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Topical metadata are simultaneously hailed as building blocks of the semantic Web and derogated as spam. The significance of the metadata controversy depends on the technological appropriateness of adding them to Web pages. A survey of Web technology suggests that Web pages are both transient and volatile: poor hosts of topical metadata. A more supportive environment exists in the closed Web. The vast majority of Web pages, however, exist in the open Web, an environment that challenges the application of legacy information retrieval concepts and methods.

Presents the Semantic Distance Model (SDM) of Relevance Assessment, a cognitive model of the relationship between semantic distance and relevance assessment. Discusses premises of the model such as the subjective nature of information and the metaphor of semantic distance. Empirical results illustrate the effects of semantic distance and semantic direction. Presents relevance auras, a combination of vertical and horizontal relevance assessments. (Author/AEF)

This test of the Strategy of Unlimited Aliasing, an indexing method that places terms from several indexers for the same information object in one index, utilized bibliographic records from the ERIC, LISA (Library and Information Science Abstracts), and ISA (Information Science Abstracts) databases. The test did not support the indexing method. (nine references) (KRN)

Describes a study in which comprehensive bibliographies and related literatures were compared by clustering indices, Bradford multipliers, bibliograph slopes, and reference scattering coefficients. It is concluded that the clustering index has the potential for being a useful tool in comparing the intensity of clustering of different literatures. (23 references) (CLB)

Four methods were used to forecast monthly circulation totals in 15 midwestern academic libraries: dummy time-series regression, lagged time-series regression, simple average (straight-line forecasting), monthly average (naive forecasting). In tests of forecasting accuracy, dummy regression method and monthly mean method exhibited smallest average error for 1 and 6 month forecasts. (EJS)

Reports on database management system (dbms) applications designed by library school students for university community at University of Iowa. Three dbms design issues are examined: synthesis of relations, analysis of relations (normalization procedure), and data dictionary usage. Database planning prior to automation using data dictionary approach is recommended. (21 references) (EJS)

Analysis of current models describing citer motivations identified seven most significant motivations for authors: currency scale, negative credit, operational information, persuasiveness, positive credit, reader alert, social consensus. Motivational background for more than 900 citational acts of 26 authors at University of Iowa were gathered and analyzed. (43 references) (EJS)

Circulation time-series data from 50 midwest academic libraries were used to test 110 variants of 8 smoothing forecasting methods. Data and methodologies and illustrations of two recommended methods--the single exponential smoothing method and Brown's one-parameter linear exponential smoothing method--are given. Eight references are cited. (EJS)

Proposes a solution to the problem of loading repetitive bibliographic information in a microcomputer-based relational database management system. The alternative design described is based on a representational redundancy design and normalization theory. (12 references) (Author/CLB)

Assesses bibliographic databases as part of visionary text systems such as hypertext and scholars' workstations. Downloading is discussed in terms of the capability to search records and to maintain unique bibliographic descriptions, and relational database management systems, file managers, and text databases are reviewed as possible hosts for bibliographic records. (17 references) (Author/MES)

Analyzes journals contributing to the literature on superconductivity from 1973 to 1987. Reveals that the literature has tripled in absolute size and has grown in intensity. Identifies core journals and reveals a communication pattern dominated by two journals, "Physical Review Letters" and "Physical Review B." Critiques problems of bibliometric methodology. (SR)

Introduces the special issue of the "Journal of American Society for Information Science and Technology," (JASIST) whose intent is to provide a forum for assessment of "where we have been and where we are going." Highlights themes that emerged from nine selected articles: Community and Trust; Communication and Community; Identify of the Information Science Community; and Theoretical Development in the Information Science Community. (AEF)

Describes a citation analysis that examined the 28 best articles published from 1969-1996 in JASIS ("Journal of the American Society for Information Science")(ASIS 1999 Handbook and Directory, p.25). Results highlight single-authored works that are twice as long (16.21 pages) as the average article (8.93 pages), are cited and self-cited more often, and focus on information retrieval and online searching. (Author/LRW)

Predicts that in the 21st century, scholars will abandon print in favor of more immediate and multidimensional venues. Suggests that JASISWeb, a Web-based version of the "Journal of the American Society for Information Science" should become the more appropriate postmodern information science "journal." (AEF)

Group of 20 scholars attributed 29.3 percent of 437 references they had cited to one of seven motives, while describing motives for majority (70.7 percent) of references as combinations. Clustering of citer motives showed three groupings: (1) persuasiveness, positive credit, currency, social consensus; (2) negative credit; (3) reader alert, operational information. (12 references) (EJS)

This paper develops object-oriented data analysis (OODA) statistical methods that are novel and complementary to existing methods of analysis of human brain scan connectomes, defined as graphs representing brain anatomical or functional connectivity. OODA is an emerging field where classical statistical approaches (e.g., hypothesis testing, regression, estimation, and confidence intervals) are applied to data objects such as graphs or functions. By analyzing data objects directly we avoid loss of information that occurs when data objects are transformed into numerical summary statistics. By providing statistical tools that analyze sets of connectomes without loss of information, new insights into neurology and medicine may be achieved. In this paper we derive the formula for statistical model fitting, regression, and mixture models; test their performance in simulation experiments; and apply them to connectomes from fMRI brain scans collected during a serial reaction time task study. Software for fitting graphical object-oriented data analysis is provided. [ABSTRACT FROM AUTHOR]