1,134 research outputs found
Advanced Cyberinfrastructure for Science, Engineering, and Public Policy
Progress in many domains increasingly benefits from our ability to view the
systems through a computational lens, i.e., using computational abstractions of
the domains; and our ability to acquire, share, integrate, and analyze
disparate types of data. These advances would not be possible without the
advanced data and computational cyberinfrastructure and tools for data capture,
integration, analysis, modeling, and simulation. However, despite, and perhaps
because of, advances in "big data" technologies for data acquisition,
management and analytics, the other largely manual, and labor-intensive aspects
of the decision making process, e.g., formulating questions, designing studies,
organizing, curating, connecting, correlating and integrating crossdomain data,
drawing inferences and interpreting results, have become the rate-limiting
steps to progress. Advancing the capability and capacity for evidence-based
improvements in science, engineering, and public policy requires support for
(1) computational abstractions of the relevant domains coupled with
computational methods and tools for their analysis, synthesis, simulation,
visualization, sharing, and integration; (2) cognitive tools that leverage and
extend the reach of human intellect, and partner with humans on all aspects of
the activity; (3) nimble and trustworthy data cyber-infrastructures that
connect, manage a variety of instruments, multiple interrelated data types and
associated metadata, data representations, processes, protocols and workflows;
and enforce applicable security and data access and use policies; and (4)
organizational and social structures and processes for collaborative and
coordinated activity across disciplinary and institutional boundaries.Comment: A Computing Community Consortium (CCC) white paper, 9 pages. arXiv
admin note: text overlap with arXiv:1604.0200
Libraries and the management of research data
A discussion of the role of university libraries in the management of digital research data outputs. Reviews some of the recent history of progress in this area from a UK perspective, with reference to international developments
Towards a cyberinfrastructure for enhanced scientific
A new generation of information and communication infrastructures, including advanced Internet computing and Grid technologies, promises to enable more direct and shared access to more widely distributed computing resources than was previously possible. Scientific and technological collaboration, consequently, is more and more coming to be seen as critically dependent upon effective access to, and sharing of digital research data, and of the information tools that facilitate data being structured for efficient storage, search, retrieval, display and higher level analysis. A recent (February 2003) report to the U.S. NSF Directorate of Computer and Information System Engineering urged that funding be provided for a major enhancement of computer and network technologies, thereby creating a cyberinfrastructure whose facilities would support and transform the conduct of scientific and engineering research. The articulation of this programmatic vision reflects a widely shared expectation that solving the technical engineering problems associated with the advanced hardware and software systems of the cyberinfrastructure will yield revolutionary payoffs by empowering individual researchers and increasing the scale, scope and flexibility of collective research enterprises. The argument of this paper, however, is that engineering breakthroughs alone will not be enough to achieve such an outcome; success in realizing the cyberinfrastructure’s potential, if it is achieved, will more likely to be the resultant of a nexus of interrelated social, legal and technical transformations. The socio-institutional elements of a new infrastructure supporting collaboration – that is to say, its supposedly “softer” parts -- are every bit as complicated as the hardware and computer software, and, indeed, may prove much harder to devise and implement. The roots of this latter class of challenges facing “e-Science” will be seen to lie in the micro- and meso-level incentive structures created by the existing legal and administrative regimes. Although a number of these same conditions and circumstances appear to be equally significant obstacles to commercial provision of Grid services in interorganizational contexts, the domain of publicly supported scientific collaboration is held to be the more hospitable environment in which to experiment with a variety of new approaches to solving these problems. The paper concludes by proposing several “solution modalities,” including some that also could be made applicable for fields of information-intensive collaboration in business and finance that must regularly transcends organizational boundaries.
Towards a cyberinfrastructure for enhanced scientific
Scientific and technological collaboration is more and more coming to be seen as critically dependent upon effective access to, and sharing of digital research data, and of the information tools that facilitate data being structured for efficient storage, search, retrieval, display and higher level analysis. A February 2003 report to the U.S. NSF Directorate of Computer and Information System Engineering urged that funding be provided for a major enhancement of computer and network technologies, thereby creating a cyberinfrastructure whose facilities would support and transform the conduct of scientific and engineering research. The argument of this paper is that engineering breakthroughs alone will not be enough to achieve such an outcome; success in realizing the cyberinfrastructure’s potential, if it is achieved, will more likely to be the resultant of a nexus of interrelated social, legal and technical transformations. The socio-institutional elements of a new infrastructure supporting collaboration that is to say, its supposedly “softer” parts -- are every bit as complicated as the hardware and computer software, and, indeed, may prove much harder to devise and implement. The roots of this latter class of challenges facing “e- Science” will be seen to lie in the micro- and meso-level incentive structures created by the existing legal and administrative regimes. Although a number of these same conditions and circumstances appear to be equally significant obstacles to commercial provision of Grid services in interorganizational contexts, the domain of publicly supported scientific collaboration is held to be the more hospitable environment in which to experiment with a variety of new approaches to solving these problems. The paper concludes by proposing several “solution modalities,” including some that also could be made applicable for fields of information-intensive collaboration in business and finance that must regularly transcends organizational boundaries.
Trusted CI Experiences in Cybersecurity and Service to Open Science
This article describes experiences and lessons learned from the Trusted CI
project, funded by the US National Science Foundation to serve the community as
the NSF Cybersecurity Center of Excellence. Trusted CI is an effort to address
cybersecurity for the open science community through a single organization that
provides leadership, training, consulting, and knowledge to that community. The
article describes the experiences and lessons learned of Trusted CI regarding
both cybersecurity for open science and managing the process of providing
centralized services to a broad and diverse community.Comment: 8 pages, PEARC '19: Practice and Experience in Advanced Research
Computing, July 28-August 1, 2019, Chicago, IL, US
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
The advanced cyberinfrastructure research and education facilitators virtual residency: Toward a national cyberinfrastructure workforce
An Advanced Cyberinfrastructure Research and Education Facilitator (ACI-REF) works directly with researchers to advance the computing- and data-intensive aspects of their research, helping them to make effective use of Cyberinfrastructure (CI). The University of Oklahoma (OU) is leading a national "virtual residency" program to prepare ACI-REFs to provide CI facilitation to the diverse populations of Science, Technology, Engineering and Mathematics (STEM) researchers that they serve. Until recently, CI Facilitators have had no education or training program; the Virtual Residency program addresses this national need by providing: (1) training, specifically (a) summer workshops and (b) third party training opportunity alerts; (2) a community of CI Facilitators, enabled by (c) a biweekly conference call and (d) a mailing list
From Artifacts to Aggregations: Modeling Scientific Life Cycles on the Semantic Web
In the process of scientific research, many information objects are
generated, all of which may remain valuable indefinitely. However, artifacts
such as instrument data and associated calibration information may have little
value in isolation; their meaning is derived from their relationships to each
other. Individual artifacts are best represented as components of a life cycle
that is specific to a scientific research domain or project. Current cataloging
practices do not describe objects at a sufficient level of granularity nor do
they offer the globally persistent identifiers necessary to discover and manage
scholarly products with World Wide Web standards. The Open Archives
Initiative's Object Reuse and Exchange data model (OAI-ORE) meets these
requirements. We demonstrate a conceptual implementation of OAI-ORE to
represent the scientific life cycles of embedded networked sensor applications
in seismology and environmental sciences. By establishing relationships between
publications, data, and contextual research information, we illustrate how to
obtain a richer and more realistic view of scientific practices. That view can
facilitate new forms of scientific research and learning. Our analysis is
framed by studies of scientific practices in a large, multi-disciplinary,
multi-university science and engineering research center, the Center for
Embedded Networked Sensing (CENS).Comment: 28 pages. To appear in the Journal of the American Society for
Information Science and Technology (JASIST
DataONE: Facilitating eScience through Collaboration
Objective: To introduce DataONE, a multi-institutional, multinational, and interdisciplinary collaboration that is developing the cyberinfrastructure and organizational structure to support the full information lifecycle of biological, ecological, and environmental data and tools to be used by researchers, educators, and the public at large.
Setting: The dynamic world of data intensive science at the point it interacts with the grand challenges facing environmental sciences.
Methods: Briefly discuss science’s “fourth paradigm,” then introduce how DataONE is being developed to answer the challenges presented by this new environment. Sociocultural perspectives are the primary focus of the discussion.
Results: DataONE is highly collaborative. This is a result of its cyberinfrastructure architecture, its interdisciplinary nature, and its organizational diversity. The organizational structure of an agile management team, diverse leadership team, and productive working groups provides for a successful collaborative environment where substantial contributions to the DataONE mission have been made by a large number of people.
Conclusions: Librarians and information science researchers are key partners in the development of DataONE. These roles are likely to grow as more scientists engage data at all points of the data lifecycle
- …