/Consortium/).

Overview

The W3C was founded in 1994 by Tim Berners-Lee, the inventor of the World Wide Web, and MIT in collaboration with CERN, DARPA, and the European Commission. The organization aims to develop inter-operable technologies and provide specifications, guidelines, software, and tools to help the web to reach its full potential. A primary aim of the consortium is to develop non-proprietary standards and promote inter-operability. The consortium is international in scope, has offices in fourteen locations around the world, and draws its membership from around the globe (http://www.w3.org/).

The W3C is behind many of the technologies that are in common global use, such as HTML, SOAP/XMLP, URLs, and XML.

Business value proposition

The W3C is an organization that provides leadership in the area of web technologies. Individuals and corporations can become members and, through working committees, help to develop the formulations of future web-based technologies.

Summary of positive issues

W3C provides a forum through which web-based technologies are developed. Organizations are able to join the consortium and work with the committees to innovate and create new technologies.

Foundation concept: Domain name.

Definition: The non-profit corporation delegated responsibility for the allocation of IP addresses and other internet-related identifiers by the US Department of Commerce.

Overview

IP addresses and domain names are critical to the operation of the internet, and at the top level must be managed by a recognized authority. The US Department of Commerce somehow became the international authority for such things, and delegates that authority to the Internet Corporation for Assigned Names and Numbers (ICANN). It is a non-profit corporation, with an international board, and has subsumed the former responsibilities of the Internet Assigned Numbers Authority (IANA).

ICANN usually allocates IP addresses in large groups to regional authorities, who then allocate them individually or in smaller groups to ISPs and other organizations. ICANN is also responsible for the overall management of DNS, the Domain Name Service, and creates the top-level domains (such as “.com” and “.org”) and the national domains (such as “.uk” and “.nu”).

ICANN is often blamed, completely unfairly, for the fact that IP addresses are running out, and organizations in the developing world might not be getting the share they would like. They are also sometimes blamed, perhaps less unfairly, for the fact that prices for registration are much higher than they once were, and this is seen as unreasonably favoring the old established organizations over new ones.

Definition: An organized collection of information.

Overview

A collection of files and records is just raw data. Once it has been organized, rationalized, and formatted so that it can be effectively accessed in a uniform way, enabling general queries to be answered by a simple procedure, it becomes a database.

Rational organization is of course essential for any effective record keeping, but for a database system the demands are far more rigorous. A database system will be expected to be able to answer queries totally automatically. To answer even the simplest of queries, such as “what is the salary of the employee named Q. X. Smith in the advertising department?,” mechanically, without any access to intelligence, requires an established format to the data. A human searcher could simply leaf through all the employee records; they would easily be able to pick out the employee's name and their departmental assignment from each form, because everybody knows what proper names look like. It is just common sense; nobody would ever confuse a department name with a social-security number even if they were written in unexpected places on the form.

Of course, computers don't have common sense, and can't be expected to know what makes a credible name for a human. For any such query to be answerable, every single employee record must be formatted uniformly, so that the query application knows exactly where in each record to find the employee's name, department, and salary.

Foundation concept: Programming language.

Definition: A popular object-oriented programming language, derived from C++ but with many significant differences, some of them improvements.

Not to be confused with: JavaScript.

Overview

For many years, C++ was the only programming language available for largescale programming projects that properly supported modern programming methodologies, apart from the very unpopular Ada. For all its popularity, which continues unabated, C++ has many faults, which can not possibly be rectified without changing it into a fundamentally different kind of language. C++ has many safety features, which would go a long way toward making programs more reliable, but none are enforced; programmers can and do override them at will. C++ carries with it the unfortunate legacy of older languages (most of the old C language survives as part of C++), and it almost encourages an unstructured overcomplicated style of programming. The language itself is exceptionally complex (the official standard fills 774 pages), and very few expert programmers are aware of all of its rules.

Java was developed by a small team at Sun Microsystems, and released to the public in 1995. It was intended to do many good things: remove or replace the worst features of C++, be a relatively simple language that can be completely known and understood, provide safety features that programmers can not choose to ignore, fully embody the object-oriented design methodology, provide automatic cross-platform compatibility for all programs, provide a uniform simplified access to “windowy” graphical user interfaces, be “internet-friendly,” provide an extensive thoroughly tested library of programming utilities, and allow secure execution, guaranteeing that programs from untrusted sources can not do any harm.

Foundation concept: Artificial intelligence.

Definition: The development and use of techniques to understand natural language input and to formulate an intelligent response.

Overview

Since the earliest days of computing, the idea of interacting with a machine through speech has been very appealing. To do so requires solving two problems: firstly, a system must be able to take a captured audio signal and recognize the words within it; and secondly, the system then has to be able to understand what the whole thing means. Researchers have been working upon both of these problems and have achieved a certain degree of success in each. It is not uncommon for business users to interact with airline reservation systems, for example, through an automated voice-recognition system. Many of the more successful systems bypass most of the first stage by accepting only typed input, not audible speech.

The origins of Natural language processing (NLP) are almost as old as computing itself. In the 1950s and 1960s researchers began to develop a variety of techniques aimed at understanding the ways computers could be used to provide NLP. One such system, Eliza, was created by Joseph Weizenbaum, whose system pretended to be a psychologist with whom a dialog could be enacted; a typical interaction with Eliza might start like this:

1. Eliza: How are you?

2. Human: I'm feeling ill.

3. Eliza: How long have you been feeling ill?

4. Human: Just a few days.

5. Eliza: Do carry on.

What is this book about and who should read it?

This book is about facilitating change with component technology, but is different from most approaches to the topic. The components in the book are not traditional I/T components. Rather they are shared components of knowledge from which patterns of business knowledge are assembled. A fundamental premise of this paradigm is that meanings are patterns of information, abstract structures that may be derived from other components, which are also meanings. If we can identify and describe these components and their structures with precision, we can automate the process. Business processes and information systems configured from these components will be extremely flexible, configurable, and coordinated.

This book lays the foundation of a new computing paradigm – a paradigm in which computers manipulate meanings, not program code or blind symbols. Computers of the future, built on the principles described in the book, will operate on the plane of meanings – a little like we do.

Business meanings, patterns, and rules jointly constitute the substance of a business process. Without the business layer, technological standards have little meaning. The return on investment from reusing business knowledge can complement, and be orders of magnitude larger than by adherence to technical standards alone. This book establishes a framework for the transfer and reuse of business knowledge in different contexts. This is why we urge architects interested in service oriented architecture and business process management to read this book. This book is for information and process architects.

Activity (and other) costs (Module V, section 3).

Aggregate object. A collection (Module V, section 2). A composition is a structured aggregate.

Array (Chapter 4, section 1).

Assemble. A polymorphism of process and the part of relationship (Module V, section 4). Assemble emerged from a process that made an item a part of an aggregate in step with the flow of time. Similarly disassembly cuts the relationship between an aggregate and its parts, so that the part does not remain a part of the aggregate after disassembly has occurred. Thus disassemble is also a process, but it is a polymorphism of the exclude relationship (near the top of figure 116). Polymorphisms of disassemble will tell us how an aggregate is picked apart – explosively, all at once, or in steps – perhaps even one item at a time.

Attribute. A kind of object property that is also a subtype of domain. It is a relationship between an object class and a subtype of a domain that consists of a single value at any given time (Chapter 3, section 2).

Beginning and ending moments of an event (both are subtypes of moment).

Borel object. A generalization of the concept of array, useful for categorization and segmentation of objects and state spaces – a power set of values, or an infinitely large power set of ranges (see Module V, section 1).

Bounds (Chapter 3, section 2).

Capacity. A kind of cardinality constraint (see Module V, section 1).

Attributes have meanings. So have their values. Domains are the wellspring of meaning. Domains are sets of values. These values are measures of a meaning.

What does being a measure of meaning mean? Consider a room. Assume it is 30 feet long, 20 feet wide, and 10 feet high. These numbers describe the dimensions of the room. However, by themselves the numbers are only numbers. They mean nothing. Numbers only measure magnitudes, not meaning. Moreover, different numbers might describe the same dimensions. For example, measured in inches, the same room would be 360 units long, 240 units broad, and 120 units high. The larger numbers do not mean that the room has some how expanded; they only mean that the values of length, breadth, and height, i.e., the meaning of these values, have been expressed by mapping them to different sets of numbers.