Designing Institutional Infrastructure for E-Science

A new generation of information and communication infrastructures, including advanced Internet computing and Grid technologies, promises more direct and shared access to more widely distributed computing resources than was previously possible. Scientific and technological collaboration, consequently, is more and more dependent upon access to, and sharing of digital research data. Thus, the U.S. NSF Directorate committed in 2005 to a major research funding initiative, “Cyberinfrastructure Vision for 21st Century Discovery”. These investments are aimed at enhancement of computer and network technologies, and the training of researchers. Animated by much the same view, the UK e-Science Core Programme has preceded the NSF effort in funding development of an array of open standard middleware platforms, intended to support Grid enabled science and engineering research. This proceeds from the sceptical view that engineering breakthroughs alone will not be enough to achieve the outcomes envisaged. Success in realizing the potential of e-Science—through the collaborative activities supported by the "cyberinfrastructure," if it is to be achieved, will be the result of a nexus of interrelated social, legal, and technical transformations.e-science, cyberinfrastructure, information sharing, research

Complex adaptive systems theory applied to virtual scientific collaborations: The case of DataONE

This study is the exploration of the emergence of DataONE, a multidisciplinary, multinational, and multi-institutional virtual scientific collaboration to develop a cyberinfrastructure for earth sciences data, from the complex adaptive systems perspective. Data is generated through conducting 15 semi-structured interviews, observing three 3-day meetings, and 51 online surveys. The main contribution of this study is the development of a complexity framework and its application to a project such as DataONE. The findings reveal that DataONE behaves like a complex adaptive system: various individuals and institutions interacting, adapting, and coevolving to achieve their own and common goals; during the process new structures, relationships, and products emerge that harmonize with DataONE’s goals. DataONE is quite resilient to threats and adaptive to its environment, which are important strengths. The strength comes from its diversified structure and balanced management style that allows for frequent interaction among members. The study also offers insights to PI(s), managers, and funding institutions on how to treat complex systems. Additional results regarding multidisiplinarity, library and information sciences, and communication studies are presented as well

The Federal Big Data Research and Development Strategic Plan

This document was developed through the contributions of the NITRD Big Data SSG members and staff. A special thanks and appreciation to the core team of editors, writers, and reviewers: Lida Beninson (NSF), Quincy Brown (NSF), Elizabeth Burrows (NSF), Dana Hunter (NSF), Craig Jolley (USAID), Meredith Lee (DHS), Nishal Mohan (NSF), Chloe Poston (NSF), Renata Rawlings-Goss (NSF), Carly Robinson (DOE Science), Alejandro Suarez (NSF), Martin Wiener (NSF), and Fen Zhao (NSF). A national Big Data1 innovation ecosystem is essential to enabling knowledge discovery from and confident action informed by the vast resource of new and diverse datasets that are rapidly becoming available in nearly every aspect of life. Big Data has the potential to radically improve the lives of all Americans. It is now possible to combine disparate, dynamic, and distributed datasets and enable everything from predicting the future behavior of complex systems to precise medical treatments, smart energy usage, and focused educational curricula. Government agency research and public-private partnerships, together with the education and training of future data scientists, will enable applications that directly benefit society and the economy of the Nation. To derive the greatest benefits from the many, rich sources of Big Data, the Administration announced a “Big Data Research and Development Initiative” on March 29, 2012.2 Dr. John P. Holdren, Assistant to the President for Science and Technology and Director of the Office of Science and Technology Policy, stated that the initiative “promises to transform our ability to use Big Data for scientific discovery, environmental and biomedical research, education, and national security.” The Federal Big Data Research and Development Strategic Plan (Plan) builds upon the promise and excitement of the myriad applications enabled by Big Data with the objective of guiding Federal agencies as they develop and expand their individual mission-driven programs and investments related to Big Data. The Plan is based on inputs from a series of Federal agency and public activities, and a shared vision: We envision a Big Data innovation ecosystem in which the ability to analyze, extract information from, and make decisions and discoveries based upon large, diverse, and real-time datasets enables new capabilities for Federal agencies and the Nation at large; accelerates the process of scientific discovery and innovation; leads to new fields of research and new areas of inquiry that would otherwise be impossible; educates the next generation of 21st century scientists and engineers; and promotes new economic growth. The Plan is built around seven strategies that represent key areas of importance for Big Data research and development (R&D). Priorities listed within each strategy highlight the intended outcomes that can be addressed by the missions and research funding of NITRD agencies. These include advancing human understanding in all branches of science, medicine, and security; ensuring the Nation’s continued leadership in research and development; and enhancing the Nation’s ability to address pressing societal and environmental issues facing the Nation and the world through research and development

The Federal Big Data Research and Development Strategic Plan

This document was developed through the contributions of the NITRD Big Data SSG members and staff. A special thanks and appreciation to the core team of editors, writers, and reviewers: Lida Beninson (NSF), Quincy Brown (NSF), Elizabeth Burrows (NSF), Dana Hunter (NSF), Craig Jolley (USAID), Meredith Lee (DHS), Nishal Mohan (NSF), Chloe Poston (NSF), Renata Rawlings-Goss (NSF), Carly Robinson (DOE Science), Alejandro Suarez (NSF), Martin Wiener (NSF), and Fen Zhao (NSF). A national Big Data1 innovation ecosystem is essential to enabling knowledge discovery from and confident action informed by the vast resource of new and diverse datasets that are rapidly becoming available in nearly every aspect of life. Big Data has the potential to radically improve the lives of all Americans. It is now possible to combine disparate, dynamic, and distributed datasets and enable everything from predicting the future behavior of complex systems to precise medical treatments, smart energy usage, and focused educational curricula. Government agency research and public-private partnerships, together with the education and training of future data scientists, will enable applications that directly benefit society and the economy of the Nation. To derive the greatest benefits from the many, rich sources of Big Data, the Administration announced a “Big Data Research and Development Initiative” on March 29, 2012.2 Dr. John P. Holdren, Assistant to the President for Science and Technology and Director of the Office of Science and Technology Policy, stated that the initiative “promises to transform our ability to use Big Data for scientific discovery, environmental and biomedical research, education, and national security.” The Federal Big Data Research and Development Strategic Plan (Plan) builds upon the promise and excitement of the myriad applications enabled by Big Data with the objective of guiding Federal agencies as they develop and expand their individual mission-driven programs and investments related to Big Data. The Plan is based on inputs from a series of Federal agency and public activities, and a shared vision: We envision a Big Data innovation ecosystem in which the ability to analyze, extract information from, and make decisions and discoveries based upon large, diverse, and real-time datasets enables new capabilities for Federal agencies and the Nation at large; accelerates the process of scientific discovery and innovation; leads to new fields of research and new areas of inquiry that would otherwise be impossible; educates the next generation of 21st century scientists and engineers; and promotes new economic growth. The Plan is built around seven strategies that represent key areas of importance for Big Data research and development (R&D). Priorities listed within each strategy highlight the intended outcomes that can be addressed by the missions and research funding of NITRD agencies. These include advancing human understanding in all branches of science, medicine, and security; ensuring the Nation’s continued leadership in research and development; and enhancing the Nation’s ability to address pressing societal and environmental issues facing the Nation and the world through research and development

Preparing for a Northwest Passage: A Workshop on the Role of New England in Navigating the New Arctic

Preparing for a Northwest Passage: A Workshop on the Role of New England in Navigating the New Arctic (March 25 - 27, 2018 -- The University of New Hampshire) paired two of NSF\u27s 10 Big Ideas: Navigating the New Arctic and Growing Convergence Research at NSF. During this event, participants assessed economic, environmental, and social impacts of Arctic change on New England and established convergence research initiatives to prepare for, adapt to, and respond to these effects. Shipping routes through an ice-free Northwest Passage in combination with modifications to ocean circulation and regional climate patterns linked to Arctic ice melt will affect trade, fisheries, tourism, coastal ecology, air and water quality, animal migration, and demographics not only in the Arctic but also in lower latitude coastal regions such as New England. With profound changes on the horizon, this is a critical opportunity for New England to prepare for uncertain yet inevitable economic and environmental impacts of Arctic change

TOWARDS INSTITUTIONAL INFRASTRUCTURES FOR E-SCIENCE: The Scope of the Challenge

The three-fold purpose of this Report to the Joint Information Systems Committee (JISC) of the Research Councils (UK) is to: • articulate the nature and significance of the non-technological issues that will bear on the practical effectiveness of the hardware and software infrastructures that are being created to enable collaborations in e- Science; • characterise succinctly the fundamental sources of the organisational and institutional challenges that need to be addressed in regard to defining terms, rights and responsibilities of the collaborating parties, and to illustrate these by reference to the limited experience gained to date in regard to intellectual property, liability, privacy, and security and competition policy issues affecting scientific research organisations; and • propose approaches for arriving at institutional mechanisms whose establishment would generate workable, specific arrangements facilitating collaboration in e-Science; and, that also might serve to meet similar needs in other spheres such as e- Learning, e-Government, e-Commerce, e-Healthcare. In carrying out these tasks, the report examines developments in enhanced computer-mediated telecommunication networks and digital information technologies, and recent advances in technologies of collaboration. It considers the economic and legal aspects of scientific collaboration, with attention to interactions between formal contracting and 'private ordering' arrangements that rest upon research community norms. It offers definitions of e-Science, virtual laboratories, collaboratories, and develops a taxonomy of collaborative e-Science activities which is implemented to classify British e-Science pilot projects and contrast these with US collaboratory projects funded during the 1990s. The approach to facilitating inter-organizational participation in collaborative projects rests upon the development of a modular structure of contractual clauses that permit flexibility and experience-based learning.

Designing Institutional Infrastructures for e-Science

The opportunity exists today for unprecedented connections between scientists, information, data, computational services, and instruments through the Internet. A new generation of information and communication infrastructures, including advanced Internet computing and Grid technologies, is beginning to enable much greater direct and shared access to more widely distributed computing resources than previously has been possible.3 The term ‘e-Science’ usually is applied in reference to large scale science that, increasingly, is being carried out through distributed global collaborations enabled by the Internet.4 Such collaborative scientific enterprises typically require access to very extensive data collections, very large scale computing resources, and high performance visualisation of research data and analysis of results by the individual users. The potential for these advances in technology to support new levels of collaborative activity in scientific and engineering, and ultimately in other domains, is a major driving force behind the UK’s Core e-Science Programme.

Accelerating transition to virtual research organisation in social science (AVROSS) : final report

This report is the fourth deliverable of the AVROSS study (Accelerating Transition to Virtual Research Organisation in Social Science, AVROSS). The study aims were to identify the requirements and options for accelerating the transition from traditional research to virtual research organisations through e-Infrastructures. The reason for this focus is that it is clear that "soft" sciences have both much to gain and a key role to play in promoting e-Infrastructure uptake across the disciplines, but to date have not been the fastest adopters of advanced grid-based e-Infrastructure. Our recommendations to EU policy-makers can be expected to point the way to changing this situation, promoting e-Infrastructure in Europe in these disciplines, with clear requirements to developers and expected impact in several other disciplines with related requirements, such as e-Health