On Roles of Models in Information Systems - Intentional Perspectives on Information Systems Engineering - page 29

through her REMORA methodology [ 26] and later through her work on intentional
modeling [ 27] . Central in much of the research in information systems modeling
has been to achieve a cross-disciplinary approach to business process design. As the
years have gone by the work on information systems modeling has become more
and more central to information technology as a whole.
We shall, however, not discuss these concepts further. We restrict the rest of our
discussion to a model ontology that is relevant to data and information.
4.1 Meaning
Digital data is always associated with meaning. Each data element represents some
relevant property of the world. This is necessary in order for the data to be use-
ful to the world outside of the computer, as well as for ensuring that systems
provide for meaningful communication among their components. What meaning
data convey depends on how the human receiver of data perceives the phenom-
ena that the data refer to. More often than not there is no explicit model of the
world for the human interpreter to lean to. In data systems the world models are
usually implicit in the software, and are hidden to the human interpreters of the
data.
Relationships between digital data and what the data refer to are seldom
explicitly stated, but are usually informally indicated by the names given to the
data elements, e.g., a data element named NAME-OF-PERSON is understood to
represent information about the name of a person, and a data structure named
EMPLOYEE usually represents information about persons who work in a com-
pany. The structure of a data base reflects the world view of the data base designer,
and is expressed through the names of the data structures. This works well within
each individual information system, but leads to difficulties when integrating several
data bases representing different world views. The need for explicitly express-
ing the meaning of data was encountered in the data base field when trying to
find approaches to data integration. The first approaches to data integration were
concerned with structural integration. Recent research is concerned with semantic
integration, see [ 36] for an overview of the research area.
Data on the World Wide Web are mostly natural language text. The meaning of
a text is intuitive in the same way as every text is intuitively understood through
the reader's association of terms and sentences to the reader's understanding of the
world. Linguistic theory applies to most of the data on the web. The objective of
having a “semantic web” is unreachable unless there is an explicit relation between
the linguistic constructs and the appropriate world model, that is, between the data
and the conceptual models of what the data stand for. So we are faced with the
same problems for providing meaning to data independent of whether the data is
structured or unstructured.
Information modeling is an approach to provide meaning to data. Information
models relate conceptual models and data models. Conceptual models provide struc-
ture to the relevant world views and provide means to relate different world views