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This paper reports the analysis of search logs from a commercial image provider over a onemonth period and discusses the results in relation to previous findings. The study analyzes image searches, image queries composing the search, user search modification strategies, results returned, and user browsing of results. Unique term searches are less frequent than earlier research has shown, with more descriptive and thematic queries occurring. Boolean searching, while heavily employed, appears to be ineffective and leads to query modifications. While there was a large amount of query modification (55.8% of queries), the tactics overall do not appear to be carefully thought out but rather seem to be largely experimental. Given the willingness to modify queries but the inability to do so, much more support for query modification could be offered.

This article presents exploratory research evaluating a conceptual structure for the description of visual content of images. The structure, which was developed from empirical research in several fields (e.g., Computer Science, Psychology, Information Studies, etc.), classifies visual attributes into a "Pyramid" containing four syntactic levels (type/technique, global distribution, local structure, composition), and six semantic levels (generic, specific, and abstract levels of both object and scene, respectively). Various experiments are presented, which address the Pyramid's ability to achieve several tasks:(1) classification of terms describing image attributes generated in a formal and an informal description task, (2) classification of terms that result from a structured approach to indexing, and (3) guidance in the indexing process. Several descriptions, generated by naive users and indexers, are used in experiments that include two image collections: a random Web sample, and a set of news images. To test descriptions generated in a structured setting, an Image Indexing Template (developed independently over several years of this project by one of the authors) was also used. The experiments performed suggest that the Pyramid is conceptually robust (i.e., can accommodate a full range of attributes), and that it can be used to organize visual content for retrieval, to guide the indexing process, and to classify descriptions obtained manually and automatically.

The potential impact of the Internet on the public's demand for the services and resources of public libraries is an issue of critical importance. The research reported in this article provides baseline data concerning the evolving relationship between the public's use of the library and its use of the Internet. The authors developed a consumer model of the American adult market for information services and resources, segmented by use (or nonuse) of the public library and by access (or lack of access) to, and use (or nonuse) of, the Internet. A national Random Digit Dialing telephone survey collected data to estimate the size of each of six market segments, and to describe their usage choices between the public library and the Internet. The analyses presented in this article provide estimates of the size and demographics of each of the market segments; describe why people are currently using the public library and the Internet; identify the decision criteria people use in their choices of which provider to use; identify areas in which libraries and the Internet appear to be competing and areas in which they appear to be complementary; and identify reasons why people choose not to use the public library and/or the Internet. The data suggest that some differentiation between the library and the Internet is taking place, which may very well have an impact on consumer choices between the two. Longitudinal research is necessary to fully reveal trends in these usage choices, which have implications for all types of libraries in planning and policy development.

The rapid accumulation of genome annotations, as well as their widespread reuse in clinical and scientific practice, poses new challenges to management of the quality of scientific data. This study contributes towards better understanding of scientists' perceptions of and priorities for data quality and data quality assurance skills needed in genome annotation.This study was guided by a previously developed general framework for assessment of data quality and by a taxonomy of data-quality (DQ) skills, and intended to define context-sensitive models of criteria for data quality and skills for genome annotation. Analysis of the results revealed that genomics scientists recognize specific sets of criteria for quality in the genome-annotation context. Seventeen data quality dimensions were reduced to 5-factor constructs, and 17 relevant skills were grouped into 4-factor constructs. The constructs defined by this study advance the understanding of data quality relationships and are an important contribution to data and information quality research. In addition, the resulting models can serve as valuable resources to genome data curators and administrators for developing data-curation policies and designing DQassurance strategies, processes, procedures, and infrastructure. The study's findings may also inform educators in developing data quality assurance curricula and training courses.