Browsing by Author "Jeng, Wei"

Now showing 1 - 6 of 6
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    Confronting the Challenges of Computational and Social Perspectives of the Data Continuum
    (Sciendo, 2020-06) Murillo, Angela P.; Curty, Renata G.; Jeng, Wei; He, Daqing; Library and Information Science, School of Informatics and Computing
    As the availability of data is increasing everyday, the need to reflect on how to make these data meaningful and impactful becomes vital. Current data paradigms have provided data life cycles that often focus on data acumen and data stewardship approaches. In an effort to examine the convergence, tensions, and harmonies of these two approaches, a group of researchers participated in an interactive panel session at the Association of Information Science and Technology Annual meeting in 2019. The panel presenters described their various research activities in which they confront the challenges of the computational and social perspectives of the data continuum. This paper provides a summary of this interactive panel.
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    The Convergence of Computational and Social Approaches for Unveiling Meaningful and Valuable Data
    (Wiley, 2019) Murillo, Angela P.; Curty, Renata G.; Jeng, Wei; He, Daqing; Library and Information Science, School of Informatics and Computing
    The current data paradigm is seeking a more integrated and comprehensive framework to make sense of data and its derived issues. From the perspective of the data life cycle, we argue that computational and social approaches complement each other to confront data challenges. Computational approaches consist of ETL (extract, transform, and load), modeling, and machine learning techniques; social approaches include policy and regulations, data sharing and reuse behavior, reproducibility, ethical and privacy issues. In this panel, we frame these two approaches as data acumen and data stewardship. The merging of these two perspectives allows data not only to become discoverable, accessible, and interoperable, but also to further the value of revealing meaningful patterns and become supportive evidence for important decision making. In this panel, the opening facilitator and three panelists will report on their recent studies in terms of this convergence of both data acumen and stewardship while sharing their recent research insights on case studies in three disciplines: agriculture, biomedicine, and archeology.
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    Data curation as collective action during COVID-19
    (Wiley, 2021-03) Shankar, Kalpana; Jeng, Wei; Thomer, Andrea; Weber, Nicholas; Yoon, Ayoung; Library and Information Science, School of Informatics and Computing
    In this commentary, the authors, an international group data curation researchers and educators, reflect on some of the challenges and opportunities for data curation in the wake of the COVID-19 pandemic. We focus on some topics of particular interest to the information science community: data infrastructures for scholarly communication and research, the politicization of data curation and visualization for public-facing “dashboards,” and human subjects research and policies. We conclude with some areas of opportunity and need, including broader and richer data curation education in the information schools, the establishment of better data management policy implementations by research funders, the award of formal academic credit for data curation activities and data sharing, and engagement in cooperative action around data ethics and security.
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    In between data sharing and reuse: Shareability, availability and reusability in diverse contexts
    (2017-11) Yoon, Ayoung; Jeng, Wei; Curty, Renata; Murillo, Angela P.
    Although data availability cannot be considered the sole predictor of effective reuse, because only accessible and well-managed data can make reuse possible, data reuse is contingent on the availability of data. It is critical to understand the nature of shareability, availability, and reusability, and their synergy and relationships, to further understand the dynamics of data reuse practices in multiple environments and contexts. This panel aims to closely examine aspects related to data shareability, availability and reusability, based on the assumption that each condition poses a cumulative effect on each other and impacts the efficiency and efficacy of the data reuse process. The panelists will present their findings and perspectives in a diverse context regarding data availability, between academic and non-academic; data shareability and data reusability, social sciences and earth science, researchers’ and journal publishers’ perspectives. Presentations will be followed by an interactive session taking the team-based approach, with the expectation to engage participants in discussion and experience-sharing, and to contribute in terms of practice and research with the current knowledge and applications.
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    In between data sharing and reuse: Shareability, availability and reusability in diverse contexts
    (2017-11) Yoon, Ayoung; Jeng, Wei; Curty, Renata; Murillo, Angela P.
    Although data availability cannot be considered the sole predictor of effective reuse, because only accessible and well-managed data can make reuse possible, data reuse is contingent on the availability of data. It is critical to understand the nature of shareability, availability, and reusability, and their synergy and relationships, to further understand the dynamics of data reuse practices in multiple environments and contexts. This panel aims to closely examine aspects related to data shareability, availability and reusability, based on the assumption that each condition poses a cumulative effect on each other and impacts the efficiency and efficacy of the data reuse process. The panelists will present their findings and perspectives in a diverse context regarding data availability, between academic and non-academic; data shareability and data reusability, social sciences and earth science, researchers’ and journal publishers’ perspectives. Presentations will be followed by an interactive session taking the team-based approach, with the expectation to engage participants in discussion and experience-sharing, and to contribute in terms of practice and research with the current knowledge and applications.
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    Untangling data sharing and reuse in social sciences
    (2016) Yoon, Ayoung; Curty, Renata; Jeng, Wei; Qin, Jian
    The discipline of social science has unique research norms and cultures regarding data sharing and reuse that can be affected by complex factors related to context, time and dependence on human subjects. Compared with STEM disciplines, social sciences emphasize the protection of study participants and observees. Extra effort is required from reusers to preserve data interconnectedness in order to guarantee the data's understandability and informative value. In this panel, the panelists will present their research findings and provide perspective on social science data sharing and reuse, including factors that may influence data reuse behavior, researchers' trust judgment in data for data reuse, and infrastructural barriers and incentives for data sharing among social scientists. This panel aims to provide an overview of the current state of social science data reuse and sharing, and, in collaboration with panel participants, elicit topics for future research. It also proposes a practical agenda to develop alternative incentives for individual researchers, and potential ways in which data sharing and reuse can be improved, coordinated, and encouraged among social scientists.