The proliferation of discipline-specific metadata schemes contributes to artificial barriers that can impede interdisciplinary and transdisciplinary research. The authors considered this problem by examining the domains, objectives, and architectures of nine metadata schemes used to document scientific data in the physical, life, and social sciences. They used a mixed-methods content analysis and Greenberg's (2005) metadata objectives, principles, domains, and architectural layout (MODAL) framework, and derived 22 metadata-related goals from textual content describing each metadata scheme. Relationships are identified between the domains (e.g., scientific discipline and type of data) and the categories of scheme objectives. For each strong correlation (>0.6), a Fisher's exact test for nonparametric data was used to determine significance (p < .05).Significant relationships were found between the domains and objectives of the schemes. Schemes describing observational data are more likely to have "scheme harmonization" (compatibility and interoperability with related schemes) as an objective; schemes with the objective "abstraction" (a conceptual model exists separate from the technical implementation) also have the objective "sufficiency" (the scheme defines a minimal amount of information to meet the needs of the community); and schemes with the objective "data publication" do not have the objective "element refinement." The analysis indicates that many metadata-driven goals expressed by communities are independent of scientific discipline or the type of data, although they are constrained by historical community practices and workflows as well as the technological environment at the time of scheme creation. The analysis reveals 11 fundamental metadata goals for metadata documenting scientific data in support of sharing research data across disciplines and domains. The authors report these results and highlight the need for more metadata-related research, particularly in the context of recent funding agency policy changes.

Digital data repositories ought to support immediate operational needs and long-term project goals. This paper presents the Dryad repository's metadata best practice balancing of these two needs. The paper reviews background work exploring the meaning of science, characterizing data, and highlighting data curation metadata challenges. The Dryad repository is introduced, and the initiative's metadata best practice and underlying rationales are described. Dryad's metadata approach includes two prongs: one addressing the long-term goal to align with the Semantic Web via a metadata application profile; and another addressing the immediate need to make content available in DSpace via an extensible markup language (XML) schema. The conclusion summarizes limitations and advantages of the two prongs underlying Dryad's metadata effort.

Background and Aims Research indicates that high consumers of alcohol exhibit attentional bias (AB) towards alcohol‐related cues, suggestive of a cognitive mechanism that might drive substance seeking. Many tasks that measure AB (e.g. visual probe, addiction Stroop), however, are limited by their reliance on non‐appetitive control cues, the serial presentation of stimuli and their poor internal reliability. The current study employed a visual conjunction search (VCS) task capable of presenting multiple alcoholic and non‐alcoholic appetitive cues simultaneously to assess whether social drinkers attend selectively to alcoholic stimuli. To assess the construct validity of this task, we examined whether alcohol consumption and related problems, subjective craving and drinking motives predict alcohol‐specific AB. Design and setting A VCS task was performed in a laboratory setting, which required participants to detect the presence of appetitive alcoholic (wine, beer) and non‐alcoholic (cola, lemonade) targets within arrays of matching and non‐matching distractors. Participants Data from 99 participants were assessed [meanage = 20.77, standard deviation (SD) = 2.98; 64 (65%) females], with 81.8% meeting the threshold for harmful alcohol consumption (meanAUDIT = 12.89, SD = 5.79). Measurements Self‐reports of alcohol consumption and related problems [Alcohol Use Disorders Identification Test (AUDIT)], subjective craving (Alcohol Craving Questionnaire Short Form) and drinking motives (Drinking Motives Questionnaire Short Form) were obtained, and the VCS task measured response times for the correct detection of alcoholic and non‐alcoholic targets. Findings Participants were significantly quicker to detect alcoholic relative to non‐alcoholic appetitive targets (P < 0.001, dz = 0.41), which was predicted positively by AUDIT scores (P = 0.013, R2 = 0.06%). The VCS task achieved excellent reliability (α > 0.79), superior to other paradigms. Conclusions The visual conjunction search task appears to be a highly reliable method for assessing alcohol‐related attentional bias, and shows that heavy social drinkers prioritize alcoholic cues in their immediate environment.

Editor's Summary HIVE (Helping Interdisciplinary Vocabulary Engineering) is an effort to automatically generate metadata for content, drawing descriptor terms from multiple vocabularies encoded as Simple Knowledge Organization Systems (SKOS). The effort is a response to the challenges of interoperability, cost and usability of multiple terminology sets often needed to adequately describe digital resources. By offering access to more than one vocabulary with useful descriptors for a broad domain, HIVE enables aggregating the best terms to describe resources and automatically apply metadata. HIVE offers knowledge management value for multidisciplinary digital collections while demonstrating the expanded potential use of SKOS. The initiative is headed by the Metadata Research Center at the University of North Carolina's School of Information and Library Science working with several institutional partners. Conferences and workshops are scheduled to inform interested developers and users, who are invited to try out, contribute to and evaluate the system.

The sensitivity of terrestrial isopods to changes in both temperature and moisture make them suitable models for examining possible responses of arthropod macro-decomposers to predicted climate change. Effects of changes in both temperature and relative humidity on aggregation, growth and survivorship of species of isopods contrasting in their morphological and physiological adaptations to moisture stress have been investigated in laboratory microcosms.All three traits were more sensitive to a reduction in relative humidity of 20–25% than they were to an increase in temperature of 5–6 °C. These results suggest that predicted changes in climate in south east England may reduce the extent to which soil animals stimulate microbial activity and hence carbon dioxide (CO2) emissions from soils in the future. This may help to mitigate the potential for a positive feedback between increased CO2 emissions from soils, and increased greenhouse effects causing an increase in soil temperatures.