Towards a Life Sciences Code: Countering the Threats from Biological Weapons

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Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

Challenging the Computational Metaphor: Implications for How We Think

This paper explores the role of the traditional computational metaphor in our thinking as computer scientists, its influence on epistemological styles, and its implications for our understanding of cognition. It proposes to replace the conventional metaphor--a sequence of steps--with the notion of a community of interacting entities, and examines the ramifications of such a shift on these various ways in which we think

Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure

Big data research has attracted great attention in science, technology, industry and society. It is developing with the evolving scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies. However, its nature and fundamental challenge have not been recognized, and its own methodology has not been formed. This paper explores and answers the following questions: What is big data? What are the basic methods for representing, managing and analyzing big data? What is the relationship between big data and knowledge? Can we find a mapping from big data into knowledge space? What kind of infrastructure is required to support not only big data management and analysis but also knowledge discovery, sharing and management? What is the relationship between big data and science paradigm? What is the nature and fundamental challenge of big data computing? A multi-dimensional perspective is presented toward a methodology of big data computing.Comment: 59 page

Why social scientists should engage with natural scientists

It has become part of the mantra of contemporary science policy that the resolution of besetting problems calls for the active engagement of a wide range of sciences. The paper reviews some of the key challenges for those striving for a more impactful social science by engaging strategically with natural scientists. It argues that effective engagement depends upon overcoming basic assumptions that have structured past interactions: particularly, the casting of social science in an end-of-pipe role in relation to scientific and technological developments. These structurings arise from epistemological assumptions about the underlying permanence of the natural world and the role of science in uncovering its fundamental order and properties. While the impermanence of the social world has always put the social sciences on shakier foundations, twenty-first century concerns about the instability of the natural world pose different epistemological assumptions that summon a more equal, immediate and intense interaction between field and intervention oriented social and natural scientists. The paper examines a major research programme that has exemplified these alternative epistemological assumptions. Drawing on a survey of researchers and other sources it seeks to draw out the lessons for social/natural science cross-disciplinary engagement