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  • Republic of the Philippines e-Government Transformation

    Capili, Miro Frances (World Bank, Washington, DC, 2016-03-02)
    The Philippines is one of the eight
 founding members of the open government partnership (OGP)
 alongside Brazil, Indonesia, Mexico, Norway, South Africa,
 United Kingdom, and the United States. The overarching
 concept of open government recognizes that good governance
 derives from the principle of transparency by providing an
 easily accessible, readily usable, and up-to-date online
 platform of digitized public records. Open data is an
 important component and commitment area of the OGP. The
 Philippines developed its first national open government
 action plan, which detailed nineteen initiatives under four
 broad outcome areas, from June to September 2011. This paper
 aims to: (1) document the historical development, key
 drivers, and milestones of open government Philippines and
 open data Philippines, and (2) pose recommendations for
 moving forward with its commitments. It reviews the
 composition and formation of the open data task force and
 showcases the features of data.gov.ph. The paper seeks to
 pose recommendations pertaining to the following areas: (1)
 release and manage organized, operable, and relevant data;
 (2) refine technical aspects of open data; (3)
 institutionalize open data within government; (4) promote
 civic engagement and stakeholder outreach; and (5) adopt
 complementary metrics and measures of success. The paper
 also opens a series of reports on the key stages in the
 development of the program, including implementation and
 impact evaluation.
  • Using Locational Data from Mobile Phones to Enhance the Science of Delivery

    Kelly, Tim; Saarinen, Vesa; Haddad, Ryan; Leinonen, Teemu (World Bank, Washington, DC, 2014-06)
    The objective of this report is to
 examine the potential of locational data for the
 'science of delivery' in the field of development.
 The 'science of delivery' is a term popularized by
 the World Bank President, Jim Yong Kim, and refers to using
 evidence-based experimentation to improve development
 outcomes (Walji, 2013). In this context, locational data is
 a new tool that is starting to be used in a variety of
 development fields including health, education, disaster
 risk management, traffic planning etc. this broad
 introduction to the topic in chapter one, the next chapter
 explores the technology behind locational data. Chapter
 three presents the methodology followed in this research and
 chapter four, which is the heart of this report, then
 presents a series of mini case studies of how it is actually
 being used in a representative sample of different
 development fields. This is the 'evidence-based
 experimentation' which can be harnessed to improve the
 'science of delivery', and examples of both active
 and passive collection of locational data are presented.
 Finally, chapter five examines, in broader terms, the longer
 term potential of locational data as a development tool,
 once smartphone ownership becomes more widespread.
  • Digital transformation management: Scientific approaches and economic policy

    Valery V. Aturin; Irina S. Moga; Samal M. Smagulova (Ural State University of Economics, 2020-04-01)
    The article explores the problems and trends in digital transformation of the world economy in the context of revolutionary changes in the technological sphere, unstable state of a number of national economies and international trade. The theoretical and methodological basis of the study includes the traditional ideas about technological advances and their impact on global reproduction, as well as the conceptual framework of digital economy. The authors follow the research methods, such as comparative analysis, synthesis, historical and logical methods. The research identifies the evaluation parameters of digital transformation, including the assessment of broadband internet access, the potential of reducing the cost price of digital devices and the marginal cost of traditional industries, and the assessment of the convergence and the speed of technology diffusion. The authors find that the key characteristics of new economic policy are flexibility and detailed specification to fine-tune the combination of tools depending on the object of management. Having analyzed the avenues for digital transformation, we establish the areas of high uncertainty – job market, data control, security, the environment, etc. – that act as potential sources of shocks. Our findings also prove the necessity to create conditions for the growth of technology-centric companies.
  • Emotion-Driven System for Data Center Management

    Alberto Corredera; Marta Romero; Jose M. Moya (MDPI AG, 2019-09-01)
    Complex Information Systems and infrastructures, like Smart Cities, must be efficiently operated, minimizing inefficiencies and maximizing productivity. Traditional approaches are focused on improving the systems, automating processes and services, leaving aside human and emotions considerations. To achieve this efficient operation, we attempted to cover both sides. We found new ways to capture the information coming from the workforce, in our case, the operations management team, and, merged this information with the data from the IoT sensors from the systems, enabling a holistic view of the entire operations occurring in real-time. In a Data Center environment, we have developed a set of tools for capturing the emotional data in order to detect potential biases caused by the specific mood of the person inside the operations team. We used Artificial Intelligence algorithms for finding the patterns that will help us to manage the system in the future. We compared and verified our findings with the existing references from other disciplines, e.g., Psychology. In this article, we expose some methods to be developed in future studies for supervising and increasing productivity in Data Centers, as a useful example for Smart Cities. Our research focuses on monitoring the mood and the emotional status of the personnel responsible for operating the system. We use this emotional data as an input for measurement.

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