Earlier work in the philosophical foundations of information modeling identified four key concepts in which philosophical groundwork must be further developed. This chapter reviews that earlier work and expands on one key area—the Problem of Universals—which is at the very heart of information modeling.
For several decades now, articles have been appearing periodically, in the Information Systems research literature, criticizing the field for (1) a lack of theory, (2) no core set of concepts, and (3) no accepted paradigm. All of these criticisms point to a lack of philosophical grounding which would help provide a common basis from which researchers could work, a collection of central problems, and a collection of agreed upon methods for advancing knowledge in the field. It is difficult to tell exactly when this self flagellating critical self-examination first began. But a reasonable point at which to establish the basis of this critical self-examination would be an article by Peter Keen at the 1st International Conference on Information Systems which begins with the observation that “At present, MIS research is a theme rather than a substantive field.” (Keen, 1980, pg. 9) Keen goes on to criticize MIS research for a lack of a cumulative tradition and other factors that are key requirements for a scientific discipline.
This idea was elaborated upon several years later by Culnan who cited Keen’s remarks, and embarked upon an analysis of the Information Systems research literature looking for common themes and potentially competing paradigms. Culnan points out that “As a field matures, new theories are proposed and compete until paradigms emerge.” (Culnan, 1986, pg. 156) Or, at least, that is the way it is supposed to work. Culnan concludes that the Information Systems research literature consists of “research themes rather than paradigms or even well defined subfields” (Culnan, 1986, pg. 167) but excuses the field for its shortcomings with the observation that “MIS is very much a young academic field.” (pg. 167)
Culnan’s approach was empirical in that she analyzed existing journal articles. Weber, on the other hand, took a theoretical approach sketching out what we should be looking for from a conceptual perspective. Weber observes “If a science progresses only when it has a paradigm, it behooves the members of a field to seek paradigms and to articulate paradigms via normal science as their primary research activities.” (Weber 1987, pg. 9) He also remarked, with regard to referent disciplines, that “the IS discipline must develop its own paradigm rather than rely on other disciplines’ paradigms if it is to survive in the long run as a distinct discipline.” (Weber, 1987, pg. 4)
Orlikowski and Iacono coalesced the concepts of paradigm, cumulative tradition, and core concepts in the “IT Artifact” which may be one of the most important concepts in all of information systems theory and research.
We believe that the lack of theories about IT artifacts, the ways in which they emerge and evolve over time, and how they become independent with socio-economic contexts and practices, are key unresolved issues for our field and ones that will become even more problematic in these dynamic and innovative times. (Orlikowski and Iacono, 2001, Pg. 133.)
This is an important observation and certainly sharpens the focus of the investigation, but doesn’t answer the question - What is the “IT Artifact”? Weber (1987) attempts to answer that question. He cites E.F. Codd’s (Codd, 1970) paper as one of the most cited articles in Information Systems and one that could be considered a candidate as a paradigm suggesting that the IT Artifact is some kind of a data model. In a later editorial in MIS Quarterly, Weber points out, “After a long period of discernment, we found we could identify only one class of phenomena, for which theories sourced from other disciplines seemed deficient— namely, phenomena associated with building conceptual models and designing databases.” (Weber, 2003, pg viii) So maybe the IT Artifact has something to do with information models or information modeling. This is possible since data modeling and information modeling are, perhaps, the only intellectual developments that are unique to information systems. Yet the theories in these areas are sketchy at best.