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A national data infrastructure (NDI) provides data, data-related services and guidelines for the re-use of data to individuals and organizations. It facilitates efficient sharing of data, supports new business models, and is thus ...
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A national data infrastructure (NDI) provides data, data-related services and guidelines for the re-use of data to individuals and organizations. It facilitates efficient sharing of data, supports new business models, and is thus a key enabler for the digital economy, open research, societal collaboration and political processes. While several European countries have taken steps to set up data infrastructures cutting across institutional silos, approaches vary, and there is no common understanding of what a NDI exactly comprises. In Switzerland, activities are still at a conceptual stage. In order to foster a shared vision of what a NDI is about, stakeholder interviews were carried out with representatives of public administration, research, civil society, and the private sector. There is broad consensus among key stakeholders that a NDI is to be conceived as a nationwide distributed technical infrastructure allowing the sharing of data, based on predefined rules. Our findings also suggest that the notion of a NDI should be approached from four perspectives: a big data, a base register, an open data, and a mydata perspective. For its implementation, effective coordination across several dimensions (ethical, legal, political, economical, organizational, semantical, and technical) is crucial, which calls for a truly multidisciplinary approach.
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Abstract As data becomes available online, it often remains inaccessible to marginalized communities where the resources, skills, and knowledge required to access and use such data are unevenly distributed. To make data more acces...
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Abstract As data becomes available online, it often remains inaccessible to marginalized communities where the resources, skills, and knowledge required to access and use such data are unevenly distributed. To make data more accessible to one such marginalized community in Atlanta’s Westside neighborhood, I participated in infrastructuring their civic data using city commons framework developed by Balestrini et al. This process involved three steps: taking a design based ethnographic approach to investigate a data dashboard, organizing data literacy workshops, and reimagining what a community-owned and operated form of data infrastructure would look like. My three-step process led me to identify the human infrastructure, which includes the individuals, organizations, values, needs, resources, and capital needed to do the work of infrastructuring civic data. I organize these elements of the human infrastructure into a taxonomy I call the Human Infrastructure of Civic Data (HICD). The HICD builds on the city commons framework and offers the CSCW community a taxonomy that can be used to identify the human infrastructure within communities and engage them in infrastructuring their civic data.
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Academic knowledge building has progressed for the past few centuries using small data studies characterized by sampled data generated to answer specific questions. It is a strategy that has been remarkably successful, enabling th...
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Academic knowledge building has progressed for the past few centuries using small data studies characterized by sampled data generated to answer specific questions. It is a strategy that has been remarkably successful, enabling the sciences, social sciences and humanities to advance in leaps and bounds. This approach is presently being challenged by the development of big data. Small data studies will however, we argue, continue to be popular and valuable in the future because of their utility in answering targeted queries. Importantly, however, small data will increasingly be made more big datalike through the development of new data infrastructures that pool, scale and link small data in order to create larger datasets, encourage sharing and reuse, and open them up to combination with big data and analysis using big data analytics. This paper examines the logic and value of small data studies, their relationship to emerging big data and data science, and the implications of scaling small data into data infrastructures, with a focus on spatial data examples.
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Academic knowledge building has progressed for the past few centuries using small data studies characterized by sampled data generated to answer specific questions. It is a strategy that has been remarkably successful, enabling th...
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Academic knowledge building has progressed for the past few centuries using small data studies characterized by sampled data generated to answer specific questions. It is a strategy that has been remarkably successful, enabling the sciences, social sciences and humanities to advance in leaps and bounds. This approach is presently being challenged by the development of big data. Small data studies will however, we argue, continue to be popular and valuable in the future because of their utility in answering targeted queries. Importantly, however, small data will increasingly be made more big data-like through the development of new data infrastructures that pool, scale and link small data in order to create larger datasets, encourage sharing and reuse, and open them up to combination with big data and analysis using big data analytics. This paper examines the logic and value of small data studies, their relationship to emerging big data and data science, and the implications of scaling small data into data infrastructures, with a focus on spatial data examples.
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Geothermal data are published using different IT services, formats and content representations, and can refer to both regional and global scale information. Geothermal stakeholders search for information with different aims. E-Inf...
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Geothermal data are published using different IT services, formats and content representations, and can refer to both regional and global scale information. Geothermal stakeholders search for information with different aims. E-Infrastructures are collaborative platforms that address this diversity of aims and data representations. In this paper, we present a prototype for a European Geothermal Information Platform that uses INSPIRE recommendations and an e-Infrastructure (D4Science) to collect, aggregate and share data sets from different European data contributors, thus enabling stakeholders to retrieve and process a large amount of data. Our system merges segmented and national realities into one common framework. We demonstrate our approach by describing a platform that collects data from Italian, French, Hungarian, Swiss and Icelandic geothermal data providers.
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Much of the literature on value creation in social media-based infrastructures has largely neglected the pivotal role of data and their processes. This paper tries to move beyond this limitation and discusses data-based value crea...
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Much of the literature on value creation in social media-based infrastructures has largely neglected the pivotal role of data and their processes. This paper tries to move beyond this limitation and discusses data-based value creation in data-intensive infrastructures, such as social media, by focusing on processes of data generation, use and reuse, and on infrastructure development activities. Building on current debates in value theory, the paper develops a multidimensional value framework to interrogate the data collected in an embedded ethnographical case study of the development of PatientsLikeMe, a social media network for patients. It asks when, and where, value is created from the data, and what kinds of value are created from them, as they move through the data infrastructure; and how infrastructure evolution relates to, and shapes, existing data-based value creation practices. The findings show that infrastructure development can have unpredictable consequences for data-baSed value creation, shaping shared practices in complex ways and through a web of interdependent situations. The paper argues for an understanding of infrastructural innovation that accounts for the situational inter-dependencies of data use and reuse. Uniquely positioned, the paper demonstrates the importance of research that looks critically into processes of data use in infrastructures to keep abreast of the social consequences of developments in big data and data analytics aimed at exploiting all kinds of digital traces for multiple purposes.
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In the context of NFDI4Health, a pilot project will be carried out in orderto establish possible roles, tasks and institutional positions of a datasteward. In the course of the pilot project, a concept is to be developedto allow f...
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In the context of NFDI4Health, a pilot project will be carried out in orderto establish possible roles, tasks and institutional positions of a datasteward. In the course of the pilot project, a concept is to be developedto allow for the cooperation between a specialised steward at the facultyand the library staff offering more generic training services.
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Se afirma explícita o implícitamente que una Infraestructura de Datos Espaciales (IDE) es un conjunto de herramientas o sistema informático integrado que persigue poner a disposición de todos los usuarios sin distinción la in...
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Se afirma explícita o implícitamente que una Infraestructura de Datos Espaciales (IDE) es un conjunto de herramientas o sistema informático integrado que persigue poner a disposición de todos los usuarios sin distinción la información geográfica (IG) disponible en la web, a través de un “escaparate” denominado geoportal.En este contexto, surge una interrogante a partir del análisis de los geoportales y de la afirmación de que deben ser [útiles] para todos los usuarios sin distinción: ?es eso una realidad o un desideratum?
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There is a critical need to make infrastructure systems more efficient, resilient, and sustainable. Infrastructure systems provide the basis for everyday life and enable the flow of goods, information, and services within urban an...
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There is a critical need to make infrastructure systems more efficient, resilient, and sustainable. Infrastructure systems provide the basis for everyday life and enable the flow of goods, information, and services within urban and regional settings. Providing data-centric solutions to improve this flow is essential. This can only be achieved if we manage to transform passive infrastructure assets into cyber-physical systems. Digital twins bring the opportunity to turn passive infrastructure assets into data-centric systems of systems.This article aims to provide a summary of existing digital twin architectures and exemplify a digital twin design and implementation. To this end, a literature review of digital twin architecture is presented in addition to a case study of a digital twin implementation in smart infrastructure. The case study focuses on a digital twin implementation of a bridge and describes in detail the physical, cyber, integration, and service layers of this implementation. Later in the article, we discuss the learnings from this case study under three main categories - systems perspective, information perspective, and organisational perspective. The findings show the importance of acquiring a systems perspective when designing digital twins today to enable interoperable systems of systems in the future. Furthermore, the findings highlight the vital necessity of data and information management while also considering the multidisciplinary aspects of digital twin design and implementation.
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