The creative industries are innovating to adapt to a changing digital culture and evidence does not support claims about overall patterns of revenue reduction due to individual copyright infringement. The experiences of other countries that have implemented punitive measures against individual online copyright infringers indicate that the approach does not have the impacts claimed by some in the creative industries. A review of the UK Digital Economy Act 2010 is needed based on independent analysis of the social, cultural and political impacts of punitive copyright infringement measures against citizens, and the overall experience of the creative industries.
Current research on flooding risk often focuses on understanding hazards, de-emphasizing the complex pathways of exposure and vulnerability. We investigated the use of both hydrologic and social demographic data for flood exposure mapping with Random Forest (RF) regression and classification algorithms trained to predict both parcel- and tract-level flood insurance claims within New York State, US. Topographic characteristics best described flood claim frequency, but RF prediction skill was improved at both spatial scales when socioeconomic data was incorporated. Substantial improvements occurred at the tract-level when the percentage of minority residents, housing stock value and age, and the political dissimilarity index of voting precincts were used to predict insurance claims. Census tracts with higher numbers of claims and greater densities of low-lying tax parcels tended to have low proportions of minority residents, newer houses, and less political similarity to state level government. We compared this data-driven approach and a physically-based pluvial flood routing model for prediction of the spatial extents of flooding claims in two nearby catchments of differing land use. The floodplain we defined with physically based modeling agreed well with existing federal flood insurance rate maps, but underestimated the spatial extents of historical claim generating areas. In contrast, RF classification incorporating hydrologic and socioeconomic demographic data likely overestimated the flood-exposed areas. Our research indicates that quantitative incorporation of social data can improve flooding exposure estimates.
This short article argues that an adequate response to the implications for governance raised by 'Big Data' requires much more attention to agency and reflexivity than theories of 'algorithmic power' have so far allowed. It develops this through two contrasting examples: the sociological study of social actors used of analytics to meet their own social ends (for example, by community organisations) and the study of actors' attempts to build an economy of information more open to civic intervention than the existing one (for example, in the environmental sphere). The article concludes with a consideration of the broader norms that might contextualise these empirical studies, and proposes that they can be understood in terms of the notion of voice, although the practical implementation of voice as a norm means that voice must sometimes be considered via the notion of transparency.
Product manufacturers are extending their responsibilities in the whole life cycle by providing services to their customers. In recent years, product service system has become an important research topic to address the special requirements in the new service driven business model. High value machine tools in modern manufacturing factories are special products: they are regarded as 'products' from maintenance point of view, and they also manufacture other products. In the new business model, the quality and behavior of a machine tool not only affect the quality of the parts it manufactures, but also affect the profits of the machine tool's manufacturer. However, in the research area of product service systems and related computerized maintenance systems, there is a lack of investigation into the special nature, problems and requirements of high value machine tool maintenance, which are very important in modern digitized manufacturing systems. Therefore, this research investigated the various relationships between different stakeholders in the machine tools' lifecycle, focusing on knowledge management, communication and the decision-making processes. This research also explored the potential application of advanced content management systems, which are widely implemented in the financial, business and government organizations, in the manufacturing engineering domain which has been dominated by traditional engineering information systems. A prototype collaborative maintenance planning system is proposed, developed and evaluated using an example machine tool, which indicated that significant improvement could be achieved and the content management technology has a number of advantages over the traditional engineering information systems, such as computer aided engineering, product data and lifecycle management, and enterprise resource planning systems, in managing machine tool maintenance and service information including dynamic and unstructured knowledge.
Social networking applications such as Facebook, Twitter, and YouTube are increasingly being used in various ways by organizations. In this article we examine the potential misuse of social media by employees, the UK legislation relevant to such misuse, and also examine approaches by which organizations can attempt to limit such misuse via appropriate guidance for employees.
This report presents the final policy recommendations for EU Kids Online Deliverable D7.2: Final recommendations for policy, methodology and research to the European Commission Safer Internet Programme (October 2011). It has been produced by Brian O'Neill, Sonia Livingstone and Sharon McLaughlin with members of the EU Kids Online network (Annex 1), as advised by the International Advisory Panel (Annex 2).
A central objective of EU Kids Online is to strengthen the evidence base for policies regarding online safety in Europe. Its findings regarding children's online experiences from across Europe offer an unrivalled opportunity to gain greater knowledge of European children's and parents' experiences and practices regarding risky and safer use of the internet and online technologies, thereby informing the promotion of a safer online environment for children. This chapter draws out in summary form the main implications for policy making and highlights significant issues arising from the findings of the survey, aligning them with existing initiatives where relevant in the distinct areas of risk and safety addressed. Policy actors addressed include policy makers at the European level, the Safer Internet Programme itself; Safer Internet Centres in each of the countries; national governments who play an important role in regulatory oversight; schools as central providers of internet safety training and education; industry at both national and European level as service providers and developers of children's online content; and finally, children, young people and their parents as not only the targets for awareness-raising but who also have active roles in promoting and supporting safer internet practices.
Front Cover; Digital Evidence and Computer Crime: Forensic Science, Computers and the Internet; Copyright; Table of Contents; Acknowledgments; Author Biographies; Introduction; Part 1. Digital Forensics; Chapter 1. Foundations of Digital Forensics; 1.1 Digital Evidence; 1.2 Increasing Awareness of Digital Evidence; 1.3 Digital Forensics: Past, Present, and Future; 1.4 Principles of Digital Forensics; 1.5 Challenging Aspects of Digital Evidence; 1.6 Following the Cybertrail; 1.7 Digital Forensics Research; 1.8 Summary; References; Chapter 2. Language of Computer Crime Investigation
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This article proposes a solution to understand the spatial hybridity of social media spaces such as Facebook and Instagram, constructed between a corporate entity and a civic space. Switching the main poles of third space theory to represent 'corporate' and 'civic' spaces, this essay compares Facebook/Instagram to similar off-line spaces in order to propose they are a 'corpo-civic' space. In doing so, it provides recommendations for fairer moderation of user content posted on these platforms based on international human rights standards and ethics that already exist off-line.
This work was supported by the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 812777. We also greatly appreciate funding from the Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (FORMAS) grants #2018-01074 and #2017-00946 to CG-B. FP appreciates funding from São Paulo Research Foundation (FAPESP, Brazil) projects #2016/20440-3 and #2018/13600-0. ; Background: Relationships among genetic or epigenetic features can be explored by learning probabilistic networks and unravelling the dependencies among a set of given genetic/epigenetic features. Bayesian networks (BNs) consist of nodes that represent the variables and arcs that represent the probabilistic relationships between the variables. However, practical guidance on how to make choices among the wide array of possibilities in Bayesian network analysis is limited. Our study aimed to apply a BN approach, while clearly laying out our analysis choices as an example for future researchers, in order to provide further insights into the relationships among epigenetic features and a stressful condition in chickens (Gallus gallus). Results: Chickens raised under control conditions (n = 22) and chickens exposed to a social isolation protocol (n = 24) were used to identify differentially methylated regions (DMRs). A total of 60 DMRs were selected by a threshold, after bioinformatic pre-processing and analysis. The treatment was included as a binary variable (control = 0; stress = 1). Thereafter, a BN approach was applied: initially, a pre-filtering test was used for identifying pairs of features that must not be included in the process of learning the structure of the network; then, the average probability values for each arc of being part of the network were calculated; and finally, the arcs that were part of the consensus network were selected. The structure of the BN consisted of 47 out of 61 features (60 DMRs and the stressful condition), displaying 43 functional ...
This paper examines the innovation strategy of Siemens, a key player in Europe's digital economy, by performing network and lexical analyses using data derived from Siemens's patents and scientific publications since 1998. We observe that the company's innovation efforts evolved from a broader attempt to develop internal information and communication technology (ICT) capabilities – alongside its historical industrial priorities – to a strategy focused on developing artificial intelligence (AI) for sector-specific and niche applications (such as life and medical sciences). As a result, it became dependent on tech giants' clouds for accessing more general AI services and digital infrastructure. We build on the intellectual monopoly literature focusing on the effects of tech giants on other leading corporations, to analyse Siemens's experience. By abandoning the development of general ICT and given the emergence of tech giants as digital economy intellectual monopolies, we show that Siemens is risking its technological autonomy towards these big tech companies. Our results provide clues to understand the challenges faced by Europe and its firms in relation to US and Chinese tech giants.
Meeting ambitious sustainability targets motivated by climate change concerns requires the structural transformation of many industries and the careful alignment of firm- and Government-level policymaking. While private firms rely on Government support to achieve timely the necessary green investment intensity, Governments rely on private firms to tackle financial constraints and technology transfer. This interaction is analysed in the real options literature only under risk neutrality, and, consequently, the implications of risk aversion due to the idiosyncratic risk that green technologies entail are overlooked. To analyse how this interaction impacts a firm's investment policy and a Government's subsidy design under uncertainty and risk aversion, we develop a real options framework, whereby: (i) we solve the firm's investment problem assuming an exogenous subsidy; (ii) conditional on the firm's optimal investment policy, we address the Government's optimisation objective and derive the optimal subsidy level; (iii) we insert the optimal subsidy level in (i) to derive the firm's endogenous investment policy. Contrary to existing literature, results indicate that greater risk aversion lowers the amount of installed capacity yet postpones investment. Also, although greater uncertainty raises the optimal subsidy under risk neutrality, the impact of uncertainty is reversed under high levels of risk aversion.