Increasingly, scientific breakthroughs will be powered by advanced computing capabilities that help researchers manipulate and explore massive datasets. The speed at which any given scientific discipline advances will depend on how well its researchers collaborate with one another, and with technologists, in areas of eScience such as databases, workflow management, visualization, and cloud computing technologies. In The Fourth Paradigm: Data-Intensive Scientific Discovery, the collection of essays expands on the vision of pioneering computer scientist Jim Gray for a new, fourth paradigm of discovery based on data-intensive science and offers insights into how it can be fully realized.

Mission: • To inspire new activities and facilitate knowledge exchange between Nordic/Baltic • stakeholder, and to increase the international visibility of Nordic and Baltic policies and initiatives • To stress the importance of Open Access in the Nordic and Baltic countries and to describe both theoretical and best-practice models for financing, rights management and other fundamental issues. • To disseminate to both a Nordic/Baltic and an international readership information about successful initiatives and other activities in the Nordic and Baltic countries.

SciencePipes is an environment in which students, educators, citizens, resource managers, and scientists can create and share analyses and visualizations of biodiversity data. It is built to support inquiry-based learning, allowing analysis results and visualizations to be dynamically incorporated into web sites (e.g. blogs) for dissemination and consumption beyond SciencePipes.org itself. For more information: * further introduction * presentations * status of the site * NSDL article about SciencePipes.org Alpha functionality demos: * uploading and running a Kepler workflow * editing a pipe in the SciencePipes.org authoring environment SciencePipes is a project of the Cornell Lab of Ornithology Information Science Program and is funded by the National Science Digital Library.

The benefits of community participation or collaboration should outweigh the costs to support a rational decision to pursue such routes. Lions usually prefer to hunt as a group as the shared food from group kills offers a better return and lower risk than hunting alone; in a similar manner organisations may also choose to collaborate to have greater success in acquiring new resources or income. The current convergence of a number of factors appears to be driving up the R&D collaboration benefit/cost ratio. The drivers include: 1. Scientific research is becoming more complex and multi-disciplinary, requiring researchers to move more away from “working in the expert’s box”. 2. Our work, economy and society are becoming more knowledge-oriented. (I define knowledge here as including understanding gained from experience and involves individual and collective knowledge in addition to explicit knowledge such as intellectual property (IP).) 3. Business models in the chemistry and pharmaceutical industry that worked fine historically, e.g., manufacturing products based predominantly on patents related to chemistry, appear to be increasingly lacking. 4. The goals of translational and personalized medicine have stronger requirements for networked and collaborative approaches over discipline and time than the historically relatively linear drug discovery and development process. Integrated services offer greater future value creation than stand-alone products. 5. Patient Safety has become an issue of growing concern requiring new more integrative approaches to data, knowledge and disciplines. 6. Computational Science continues to grow in importance, fueling overlaps and interactions between scientific disciplines including that of computer science. 7. The maturing of the Internet-based World Wide Web including enhanced usability, services, social software and the semantic web, provide new community and collaboration resource opportunities. 8. Challenging problems we face as a

Sharing data is good. But sharing your own data? That can get complicated. As two research communities who held meetings in May on the issue report their proposals to promote data sharing in biology, a special issue of Nature examines the cultural and technical hurdles that can get in the way of good intentions.