Categorisation of Information Systems Journals

Background

The issue of categorising Information Systems Journals has been raised by a number of users of the Index.

In 2002, there was some discussion of this, which is recorded here.

Current Research

This discussion has given rise to a research project to develop a categorisation system for use in the Index and elsewhere. The results of this ongoing research is reported in the following papers.

Lamp JW and Milton SK (2003) "An Exploratory Study of Information Systems Subject Indexing" Proceedings of the Fourteenth Australasian Conference on Information Systems (ACIS2003), Perth Australia, Edith Cowan University

The motivation for detailed study of information systems research subject indexing schemes is explained, along with an analysis of two indexing schemes proposed for use in the area. A number of reference disciplines are examined for their ability to provide insights and analysis approaches. Click for PDF file

Lamp JW and Milton SK (2004) "The Reality of Information Systems Research", in Hart, D. and Gregor, S. (eds) Information Systems Foundations: Constructing and Criticising, Canberra Australia, ANU E-Press, 25-34

The examination of a practical issue with a web site has lead directly to the consideration of the need for, and impact of, an approach based on fundamental theories of “what is” to examine what information systems research is and the relations of the component areas of endeavour. This paper presents an examination of the use of the philosophical field of ontologies, and specifically the use of the ontological approaches upon which to base categories of information systems research activities. This theoretical analysis is intended to be used as the basis from which to develop a methodology to undertake the development of the categorial scheme. Click for PDF file

Lamp, J. W. and Milton, S. K. (2007) "Indexing Research: An Approach to Grounding Ingarden's Ontological Framework", in Hart, D. and Gregor, S. (eds) Information Systems Foundations: Theory, Representation and Reality, Canberra Australia, ANU E-Press, 115-132

Attempts to produce an adequate and long-lived subject indexing of information systems research have failed. In this paper we seek to address this by proposing an approach by which the terms expressed in research literature, such as that in information systems, can be systematically and meaningfully categorised. The approach is significant in that it draws upon rigorous and philosophically compatible bodies of work in two areas. Firstly, from work addressing the nature, existence, and categorisation of literary expression found in research papers (Roman Ingarden’s ontological analysis of the scientific work of art). Secondly, from qualitative research methods addressing how meaningful categories can be analysed from text and related to each other (Grounded Theory). The resulting approach has potential to be applied in many scientific disciplines beyond information systems and form the intellectual core of an information tool in e-Research. Click for PDF file

Lamp, J. W. and Milton, S. K. (2007) "Grounded Theory As Foundations For Methods In Applied Ontology", Proceedings of QualIT, Victoria University of Wellington

Research into domain specific ontologies is difficult to treat empirically. This is because it is difficult to ground domain ontology while simultaneously being true to its guiding philosophy or theory. Further, ontology generation is often introspective and reflective or relies on experts for ontology generation. Even those relying on expert generation lack rigour and tend to be more ad-hoc. We ask how Grounded Theory can be used to generate domain specific ontologies where appropriate high level theory and suitable textual data sources are available. We are undertaking generation of a domain ontology for the discipline of information systems by applying the Grounded Theory method. Specifically we are using Roman Ingarden’s theory of scientific works to seed a coding family and adapting the method to ask relevant questions when analysing rich textual data. We have found that a guiding ontological theory, such as Ingarden’s, can be used to seed a coding family giving rise to a viable method for generating ontologies for research. This is significant because Grounded Theory may be one of the key methods for generating ontologies where substantial uniform quality text is available to the ontologist. We also present our partial analysis of information systems research. Click for PDF file

Lamp, J. W. and S. K. Milton (2008) "Generating an ontology from scientific works: initial results", Proceedings of the Nineteenth Australasian Conference on Information Systems, University of Canterbury, New Zealand

Attempts to produce adequate and long-lived subject indexes of information systems and computer science research have failed. In this paper we report preliminary results of an approach by which the terms expressed in research literature, such as that in information systems, can be systematically and meaningfully categorised. The approach is based on Roman Ingarden's ontological theory of the written scholarly work: its nature, existence, and categorisation, and builds on Grounded Theory: a rigorous grounded qualitative research method addressing how meaningful categories can be analysed from text and related to each other. We have found that the key guiding unit of analysis operationalising Ingarden's approach through Grounded Theory is the "reported research activity" and that the process is possible although labour intensive. On the basis of using the approach, we propose simple steps to improve the quality of keywords in reported research. Click for PDF file


This publication is edited by John Lamp who can be reached at John.Lamp@deakin.edu.au. This page was last updated on 9 August 2013. Individual entries were updated on the date shown against the entry. Although I will attempt to keep this information accurate, I can not guarantee the accuracy of the information provided. Copyright and Privacy information

This product includes GeoLite data created by MaxMind, available from http://www.maxmind.com.