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Abstract

It is vital for library and information science to understand the subject indexing process thoroughly. However, document analysis, the first and most important step in indexing, has not received sufficient attention. As this is an exceptionally hard problem, we still do not dispose of a sound indexing theory. Therefore we have difficulties in teaching indexing and in explaining why a given subject representation is "better" than another. Technological advancements have not helped to close this fundamental gap. To proceed, we should ask the right questions instead. Several types of indexer inconsistencies can be explained as acceptable, yet different conceptualizations which resulting of the variety of groups dealing with a problem from their respective viewpoints. Multiple indexed documents are regarded as the normal case. Intersubjectively replicable indexing results are often questionable or do not constitute interesting cases of indexing at all. In the context of my ongoing dissertation in which I intend to develop an enhanced indexing theory by investigating improvements within a social sciences domain, this paper explains user-oriented selective depth analysis and why I chose that configuration. Strongly influenced by Mai's dissertation, I also communicate my first insights concerning current indexing theories. I agree that I cannot ignore epistemological stances and philosophical issues in language and meaning related to indexing and accept the openness of the interpretive nature of the indexing process. Although I present arguments against the employment of an indexing language as well, it is still indispensable in situations which demand easier access and control by devices. Despite the enormous difficulties the user-oriented and selective depth analysis poses, I argue that it is both feasible and useful if one achieves careful guidance of the possible interpretations. There is some hope because the number of useful interpretations is limited: Every summary is tailored to a purpose, audience and situation. Domain, discourse and social practice entail additional constraints. A pluralistic method mix that focusses on ecologically valid, holistic contexts and employs qualitative methods is recommended. Domain analysis urgently has to be made more practical and applicable. Only then we will be able to investigate empirically domains in order to identify their structures shaped by the corresponding discourse communities. We plan to represent the recognized problem structures and indexing questions of relevance to a small domain in formal, ontological computer models -- if we can find such stable knowledge structures. This would allow us to tailor dynamically summaries for user communities. For practical purposes we suggest to assume a less demanding position than Hjorland's "totality of the epistemological potential". It is sufficent that we identify and represent iteratively the information needs of today's user groups in interactive knowledge-based systems. The best way to formalize such knowledge gained about discourse communities is however unknown. Indexers should stay in direct contact with the community they serve or be part of it to ensure agreement with their viewpoints. Checklist/request-oriented indexing could be very helpful but it remains to be demonstrated how well it will be applicable in the social sciences. A frame-based representation or at least a sophisticated grouping of terms could help to express relational knowledge structures. There remains much work to do since in practice no one has shown yet how such an improved indexing system would work and if the indexing results were really "better".