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Most documentation systems allocate a variable number of descriptors to their documents. From a consideration of indexing as a stochastic process it is suggested that the distribution of indexing depth in such a system might represent samples of a (truncated) mixed Poisson process. Examination of five different systems showed that indexing depth does appear to be distributed in this manner, since a reasonable fit to negative binomial distributions can be made statistically. Factors in the art of indexing which influence the distribution are discussed. As a first approximation the distribution of indexing depth, i, of a system, or of any subset of descriptors in it, is simple Poisson, p(i) = e−m(mi/i!), where m is the average depth of indexing. The results contradict previous reports that a log‐normal distribution of indexing depth is to be expected.

This paper seeks to examine image retrieval within two different contexts: a monolingual context where the language of the query is the same as the indexing language and a multilingual context where the language of the query is different from the indexing language. The study also aims to compare two different approaches for the indexing of ordinary images representing common objects: traditional image indexing with the use of a controlled vocabulary and free image indexing using uncontrolled vocabulary.

This research uses three data collection methods. An analysis of the indexing terms was employed in order to examine the multiplicity of term types assigned to images. A simulation of the retrieval process involving a set of 30 images was performed with 60 participants. The quantification of the retrieval performance of each indexing approach was based on the usability measures, that is, effectiveness, efficiency and satisfaction of the user. Finally, a questionnaire was used to gather information on searcher satisfaction during and after the retrieval process.

The results of this research are twofold. The analysis of indexing terms associated with all the 3,950 images provides a comprehensive description of the characteristics of the four non‐combined indexing forms used for the study. Also, the retrieval simulation results offers information about the relative performance of the six indexing forms (combined and non‐combined) in terms of their effectiveness, efficiency (temporal and human) and the image searcher's satisfaction.

The findings of the study suggest that, in the near future, the information systems could benefit from allowing an increased coexistence of controlled vocabularies and uncontrolled vocabularies, resulting from collaborative image tagging, for example, and giving the users the possibility to dynamically participate in the image‐indexing process, in a more user‐centred way.

To present an ongoing research effort based on previous industrial experience in the content management field.

The project began with lessons learned while working in the IT industry. A model was then developed based on these lessons for managing content and enabling searching for content over the internet.

The author has used the proposed model both before and after joining academia a few years ago. The model works fine with some tune‐up from one case to another.

As this is ongoing research, the model will be subject to enhancements based on further lessons learned in the future.

The proposed model has been used by the author on several projects and has led to good results in most cases.

The model itself and the approach followed to integrate content into enterprise systems are both novel.

This chapter aims to discuss the issues associated with social indexing as a solution to the challenges of current information organization systems by investigating the quality and efficacy of social indexing.

The chapter focuses on the study which compared indexing similarity between two professional groups and also compared social tagging and professional indexing. The study employed the method of the modified vector-based Indexing Consistency Density (ICD) with three different similarity measures: cosine similarity, dot product similarity, and Euclidean distance metric.

The investigation of social indexing in comparison of professional indexing demonstrates that social tags are more accurate descriptions of resources and reflection of more current terminology than controlled vocabulary. Through the characteristics of social tagging discussed in this chapter, we have a clearer understanding of the extent to which social indexing can be used to replace and improve upon professional indexing.

As investment in professionally developed web directories diminishes, it becomes even more critical to understand the characteristics of social tagging and to obtain benefit from it. In future research, the examination of subjective tags needs to be conducted. A survey or user study on tagging behavior also would help to extend understanding of social indexing practices.

The purpose of this research is to provide a framework in which new data quality dimensions are defined. The new dimensions provide new metrics for the assessment of lecture video indexing. As lecture video indexing involves various steps, the proposed framework containing new dimensions, introduces new integrated approach for evaluating an indexing method or algorithm from the beginning to the end.

The emphasis in this study is on the fifth step of design science research methodology (DSRM), known as evaluation. That is, the methods that are developed in the field of lecture video indexing as an artifact, should be evaluated from different aspects. In this research, nine dimensions of data quality including accuracy, value-added, relevancy, completeness, appropriate amount of data, concise, consistency, interpretability and accessibility have been redefined based on previous studies and nominal group technique (NGT).

The proposed dimensions are implemented as new metrics to evaluate a newly developed lecture video indexing algorithm, LVTIA and numerical values have been obtained based on the proposed definitions for each dimension. In addition, the new dimensions are compared with each other in terms of various aspects. The comparison shows that each dimension that is used for assessing lecture video indexing, is able to reflect a different weakness or strength of an indexing method or algorithm.

Despite development of different methods for indexing lecture videos, the issue of data quality and its various dimensions have not been studied. Since data with low quality can affect the process of scientific lecture video indexing, the issue of data quality in this process requires special attention.

A rule‐governed derivation of an indexing phrase from the text of a document is, in Wittgenstein's sense, a practice, rather than a mental operation explained by reference to internally represented and tacitly known rules. Some mentalistic proposals for theory in information retrieval are criticised in light of Wittgenstein's remarks on following a rule. The conception of rules as practices shifts the theoretical significance of the social role of retrieval practices from the margins to the centre of enquiry into foundations of information retrieval. The abstracted notion of a cognitive act of ‘information processing’ deflects attention from fruitful directions of research.

This paper seeks to report a project to investigate the degree of inter‐indexer consistency in the assignment of controlled vocabulary topical subject index terms to identical graphical images by different indexers at the National Library of Wales (NLW).

An experimental quantitative methodology was devised to investigate inter‐indexer consistency. Additionally, the project investigated the relationship, if any, between indexing exhaustivity and consistency, and the relationship, if any, between indexing consistency/exhaustivity and broad category of graphic format.

Inter‐indexer consistency in the assignment of topical subject index terms to graphic materials at the NLW was found to be generally low and highly variable. Inter‐indexer consistency fell within the range 10.8 per cent to 48.0 per cent. Indexing exhaustivity varied substantially from indexer to indexer, with a mean assignment of 3.8 terms by each indexer to each image, falling within the range 2.5 to 4.7 terms. The broad category of graphic format, whether photographic or non‐photographic, was found to have little influence on either inter‐indexer consistency or indexing exhaustivity. Indexing exhaustivity and inter‐indexer consistency exhibited a tendency toward a direct, positive relationship. The findings are necessarily limited as this is a small‐scale study within a single institution.

Previous consistency studies have almost exclusively investigated the indexing of print materials, with very little research published for non‐print media. With the literature also rich in discussion of the added complexities of subjectively representing the intellectual content of visual media, this study attempts to enrich existing knowledge on indexing consistency for graphic materials and to address a noticeable gap in information theory.

User‐created metadata, often referred to as folksonomy or social classification, has received a considerable amount of attention in the digital library world. Social tagging is perceived as a tool for enhancing description of digital objects and providing a venue for user input and greater user engagement. This article seeks to examine the pros and cons of user‐generated metadata in the context of digital image collections and compares it to professionally created metadata schema and controlled vocabulary tools.

The article provides an overview of challenges to concept‐based image indexing. It analyzes the characteristics of social classification and compares images described by users to a set of images indexed in a digital collection.

The article finds that user‐generated metadata vary in the level of description, accuracy, and consistency and do not provide a solution to the challenges of image indexing. On the other hand, they reflects user's language and can lead toward user‐centered indexing and greater user engagement.

Social tagging can be implemented as a supplement to professionally created metadata records to provide an opportunity for users to comment on images.

The article introduces the idea of user‐centered image indexing in digital collections.