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Proteomics, the study of the protein complement of a biological system, is generating increasing quantities of data from rapidly developing technologies employed in a variety of different experimental workflows. Experimental processes, e.g. for comparative 2D gel studies or LC-MS/MS analyses of complex protein mixtures, involve a number of steps: from experimental design, through wet and dry lab operations, to publication of data in repositories and finally to data annotation and maintenance. The presence of inaccuracies throughout the processing pipeline, however, results in data that can be untrustworthy, thus offsetting the benefits of high-throughput technology. While researchers and practitioners are generally aware of some of the information quality issues associated with public proteomics data, there are few accepted criteria and guidelines for dealing with them. In this article, we highlight factors that impact on the quality of experimental data and review current approaches to information quality management in proteomics. Data quality issues are considered throughout the lifecycle of a proteomics experiment, from experiment design and technique selection, through data analysis, to archiving and sharing.

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Data-intensive e-science applications often rely on third-party data found in public repositories, whose quality is largely unknown. Although scientists are aware that this uncertainty may lead to incorrect scientific conclusions, in the absence of a quantitative characterization of data quality properties they find it difficult to formulate precise data acceptability criteria. We present an Information Quality management workbench, called Qurator, that supports data experts in the specification of personal quality models, and lets them derive effective criteria for data acceptability. The demo of our working prototype will illustrate our approach on a real e-science workflow for a bioinformatics application.

The effects of tunnel blast excavation on the lining structures of adjacent tunnels are comprehensively studied for the Xinling highway tunnel project. First, the LS-DYNA software is applied to obtain the characteristics of vibration velocities and dynamic stresses at different positions of the tunnel liner. The results indicate that the maximum peak particle velocity (PPV) is located on the haunch of the lining facing the blasting source and that the PPV and peak tensile stress decrease with the increase in the surrounding rock grade. Second, a site test on blasting vibration is conducted to verify the simulation results. By using regression analysis of the measured vibration data, the calculation method of maximum charge per delay for optimizing blasting excavation under different surrounding rock grades is obtained. Finally, based on the statistical relationship between crack alteration and PPV on the lining before and after blasting, the safety thresholds of PPV for different portions of the tunnel are determined. The recommended safety threshold of PPV is 10 cm/s for intact lining and for B-grade and V-grade linings of the surrounding rock tunnel. However, if the lining crack grade falls between 1A and B, then the recommended safety thresholds of PPV for the III-grade and IV-grade surrounding rock tunnel are 5 cm/s and 6 cm/s, respectively. The threshold PPV proposed in this study has been successfully applied to restrict blast-induced damage during new tunnel excavation of the Xinling tunnel project.

Southern rice black-streaked dwarf virus (SRBSDV), which causes severe disease symptoms in rice (Oriza sativa L.) has been emerging in the last decade throughout northern Vietnam, southern Japan and southern, central and eastern China. Here we attempt to quantify the prevalence of SRBSDV in the Honghe Hani rice terraces system (HHRTS)—a Chinese 1300-year-old traditional rice production system. We first confirm that genetically diverse rice varieties are still being cultivated in the HHRTS and categorize these varieties into three main genetic clusters, including the modern hybrid varieties group (MH), the Hongyang improved modern variety group (HY) and the traditional indica landraces group (TIL). We also show over a 2-year period that SRBSDV remains prevalent in the HHRTS (20.1% prevalence) and that both the TIL (17.9% prevalence) and the MH varieties (5.1% prevalence) were less affected by SRBSDV than were the HY varieties (30.2% prevalence). Collectively we suggest that SRBSDV isolates are freely moving within the HHRTS and that TIL, HY and MH rice genetic clusters are not being preferentially infected by particular SRBSDV lineages. Given that SRBSDV can cause 30–50% rice yield losses, our study emphasizes both the need to better monitor the disease in the HHRTS, and the need to start considering ways to reduce its burden on rice production.

SUMMARYIn this paper we outline a framework for managing information quality (IQ) in an e-Science context. In contrast to previous approaches that take a very abstract view of IQ properties, we allow scientists to define the quality characteristics that are of importance to them in their particular domain. For example, 'accuracy' may be defined in terms of the conformance of experimental data to a particular standard. User-scientists specify their IQ preferences against a formal ontology, so that the definitions are machinemanipulable, allowing the environment to classify and organize domain-specific quality characteristics within an overall quality management framework. As an illustration of our approach, we present an example Web service that computes IQ annotations for experiment datasets in transcriptomics. Copyright

1. Identifying the macro-scale patterns and the underlying mechanisms of species richness are key aspects of biodiversity-related research. In China, previous studies on the mechanisms underlying insect richness have primarily focused on the current ecological conditions. Therefore, the impact of historical climate change on these mechanisms is less well understood. 2. Here, we use members of the Delphacidae family to evaluate the relative impact of the current environmental conditions and that of the Last Glacial Maximum on total species richness and endemism. Total species richness and endemic species richness were summed in 1 ∘ × 1 ∘ grid cells that the insects occupied. Generalised linear models, simultaneous autoregressive models, and random forest models were used to assess the effects of different environmental factors on total species richness and endemism. 3. The two patterns of species richness are jointly regulated by the current environment and the Last Glacial Maximum, but their key determinants differ. Winter coldness and the temperature annual range strongly affected the total species richness, but temperature variation during the Last Glacial Maximum also played an important role in the development of species richness. The distribution of endemic species was most strongly affected by the Last Glacial Maximum temperature change. 4. The studies confirm that historical climate change contributes to patterns of insect species richness, particularly patterns of endemism. Considering that China was mildly affected by the last glacial period, we propose that the incorporation of historical climate data into such studies will provide a better understanding of the underlying mechanisms.