How can groups elicit and aggregate the information held by their individual mem- bers? There are three possibilities. Groups might use the statistical mean of indi- vidual judgments; they might encourage deliberation; or they might use information markets. In both private and public institutions, deliberation is the standard way of proceeding; but for two reasons, deliberating groups often fail to make good deci- sions. First, the statements and acts of some group members convey relevant infor- mation, and that information often leads other people not to disclose what they know. Second, social pressures, imposed by some group members, often lead other group members to silence themselves because of fear of disapproval and associated harms. As a result, deliberation often produces a series of unfortunate results: the amplification of errors, hidden profiles, cascade effects, and group polarization. A variety of steps can be taken to ensure that deliberating groups obtain the informa- tion held by their members; restructuring private incentives, in a way that increases disclosure, is the place to start. Information markets have substantial advantages over group deliberation; such markets count among the most intriguing institutional innovations of the last quarter-century and should be used far more frequently than they now are. One advantage of information markets is that they tend to correct, rather than to amplify, the effects of individual errors. Another advantage is that they create powerful incentives to disclose, rather than to conceal, privately held information. Information markets thus provide the basis for a Hayekian critique of many current celebrations of political deliberation. They also provide a valuable heuristic for understanding how to make deliberation work better. These points bear on the discussion of normative issues, in which deliberation might also fail to improve group thinking, and in which identifiable reforms could produce better outcomes. Applications include the behavior of juries, multimember judicial panels, administrative agencies, and congressional committees; analogies, also involving information aggregation, include open source software, Internet “wikis,” and weblogs.

So far, we have mainly focused on the educational aspects of our approach, but the encouraging correlation between student hand-crafted and large-scale automatic annotations shows potential for pushing a step further. Could we envisage that student annotations be made public, contributing to a long-term international distributed annotation jamboree of large (meta)genomics datasets? This exciting possibility would undoubtedly be welcomed as a further incentive by participating students [6], and could even yield useful, if modest, scientific contributions. Final annotation quality control by instructors could be simplified by having several independent groups of students redundantly annotate the same sequences and by filtering for converging GO and taxonomy annotations before public release. Similar distributed annotation efforts have been applied to literature curation for DNA-binding data [7], and were just recently implemented in the Gene Wiki [8], WikiPathways [9], and WikiProteins [10] systems to encourage community annotation of genes, pathways, and proteins, respectively.

The new paradigms that are gaining momentum in web applications empower users with a new role: users are no longer limited to consuming or creating online content, they also provide the semantic scaffolding holding together such content, thus taking on an active role in shaping the architecture of online information. The collaborative character underlying many Web 2.0 applications puts them in the spotlight of complex systems science, since the problem of linking the low-level scale of user behavior with the high-level scale of global applicative goals is a typical problem tackled by the science of complexity: understanding how an observed emergent structure arises from the activity and interaction of many globally uncoordinated agents. The large number of users involved, together with the fact that their activity is occurring on the web, provide for the first time a unique opportunity to monitor the “microscopic” behavior of users and link it to the high-level features of applications (for example the global properties of a folksonomy) by using formal tools and concepts from the science of complexity.This research project is located at the interface of several fields, such as computer science, complex systems science, cognitive science, psycholinguistics and information architecture, and is likely to feed back into the design of better applications. The project will contribute to Semiotic Dynamics, a new field that studies how semiotic relations can originate, spread, and evolve over time in populations, by combining recent advances in linguistics and cognitive science with methodological and theoretical tools from complex systems and computer science.The TAGora project aims at exploiting the unique opportunities offered by the increasing popularity of computer-mediated social interaction in a variety of contexts. Such popularity, in fact, is making available large amounts of raw data from online semiotic systems (for example, collaborative tagging systems) and these data may become the foundantion of a true scientific investigation about the behavior of human agents on the Web and the dynamics of information in online communities.

Scientific publications are currently the only means to disseminate the details of biomedical experiments across the life sciences research community. With the ever increasing volume of scientific publications, life scientists and curators of life science knowledge bases are often confronted with the daunting task of sifting through hundreds of relevant publications to apprise themselves of the latest experimental techniques and research findings in their area of interest. The use of concise, structured annotations to describe the salient features of experiments would alleviate this difficulty. For this purpose, minimum information standards and controlled vocabularies for experiment representation are in development to be used by biologists to annotate their experiments. This paper presents the initial results from a methodology to manually annotate descriptions of experiments in scientific publications; and discusses the utility of these annotations in a bottom-up approach to creating an ontology of biomedical experiments.

draw pictures on your iphone

algorithm for inferring a tag hierarchy from social tagging data