I’m interested in organizations as information systems. Groups of machines can store, transmit and manipulate physical tokens (data processors?). Communities of people imbue these marks and signals with many additional semiological properties and use them to communicate their meanings, intentions and values thereby providing information in the sense that the sign-tokens have the effect of forming or reforming one another’s attitudes. Information is sign-tokens in a social context that adds to them properties that are intrinsic to a certain human community. A data processing system in a human context can function as ‘information systems’. People create meanings, express intentions and have values; machines do not.
Machines can embody, through the ways they function, the meanings, intentions and values of the people who built them or commissioned them. That is another, interesting issue related to the exercise of power.
Programming machines to imitate the intelligent behavior of a person is a valuable exercise for advancing our programming ability. An alternative to artificial intelligence is the augmenting of the real intelligence of teams of people by using machines. Our work began in 1971 and it soon led to the problems of semantics, which we approached via some philosophical questions. So, of course, we would answer your question in the affirmative.
Since I joined Ontolog as an observer, I have been puzzled by your use of ‘ontology’ to label a particular kind of data model / conceptual model / <whatever the data processing community used to call them>. One of my first assignments in my first job was to improve the management of stock in a group of hospitals. Many books on the subject were about ‘inventory management’ but an inventory is a rather complex sign that stands for the stock. I was not interested in managing an inventory but the stock. Obviously a marketing person had been at work. Was the short, Anglo-Saxon “stock” was not respectable enough for those authors compared with “inventory” with its root in Latin.
I used to teach systems analysis methodology by having the students learn several methods before beginning a comparative and critical analysis of them, which is to say before making a methodological study. If you call each method “a methodology” you can easily just teach several different methods and overlook the important critical comparative study of them. Is marketing the motive for “methodology” displacing the simpler, more accurate “method”?
When I saw the term “ontology” used for what I had known as a kind of data model / etc., admittedly of an interesting, novel kind, I wondered what the tacit ontological assumptions might support them. It looks like either a marketing ploy or a deliberate evasion of ontology, a key philosophical issue. I am still puzzled.
The route we took to solve the problems of semantics involved being quite clear what the signs were able to stand for in order to be meaningful. If you are dealing with a terminology, your terms can stand for dictionary definitions, as an answer to the ontological question. You can have your terms stand for Platonic Ideals, or concepts in someone’s mind, and so on. We needed our terms to stand for things in what the managers and other people working in and organization or the judge and other people involved in a legal process would regard as the “real world”. Searching for a real world semantics thrusts one face-to-face with the metaphysical issues of ontology.
Then we had to be clear how the signs and the objects they stand for connect to that real world, so that we can justify any claim to know about the world that our signs purport to inform us about. That is to say, provide an account of the epistemological issues.
At an information systems conference, when I used the terms “ontology” and “epistemology” while presenting a paper on the work we were doing, the chair of the session, a professor of computer science, stopped the session to tell me that I should not use such terms and that, if I persisted in that line of enquiry, I would become “stuck in a philosophical bog.”
I’m pleased to report that we crossed the bog safely and are now happy with our treatments of both ontology and epistemology, as least as engineers working on the development of information (not data processing) systems in business, administration and the law.
However, I still remain puzzled about the tacit ontologies or ontology behind the “ontologies” I call sophisticated, mainly hierarchical, data models
Are the participants in ontolog willing to disclose this information?
Regards,
Ronald Stamper