Virtual communities are centred upon computer-mediated communication, with participants interacting to provide specific knowledge to each other that enables them to perform common functions, to learn from each other and to build upon their collective knowledge. Without the existence of rich knowledge bases, computermediated virtual communities are of limited value. Therefore, the significance of member-generated knowledge cannot be over-emphasized. In this paper, our goal is to examine the roles of identity and organizational citizenship behaviour in facilitating knowledge transfer in computer-mediated communication contexts such as virtual communities. Our findings support the assertion that self-presentation and organizational citizenship behaviour are crucial determinants of important community outcomes. We concluded that self-presentation could be a key variable for contributing knowledge in online communities. This study has important implications for academic researchers and practitioners who seek to understand why community members share their knowledge with strangers in online communities.

The value of full text for expanding information retrieval was examined. Two full-text databases were used: Textpresso for neuroscience and ScienceDirect. Queries representing different categories were used to search different text fields (titles, abstracts, full text and, where possible, keywords). Searching the full-text field relative to the commonly used abstracts field increases retrievals by one or more orders of magnitude, depending on the categories selected. For phenomena-type categories (e.g. blood flow, thermodynamic equilibrium, etc.), retrievals are enhanced by about an order of magnitude. For infrastructure-type categories (e.g. equipment types, sponsors, suppliers, databases, etc.), retrievals are enhanced by well over an order of magnitude, and sometimes multiple orders of magnitude. Use of combination terms along with proximity specification capability is a very powerful feature for retrieving relevant records from full-text searching, and can be useful for applications like literature-related discovery.

The IL-HUMASS survey on information literacy has been designed, based on and aimed to be applied to a population of students, teachers and librarians holding various degrees in social sciences and humanities at Spanish and Portuguese universities. The case-study method, experts’ opinions, and a literature review were used to prepare an initial version that was refined through student focus groups, interviews with librarians, and academics’ reports. A final version contained 26 items grouped into four categories (information search, assessment, processing and communication/dissemination) and three self-reporting dimensions (motivation, self-efficacy and favourite source of learning). The self-reporting nature of the IL-HUMASS survey involves a self-assessment approach that has until now been proposed rarely and only in a limited way. This will enable a better understanding of user groups through a mixed analysis including two quantitative dimensions (motivation and self-efficacy) and one qualitative dimension (the preferred source of learning).

Collaboration patterns among scientists are becoming more and more complicated. Even sophisticated methods for taking the number of co-authors into account do not solve all problems related to the calculation of citation measures such as the h-index. In this article we introduce role-based h-indices and in particular the major contribution h-index, denoted as h-maj, which takes only those articles into account in which the scientist plays a major or core role. As an example we provide major contribution indices for scientists in the health sciences in China. Differences between the h-index and h-maj are shown for data based on the Web of Science (WoS), and separately, based on the China National Knowledge Infrastructure (CNKI) database. It is suggested to use the major contribution h-index as a supplementary index, especially in those fields where multiple ‘first authors’ and/or corresponding authors are common.

Managing their knowledge assets is an imperative issue for most organizations in pursuit of competitive advantage in the knowledge-based economy. Previous researchers have proposed a number of valuable taxonomies for classifying an organization’s knowledge assets. However, once knowledge assets are classified by such taxonomies as a particular type, they do not change type over time. Arguably, however, business contexts are swiftly changing, and knowledge assets may have to be constantly adapted to play new roles, and so a taxonomy capable of reflecting the changing relations between knowledge assets and environmental conditions is needed. This article proposes such a taxonomy which utilizes durability and profitability as dimensions. This taxonomy allows knowledge assets to change type in the light of the new condition. Additionally, it has the characteristics of demonstrating the alignment of assets with organizational strategies, and of being widely applicable in the for-profit sector.

Websites that provide content creation and sharing features have become quite popular recently. These sites allow users to categorize and browse content using ‘tags’ or free-text keyword topics. Since users contribute and tag social media content across a variety of social web platforms, creating new knowledge from distributed tag data has become a matter of performing various tasks, including publishing, aggregating, integrating, and republishing tag data. However, there are a number of issues in relation to data sharing and interoperability when processing tag data across heterogeneous tagging platforms. In this paper we introduce a semantic tag model that aims to explicitly offer the necessary structure, semantics and relationships between tags. This approach provides an improved opportunity for representing tag data in the form of reusable constructs at a semantic level. We also demonstrate a prototype that consumes and makes use of shared tag metadata across heterogeneous sources.

The performance of spatial queries depends mainly on the underlying index structure used to handle them. R-tree, a well-known spatial index structure, suffers largely from high overlap and high coverage resulting mainly from splitting the overflowed nodes. Assigning the remaining entries to the underflow node in order to meet the R-tree minimum fill constraint (Remaining Entries problem) may induce high overlap or high coverage. This is done without considering the geometric features of the remaining entries and this may cause a very non-optimized expansion of that particular node. This paper presents a solution to the above problem. The proposed solution to this problem distributes rectangles as follows: (1) assign m entries to the first node, which are nearest to the first seed; (2) assign other m entries to the second node, which are nearest to the second seed; (3) assign the remaining entries one by one to the nearest seed. Several experiments on real data, as well as synthetic data, show that the proposed splitting algorithm outperforms the efficient version of the original R-tree in terms of query performance.

Publication in quality journals has become a major indicator of research performance in UK universities. This paper investigates the notion of ‘quality journal’ and finds dizzying circularity in its definitions. Actually, what a quality journal is does not really matter: agreement that there are such things matters very much indeed. As so often happens with indicators of performance, the indicator has become the target. So, the challenge is to publish in quality journals, and the challenge rewards gamesmanship. Vested interests have become particularly skilful at the game, and at exercising the winners’ prerogative of changing the rules. All but forgotten in the desperation to win the game is publication as a means of communicating research findings for the public benefit. The paper examines the situation in management studies, but the problem is much more widespread. It concludes that laughter is both the appropriate reaction to such farce, and also, perhaps, the stimulus to reform.