Data Science, Data Visualization, and Digital Twins

Real-time, web-based, and interactive visualisations are proven to be outstanding methodologies and tools in numerous fields when knowledge in sophisticated data science and visualisation techniques is available. The rationale for this is because modern data science analytical approaches like machine/deep learning or artificial intelligence, as well as digital twinning, promise to give data insights, enable informed decision-making, and facilitate rich interactions among stakeholders.The benefits of data visualisation, data science, and digital twinning technologies motivate this book, which exhibits and presents numerous developed and advanced data science and visualisation approaches. Chapters cover such topics as deep learning techniques, web and dashboard-based visualisations during the COVID pandemic, 3D modelling of trees for mobile communications, digital twinning in the mining industry, data science libraries, and potential areas of future data science development

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

Collaborative Research in e-Science and Open Access to Information

This contribution examines various aspects of “openness” in research, and seeks to gauge the degree to which contemporary “e-science” practices are congruent with “open science.” Norms and practices of openness are vital for the work of modern scientific communities, but concerns about the growth of stronger technical and institutional restraints on access to research tools, data, and information recently have attracted notice—in part because of their implications for the effective utilization of advanced digital infrastructures and information technologies in research collaborations. Our discussion clarifies the conceptual differences between e-science and open science, and reports findings from a preliminary look at practices in U.K. e-science projects. Both parts serve to emphasize that it is unwarranted to presume that the development of e-science necessarily promotes global open science collaboration. Since there is evident need for further empirical research to establish where, when, and to what extent “openness” in scientific and engineering research may be expected to advance hand-in-hand, we outline a framework within which such a program of studies might be undertaken.e-Science, Open Science, Engineering Reserach

Will e-Science Be Open Science?

This contribution examines various aspects of “openness” in research, and seeks to gauge the degree to which contemporary “e-science” practices are congruent with “open science.” Norms and practices of openness are vital for the work of modern scientific communities, but concerns about the growth of stronger technical and institutional restraints on access to research tools, data, and information recently have attracted notice—in part because of their implications for the effective utilization of advanced digital infrastructures and information technologies in research collaborations. Our discussion clarifies the conceptual differences between e-science and open science, and reports findings from a preliminary look at practices in U.K. e-science projects. Both parts serve to emphasize that it is unwarranted to presume that the development of e-science necessarily promotes global open science collaboration. Since there is evident need for further empirical research to establish where, when, and to the extent “openness” and "e-ness" in scientific and engineering research may be expected to advance hand-in-hand, we outline a framework within which such a program of studies might be undertaken.e-Science, Open Science, Engineering Reserach

Understanding the Roots of Radicalisation on Twitter

In an increasingly digital world, identifying signs of online extremism sits at the top of the priority list for counter-extremist agencies. Researchers and governments are investing in the creation of advanced information technologies to identify and counter extremism through intelligent large-scale analysis of online data. However, to the best of our knowledge, these technologies are neither based on, nor do they take advantage of, the existing theories and studies of radicalisation. In this paper we propose a computational approach for detecting and predicting the radicalisation influence a user is exposed to, grounded on the notion of ’roots of radicalisation’ from social science models. This approach has been applied to analyse and compare the radicalisation level of 112 pro-ISIS vs.112 “general" Twitter users. Our results show the effectiveness of our proposed algorithms in detecting and predicting radicalisation influence, obtaining up to 0.9 F-1 measure for detection and between 0.7 and 0.8 precision for prediction. While this is an initial attempt towards the effective combination of social and computational perspectives, more work is needed to bridge these disciplines, and to build on their strengths to target the problem of online radicalisation

The Digital Technology Boomerang: New Intellectual Property Rights Threaten Global “Open Science”

There is a serious threat that ill-considered government support for expanding legal means of controlling access to information for the purpose of extracting private economic rents is resulting in the 'over- fencing of the public knowledge commons' in science and engineering. Such a new 'tragedy of the commons' would bring adverse long-run consequences for future welfare gains through technological progress, and re-distributional effects further disadvantaging the present economically less advanced countries of the world. Radical legal innovations in intellectual property protection that seriously jeopardize the effective conduct of open, collaborative science have been introduced by the little noticed European Database Directive of March 1996. This initiative forms an emblematic and substantively significant aspect of the broader set of transformations in intellectual property rights institutions that have been initiated in response to the economic ramifications of rapid progress in digital information technologies. The EC Directive poses numerous contentious issues in law and economics that will create ambiguities for business and non-profit activities in this area for years to come. The terms on which those issues are resolved will materially affect the costs and organizational feasibility of scientific projects that are of global reach and importance, especially those that depend heavily upon the collection, management and analysis of large volumes of observational data that cannot be regenerated. This paper sets out the economic case for the effectiveness of open, collaborative research, and the forces behind the recent, countervailing rush to strengthen and expand the scope of intellectual property rights protection. Focusing upon innovations in copyright law and the sui generis protection of hitherto unprotected content, it documents the genesis and analyzes the economic implications of the EC's Database Directive, and related legislative proposals (H.R. 3125, H.R. 354 and H.R. 1858) in the US. Several modest remedial proposals are advanced to mitigate the adverse impact of 'the digital technology boomerang' upon open science.intellectual property rights, copyright, sui generis protection of expressive material, economics of information-goods, open science, 'fair use,' scientific databases

High-Efficiency Digital Readout Systems for Fast Pixel-based Vertex Detectors

Particle physics is one of the science branches which heavily relies on most advanced technologies due to the increasing complexity of the problems it has to face. In future colliders, luminosities and beam energies are scaling upwards. These are necessary conditions for the discovery of new physics which both result in a larger amount of data that need to be brought out of the detector. That’s why one of the crucial points for new experiments is the evolution of data acquisition systems. Data acquisition systems employed in particle physics experiments followed the global technology trend and moved towards digital electronics and transmission lines, in this chapter we will describe how the effort of our work has been applied in this direction trying to extend digital processing on the very front-end of the detector. We will show how digital elaboration on the very front-end can help coping with new stringent requirements

Support for global science: Remote sensing's challenge

Remote sensing uses a wide variety of techniques and methods. Resulting data are analyzed by man and machine, using both analog and digital technology. The newest and most important initiatives in the U. S. civilian space program currently revolve around the space station complex, which includes the core station as well as co-orbiting and polar satellite platforms. This proposed suite of platforms and support systems offers a unique potential for facilitating long term, multidisciplinary scientific investigations on a truly global scale. Unlike previous generations of satellites, designed for relatively limited constituencies, the space station offers the potential to provide an integrated source of information which recognizes the scientific interest in investigating the dynamic coupling between the oceans, land surface, and atmosphere. Earth scientist already face problems that are truly global in extent. Problems such as the global carbon balance, regional deforestation, and desertification require new approaches, which combine multidisciplinary, multinational research teams, employing advanced technologies to produce a type, quantity, and quality of data not previously available. The challenge before the international scientific community is to continue to develop both the infrastructure and expertise to, on the one hand, develop the science and technology of remote sensing, while on the other hand, develop an integrated understanding of global life support systems, and work toward a quantiative science of the biosphere

Upgrading Pathways of Intelligent Manufacturing in China: Transitioning across Technological Paradigms

Intelligent technologies are leading to the next wave of industrial revolution in manufacturing. In developed economies, firms are embracing these advanced technologies following a sequential upgrading strategy—from digital manufacturing to smart manufacturing (digital-networked), and then to new-generation intelligent manufacturing paradigms. However, Chinese firms face a different scenario. On the one hand, they have diverse technological bases that vary from low-end electrified machinery to leading-edge digital-network technologies; thus, they may not follow an identical upgrading pathway. On the other hand, Chinese firms aim to rapidly catch up and transition from technology followers to probable frontrunners; thus, the turbulences in the transitioning phase may trigger a precious opportunity for leapfrogging, if Chinese manufacturers can swiftly acquire domain expertise through the adoption of intelligent manufacturing technologies. This study addresses the following question by conducting multiple case studies: Can Chinese firms upgrade intelligent manufacturing through different pathways than the sequential one followed in developed economies? The data sources include semi-structured interviews and archival data. This study finds that Chinese manufacturing firms have a variety of pathways to transition across the three technological paradigms of intelligent manufacturing in non-consecutive ways. This finding implies that Chinese firms may strategize their own upgrading pathways toward intelligent manufacturing according to their capabilities and industrial specifics; furthermore, this finding can be extended to other catching-up economies. This paper provides a strategic roadmap as an explanatory guide to manufacturing firms, policymakers, and investors.This research is supported by the National Natural Science Foundation of China (91646102, L1824039, L1724034, L1624045, and L1524015), the project of China’s Ministry of Education “Humanities and Social Sciences (Engineering and Technology Talent Cultivation)” (16JDGC011), CAE Advisory Project “Research on the strategy of Manufacturing Power towards 2035” (2019-ZD-9), the National Science and Technology Major Project “High-end Numerical Control and Fundamental Manufacturing Equipment” (2016ZX04005002), Beijing Natural Science Foundation Project (9182013), the Chinese Academy of Engineering’s China Knowledge Center for Engineering Sciences an Technology Project (CKCEST-2019-2-13, CKCEST-2018-1-13, CKCEST-2017-1-10, and CKCEST-2015-4-2), the UK–China Industry Academia Partnership Programme (UK-CIAPP\260), as well as the Volvo-supported Green Economy and Sustainable Development Tsinghua University (20153000181) and Tsinghua Initiative Research Project (2016THZW)

AI4D - African language dataset challenge

This work details the organisation of the AI4D - African Language Dataset Challenge, an effort to incentivize the creation, organization and discovery of African language datasets through a competitive challenge. As language and speech technologies become more advanced, the lack of fundamental digital resources for African languages (such as data, spell checkers and Part of Speech taggers) adds to the digital divide. Zindi, an African data science competition platform, hosted the AI4D - African Language Dataset Challenge in a bid to leverage the Zindi user base of 12,000 individuals.Swedish International Development Cooperation AgencyKnowledge4All FoundationZindi AfricaAI4D-Africa Networ