Motivated by the importance of infectious disease informatics (IDI) and the challenges to IDI system development and data sharing, we design and implement BioPortal, a Web-based IDI system that integrates cross-jurisdictional data to support information sharing, analysis, and visualization in public health. In this paper, we discuss general challenges in IDI, describe BioPortal's architecture and functionalities, and highlight encouraging evaluation results obtained from a controlled experiment that focused on analysis accuracy, task performance efficiency, user information satisfaction, system usability, usefulness, and ease of use.

Objective: Standardized surveillance syndromes do not exist but would facilitate sharing data among surveillance systems and comparing the accuracy of existing systems. The objective of this study was to create reference syndrome definitions from a consensus of investigators who currently have or are building syndromic surveillance systems. Design: Clinical condition–syndrome pairs were catalogued for 10 surveillance systems across the United States and the representatives of these systems were brought together for a workshop to discuss consensus syndrome definitions. Results: Consensus syndrome definitions were generated for the four syndromes monitored by the majority of the 10 participating surveillance systems: Respiratory, gastrointestinal, constitutional, and influenza-like illness (ILI). An important element in coming to consensus quickly was the development of a sensitive and specific definition for respiratory and gastrointestinal syndromes. After the workshop, the definitions were refined and supplemented with keywords and regular expressions, the keywords were mapped to standard vocabularies, and a web ontology language (OWL) ontology was created. Limitations: The consensus definitions have not yet been validated through implementation. Conclusion: The consensus definitions provide an explicit description of the current state-of-the-art syndromes used in automated surveillance, which can subsequently be systematically evaluated against real data to improve the definitions. The method for creating consensus definitions could be applied to other domains that have diverse existing definitions.

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This paper previews the imminent flood of scientific data expected from the next generation of experiments, simulations, sensors and satellites. In order to be exploited by search engines and data mining software tools, such experimental data needs to be annotated with relevant metadata giving information as to provenance, content, conditions and so on. The need to automate the process of going from raw data to information to knowledge is briefly discussed. The paper argues the case for creating new types of digital libraries for scientific data with the same sort of management services as conventional digital libraries in addition to other data-specific services. Some likely implications of both the Open Archives Initiative and e-Science data for the future role for university libraries are briefly mentioned. A substantial subset of this e-Science data needs to archived and curated for long-term preservation. Some of the issues involved in the digital preservation of both scientific data and of the programs needed to interpret the data are reviewed. Finally, the implications of this wealth of e-Science data for the Grid middleware infrastructure are highlighted.

China, Russia, and India are playing an increasingly important role in global nanotechnology research and development (R&D). This paper comparatively inspects the paper and patent publications by these three countries in the Thomson Science Citation Index Expanded (SCI) database and United States Patent and Trademark Office (USPTO) database (1976–2007). Bibliographic, content map, and citation network analyses are used to evaluate country productivity, dominant research topics, and knowledge diffusion patterns. Significant and consistent growth in nanotechnology papers are noted in the three countries. Between 2000 and 2007, the average annual growth rate was 31.43% in China, 11.88% in Russia, and 33.51% in India. During the same time, the growth patterns were less consistent in patent publications: the corresponding average rates are 31.13, 10.41, and 5.96%. The three countries’ paper impact measured by the average number of citations has been lower than the world average. However, from 2000 to 2007, it experienced rapid increases of about 12.8 times in China, 8 times in India, and 1.6 times in Russia. The Chinese Academy of Sciences (CAS), the Russian Academy of Sciences (RAS), and the Indian Institutes of Technology (IIT) were the most productive institutions in paper publication, with 12,334, 6,773, and 1,831 papers, respectively. The three countries emphasized some common research topics such as “Quantum dots,” “Carbon nanotubes,” “Atomic force microscopy,” and “Scanning electron microscopy,” while Russia and India reported more research on nano-devices as compared with China. CAS, RAS, and IIT played key roles in the respective domestic knowledge diffusion.