Information modeling (also known as conceptual modeling or semantic
data modeling) may be characterized as the formulation of a model
in which information aspects of objective and subjective reality
are presented (ldquothe applicationrdquo), independent of datasets
and processes by which they may be realized (ldquothe systemrdquo).
A methodology for information modeling should incorporate a number
of concepts which have appeared in the literature, but should also
be formulated in terms of constructs which are understandable to
and expressible by the system user as well as the system developer.
This is particularly desirable in connection with certain ldquointimaterdquo
relationships, such as being the same as or being a part of.
The conceptual basis for such a methodology, as conventionally approached,
seems flavored with notions arising in the systems arena to an inappropriate
degree. To counter this tendency it is useful to turn to a discipline
not hitherto much involved in technology, namely analytic philosophy.
%0 Journal Article
%1 ashenhurst1996
%A Ashenhurst, Robert L.
%D 1996
%J Minds and Machines
%K - Information actions analytic and attributes categories data development entities epistemology events information kinds knowledge model modeling object-oriented ontology paradigm philosophy reality relational relationships semantic statements systems the views vs.
%N 3
%P 287--394
%R 10.1007/BF00729802
%T Ontological Aspects of Information Modeling
%U http://www.springerlink.com.ezp01.library.qut.edu.au/openurl.asp?genre=article&id=doi:10.1007/BF00729802
%V 6
%X Information modeling (also known as conceptual modeling or semantic
data modeling) may be characterized as the formulation of a model
in which information aspects of objective and subjective reality
are presented (ldquothe applicationrdquo), independent of datasets
and processes by which they may be realized (ldquothe systemrdquo).
A methodology for information modeling should incorporate a number
of concepts which have appeared in the literature, but should also
be formulated in terms of constructs which are understandable to
and expressible by the system user as well as the system developer.
This is particularly desirable in connection with certain ldquointimaterdquo
relationships, such as being the same as or being a part of.
The conceptual basis for such a methodology, as conventionally approached,
seems flavored with notions arising in the systems arena to an inappropriate
degree. To counter this tendency it is useful to turn to a discipline
not hitherto much involved in technology, namely analytic philosophy.
@article{ashenhurst1996,
abstract = {Information modeling (also known as conceptual modeling or semantic
data modeling) may be characterized as the formulation of a model
in which information aspects of objective and subjective reality
are presented (ldquothe applicationrdquo), independent of datasets
and processes by which they may be realized (ldquothe systemrdquo).
A methodology for information modeling should incorporate a number
of concepts which have appeared in the literature, but should also
be formulated in terms of constructs which are understandable to
and expressible by the system user as well as the system developer.
This is particularly desirable in connection with certain ldquointimaterdquo
relationships, such as being the same as or being a part of.
The conceptual basis for such a methodology, as conventionally approached,
seems flavored with notions arising in the systems arena to an inappropriate
degree. To counter this tendency it is useful to turn to a discipline
not hitherto much involved in technology, namely analytic philosophy.},
added-at = {2007-05-04T05:48:10.000+0200},
author = {Ashenhurst, Robert L.},
biburl = {https://www.bibsonomy.org/bibtex/29cf985e187899444fc9a940a9de34a6a/p_ansell},
description = {Context-aware business processes},
doi = {10.1007/BF00729802},
interhash = {91b631f5723d90831c95a0401d5a2d53},
intrahash = {9cf985e187899444fc9a940a9de34a6a},
journal = {Minds and Machines},
keywords = {- Information actions analytic and attributes categories data development entities epistemology events information kinds knowledge model modeling object-oriented ontology paradigm philosophy reality relational relationships semantic statements systems the views vs.},
month = {October},
number = 3,
owner = {peter},
pages = {287--394},
timestamp = {2007-05-04T05:48:10.000+0200},
title = {Ontological Aspects of Information Modeling},
url = {http://www.springerlink.com.ezp01.library.qut.edu.au/openurl.asp?genre=article&id=doi:10.1007/BF00729802},
volume = 6,
year = 1996
}