William Kent
First published over twenty years ago, this little classic addresses timeless questions about how we as human beings perceive and process information about the world we operate in, and how we struggle to impose that view on our data processing machines. The concerns at this level are the same whether we use hierarchical, relational, or object-oriented information structures; whether we process data via punched-card machines or interactive graphic interfaces; whether we correspond by paper mail or e-mail; whether we shop from paper-based catalogs or the web. No matter what the technology, these underlying issues have to be understood.
You can read this book for insights into the basis of computer data processing. You can also read it for insights into the way we perceive reality, and the constructs and tactics we use to cope with complexity, ambiguity, incomplete information, mismatched viewpoints, and conflicting objectives.
This new edition preserves the original content with minor cleanup and a new preface. The format, though, has been thoroughly modernized. That ugly typewriter font is gone! It's now a pleasure for the eyes as well as the mind. And it's still as relevant as ever.
Bill Kent likes to write about information processing as well as a variety of non-technical topics. His published technical papers, both tutorial and advanced, cover the relational data model, data analysis and design, entity-relationship models, object technology, and other areas of information processing.
Bill's career in data processing spans thirty-seven years at IBM and Hewlett-Packard. At HP's Research Laboratory in Palo Alto, California, he helped develop a prototype object-oriented database system and a follow-on prototype supporting interoperability of heterogeneous database systems.
Bill was a founder and first chairman of the NCITS (National Committee for Information Technology Standards) Committee on Object Information Management (formerly ANSI X3H7). He served as acting chair of the ANSI/SPARC DBSSG Object-Oriented Database Task Group. Other activities include ANSI X3H2 (Database) and IFIP TC2.6 (Data Bases), as well as the Object Management Group (OMG), serving on their Technical Committee, Object Model Subcommittee, and Database Special Interest Group.
Bill enjoys writing, photography, canyon country, Tai Chi, drumming, skiing, rafting, and a few other things. You can discover more at his web site: http://www.bkent.net .
A brief sampler of Bill's publications:
A Simple Guide to Five Normal Forms in Relational Database Theory, Communications of the ACM, Feb. 1983.
The Many Forms of a Single Fact, Proc. IEEE COMPCON, Feb. 27-Mar. 3, 1989, San Francisco.
The Leading Edge of Database Technology, in E.D. Falkenberg, P. Lindgreen (eds), Information System Concepts: An In-depth Analysis, North Holland, 1989. Also in F.H. Lochovsky (ed), Entity-Relationship Approach to Database Design and Querying, Elsevier Science Publishers (North Holland), 1990.
The Breakdown of the Information Model in Multi-Database Systems, SIGMOD Record, Dec 1991.
A Rigorous Model of Object Reference, Identity, and Existence, Journal of Object-Oriented Programming, June 1991.
The Objects Are Coming!, Computer Standards and Interfaces, July 1993.
Richard Soley and William Kent, The OMG Object Model, in Modern Database Systems: The Object Model, Interoperability, and Beyond, Won Kim (editor), ACM Press/Addison-Wesley, 1995.
A message to mapmakers: highways are not painted red, rivers don't have county lines running down the middle, and you can't see contour lines on a mountain.
For some time now my work has concerned the representation of information in computers. The work has involved such things as file organizations, indexes, hierarchical structures, network structures, relational models, and so on. After a while it dawned on me that these are all just maps, being poor artificial approximations of some real underlying terrain.
These structures give us useful ways to deal with information, but they don't always fit naturally, and sometimes not at all. Like different kinds of maps, each kind of structure has its strengths and weaknesses, serving different purposes, and appealing to different people in different situations. Data structures are artificial formalisms. They differ from information in the same sense that grammars don't describe the language we really use, and formal logical systems don't describe the way we think. 'The map is not the territory' [Hayakawa].
What is the territory really like? How can I describe it to you? Any description I give you is just another map. But we do need some language (and I mean natural language) in order to discuss this subject, and to articulate concepts. Such constructs as 'entities', 'categories', 'names', 'relationships', and 'attributes' seem to be useful. They give us at least one way to organize our perceptions and discussions of information. In a sense, such terms represent the basis of my 'data structure', or 'model', for perceiving real information. Later chapters discuss these constructs and their central characteristics ¾ especially the difficulties involved in trying to define or apply them precisely.
Along the way, we implicitly suggest a hypothesis (by sheer weight of examples, rather than any kind of proof ¾ such a hypothesis is beyond proof): there is probably no adequate formal modeling system. Information in its 'real' essence is probably too amorphous, too ambiguous, too subjective, too slippery and elusive, to ever be pinned down precisely by the objective and deterministic processes embodied in a computer. (At least in the conventional uses of computers as we see them today; future developments in artificial intelligence may endow these machines with more of our capacity to cope.) This follows a path pointed out by Zemanek, connecting data processing with certain philosophical observations about the real world, especially the aspects of human judgment on which semantics ultimately depend ([Zemanek 72]).
In spite of such difficulties (and because I see no alternative), we also begin to explore the extent and manner in which such constructs can and have been incorporated into various data models. We are looking at real information, as it occurs in the interactions among people, but always with a view toward modeling that information in a computer based system. The questions are these: What is a useful way to perceive information for that purpose? What constructs are useful for organizing the way we think about information? Might those same constructs be employed in a computer based model of the information? How successfully are they reflected in current modeling systems? How badly oversimplified is the view of information in currently used data models? Are there limits to the effectiveness of any system of constructs for modeling information?
