eBird: engaging birders in science and conservation

How do you successfully engage an audience in a citizen-science project? The processes developed by eBird (www.ebird.org), a fast-growing web-based tool that now gathers millions of bird observations per month, offers a model.     

Obstetrics and gynecology: avoiding pregnancy in isotretinoin users

The Scientific Board of the California Medical Association presents the following inventory of items of progress in obstetrics and gynecology. Each item, in the judgment of a panel of knowledgeable physicians, has recently become reasonably firmly established, both as to scientific fact and important clinical significance. The items are presented in simple epitome and an authoritative reference, both to the item itself and to the subject as a whole, is generally given for those who may be unfamiliar with a particular item. The purpose is to assist busy practitioners, students, research workers, or scholars to stay abreast of these items of progress in obstetrics and gynecology that have recently achieved a substantial degree of authoritative acceptance, whether in their own field of special interest or another.The items of progress listed below were selected by the Advisory Panel to the Section on Obstetrics and Gynecology of the California Medical Association, and the summaries were prepared under its direction.     

Revealing and avoiding bias in semantic similarity scores for protein pairs

Background  

Semantic similarity scores for protein pairs are widely applied in functional genomic researches for finding functional clusters of proteins, predicting protein functions and protein-protein interactions, and for identifying putative disease genes. However, because some proteins, such as those related to diseases, tend to be studied more intensively, annotations are likely to be biased, which may affect applications based on semantic similarity measures. Thus, it is necessary to evaluate the effects of the bias on semantic similarity scores between proteins and then find a method to avoid them.     

Plans of mice and men: from bench science to science policy

The transition from bench science to science policy is not always a smooth one, and my journey stretched as far as the unemployment line to the hallowed halls of the U.S. Capitol. While earning my doctorate in microbiology, I found myself more interested in my political activities than my experiments. Thus, my science policy career aspirations were born from merging my love of science with my interest in policy and politics. After receiving my doctorate, I accepted the Henry Luce Scholarship, which allowed me to live in South Korea for 1 year and delve into the field of science policy research. This introduction into science policy occurred at the South Korean think tank called the Science and Technology Policy Institute (STEPI). During that year, I used textbooks, colleagues, and hands-on research projects as my educational introduction into the social science of science and technology decision-making. However, upon returning to the United States during one of the worst job markets in nearly 80 years, securing a position in science policy proved to be very difficult, and I was unemployed for five months. Ultimately, it took more than a year from the end of the Luce Scholarship to obtain my next science policy position with the American Society for Microbiology Congressional Fellowship. This fellowship gave me the opportunity to work as the science and public health advisor to U.S. Senator Harry Reid. While there were significant challenges during my transition from the laboratory to science policy, those challenges made me tougher, more appreciative, and more prepared to move from working at the bench to working in the field of science policy.     

Unconventional allies: interdisciplinary approaches to science policy and funding

Scientific research is an often misunderstood, undervalued and yet essential activity. Many nonscientists think that research is quick and easy, and that science is a compilation of established facts rather than rigorous conclusions based on available evidence. In addition, many nonscientists, and perhaps many scientists as well, forget that our social and financial investment is small relative to the massive and expensive problems that we all want scientific research to solve. Using biomedical research in the United States as an example, I will argue that countering this underinvestment in science will require broadening perspectives in the scientific community as well as coupling expanded individual advocacy and education efforts to an interdisciplinary advocacy approach. This approach is in many ways analogous to the unique solutions that emerge when scientists working in different disciplines leave their intellectual silos and work together.     

Progress bias versus status quo bias in the ethics of emerging science and technology

How should we handle ethical issues related to emerging science and technology in a rational way? This is a crucial issue in our time. On the one hand, there is great optimism with respect to technology. On the other, there is pessimism. As both perspectives are based on scarce evidence, they may appear speculative and irrational. Against the pessimistic perspective to emerging technology, it has been forcefully argued that there is a status quo bias (SQB) fuelling irrational attitudes to emergent science and technology and greatly hampering useful development and implementation. Therefore, this article starts by analysing the SQB using human enhancement as a case study. It reveals that SQB may not be as prominent in restricting the implementation of emergent technologies as claimed in the ethics literature, because SQB (a) is fuelled by other and weaker drivers than those addressed in the literature, (b) is at best one amongst many drivers of attitudes towards emergent science and technology, and (c) may not be a particularly prominent driver of irrational decision-making. While recognizing that SQB can be one driver behind pessimism, this article investigates other and counteracting forces that may be as strong as SQB. Progress bias is suggested as a generic term for the various drivers of unwarranted science and technology optimism. Based on this analysis, a test for avoiding or reducing this progress bias is proposed. Accordingly, we should recognize and avoid a broad range of biases in the assessment of emerging and existing science and technology in order to promote an open and transparent deliberation.     

Ecological indicators: Between the two fires of science and policy

This article approaches the concept of ecological indicators from a social science perspective. By applying theoretical concepts from policy analysis and social studies of science about knowledge utilization, problem structuring and the boundaries between science and policy to the issue of ecological indicators, we aim to contribute to our understanding not only of the development but more importantly of the actual use of ecological indicators in policy processes and the importance of political context.Our interest is in those ecological indicators that attempt to measure the ecological quality of ecosystems and that can be or are specifically developed to be used as instruments to evaluate the effects of policies on nature. We claim that these indicators, although they are highly dependent on scientific knowledge, cannot be solely science-based, due to the complexity of ecosystems and the normative aspects involved in assessing ecosystem quality. As a result, we situate ecological indicators in a fuzzy area between science and policy and between the production and the use of scientific knowledge.We will argue that ecological indicators can be expected to be used or rejected strategically, dependent on policy context. Furthermore we will argue that ecological indicators cannot be evaluated with traditional scientific quality criteria alone. The article concludes with some lessons for future indicator development one of them being the inclusion of stakeholder perspectives.     

VariVis: a visualisation toolkit for variation databases

Background  

With the completion of the Human Genome Project and recent advancements in mutation detection technologies, the volume of data available on genetic variations has risen considerably. These data are stored in online variation databases and provide important clues to the cause of diseases and potential side effects or resistance to drugs. However, the data presentation techniques employed by most of these databases make them difficult to use and understand.     

Cobweb: a Java applet for network exploration and visualisation

SUMMARY: Cobweb is a Java applet for real-time network visualization; its strength lies in enabling the interactive exploration of networks. Therefore, it allows new nodes to be interactively added to a network by querying a database on a server. The network constantly rearranges to provide the most meaningful topological view. AVAILABILITY: Cobweb is available under the GPLv3 and may be freely downloaded at http://bioinformatics.charite.de/cobweb.