Browsing by Subject "data sharing"

Now showing 1 - 10 of 11
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    The Data Sharing Practices and Challenges in Uganda
    (2017-11) Tomusange, Issac; Yoon, Ayoung; Mukasa, Norman
    With the rapid development and increased use of information and communication technology (ICT), the demand for data sharing and reuse is growing even in developing countries. This study aims to contribute to the recently emerging discussions on data sharing in developing countries with a focus on the case of Uganda. The goal of this study is to uncover the current practices of and efforts for data sharing in the public sector in Uganda and to understand the relevant stakeholders’ perceptions of data sharing and reuse practices/services.
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    Enabling Secure and Effective Biomedical Data Sharing through Cyberinfrastructure Gateways
    (arXiv, 2020) Goyal, Shreya; Purkayastha, Saptarshi; Phillips, Tyler; Quick, Robert; Britt, Alexis; BioHealth Informatics, School of Informatics and Computing
    Scientific cyberinfrastructures promise solutions to computational challenges with rich resources; they embrace collaborative workflows in which users can access and share scientific data and computing resources to perform research and education tasks, which catalyze scientific discovery. The Dynaswap project reports on developing a coherently integrated and trustworthy holistic secure workflow protection architecture for cyberinfrastructures which can be used on virtual machines deployed through cyberinfrastructure (CI) services such as JetStream. This service creates a user-friendly cloud environment designed to give researchers access to interactive computing and data analysis resources on demand. The Dynaswap cybersecurity architecture supports roles, role hierarchies, and data hierarchies, as well as dynamic changes of roles and hierarchical relations within the scientific infrastructure. Dynaswap combines existing cutting-edge security frameworks (including an Authentication Authorization-Accounting framework, Multi-Factor Authentication, Secure Digital Provenance, and Blockchain) with advanced security tools (e.g., Biometric-Capsule, Cryptography-based Hierarchical Access Control, and Dual-level Key Management). The security technologies have been developed and integrated with the Open Medical Record System for enhanced security purposes and delivering a secure scientific infrastructure, which allows researchers, educators, practitioners, and students to remotely access and share sensitive data, computing resources, and workflows with flexibility and convenience while also having the highest security and privacy protection. The CI is being validated in life-science research environments and in the education settings of Health Informatics.
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    Final Report of IUPUI Public Access to Research Data Working Group
    (2022-04) Baich, Tina; Ben Miled, Zina; Berbari, Nick; Chu, Gabe; Coates, Heather; Erkins, Esther; Friesen, Amanda; Guiliano, Jen; Han, Jiali; Organ, Jason; Yoon, Ayoung
    In light of the movement towards greater access to and transparency in research, the Association of American Universities (AAU) and Association of Public and Land-grant Universities (APLU) convened gatherings in October 2018 and February 2020 to provide a venue for learning, sharing, and planning (campus roadmaps) to support research universities in creating and implementing strategies and systems to provide public access to research data. At the request of Vice Chancellor of Research Janice Blum, Heather Coates and Tina Baich attended the February 2020 gathering. The primary goals of the 2020 convening were to identify best practices, where they exist, to develop a Guide to Accelerating Public Access to Research Data at Academic Institutions (now available here), and to develop a strategic plan for AAU and APLU to drive future actions. As a result, Coates and Baich proposed that the Vice Chancellor for Research convene a working group to further this work on the IUPUI campus. Vice Chancellor Blum charged the Public Access to Research Data Working Group (PARDWG) with investigating the current landscape of data sharing at IUPUI and creating a plan to increase awareness and provide education of campus stakeholders around public access to research data. Working Group members were invited to ensure broad representation of disciplines, acknowledging that data sharing happens differently in different disciplines.
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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
    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; Murrilo, Angela
    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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    Love Data Week website 2016 - 2020
    (2020-06) Coates, Heather L.; Atwood, Thea; Bass, Michelle; Condon, Patricia; Foster, Erin D.; Graebner, Carla; Ippoliti, Cynthia; Julian, Renaine; Karcher, Sebastian; Kouper, Inna; Neeser, Amy; Ratajeski, Melissa; Beke-Harrigan, Heidi; Hardeman, Megan; Vecchio, Julie; Wright, Stephanie; Yin, Wei; Glusker, Ann; Sahadath, Catie; Chaput, Jennifer; Hannan, Katie; Woodbrook, Rachel; Adamus, Trisha
    All pages from the Love Data Week event website are archived here in PDF. Love Data Week was established in 2016 as Love Your Data week. Originally created in the USA, it quickly grew to an international event in which a wide range of institutions, organizations, scholars, students, and other data lovers could celebrate their data. Coordinated by Heather Coates, the planning committee developed themes, wrote, curated content, developed activities, all to celebrate data in all its forms, promote good research data management strategies, ask hard questions about the role of data in our lives, and share data success and horror stories. Though the website is defunct, the event lives on, driven by the community.
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    Meeting the NSF Data Management Plan Requirement, IFRA 2012
    (2013-01-28) Coates, Heather L.
    This invited presentation was given at the 2012 Indiana Forum for Research Administrators. It covers the various issues related to the NSF Data Management Plan Requirement and highlights the role of data in digital preservation, scholarly communication, and the responsible conduct of research and research ethics. In addition, services and resources provided by the IUPUI University Library in support of the NSF requirement are introduced.
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    Open Science: Models to Expand Open Access Beyond Scholarly Journals
    (The Charleston Co., 2016) Champieux, Robin; Coates, Heather L.; Emery, Jill
    In February 2016, Robin Champieux, Scholarly Communication Librarian at Oregon Health & Science University (OHSU) and Heather Coates, Digital Scholarship & Data Management Librarian at Indiana University Purdue University-Indianapolis (IUPUI) co-presented a webinar for Electronic Resources & Libraries on Open Science.
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    Raising the visibility of protected data: A pilot data catalog project
    (2020) Foster, Erin D.; Coates, Heather L.
    Sharing research data that is protected for legal, regulatory, or contractual reasons can be challenging and current mechanisms for doing so may act as barriers to researchers and discourage data sharing. Additionally, the infrastructure commonly used for open data repositories does not easily support responsible sharing of protected data. This chapter presents a case study of an academic university library’s work to configure the existing institutional data repository to function as a data catalog. By engaging in this project, university librarians strive to enhance visibility and access to protected datasets produced at the institution and cultivate a data sharing culture.
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    A Solutions-Based Approach to Building Data-Sharing Partnerships
    (AcademyHealth, 2018) Wiehe, Sarah E.; Rosenman, Marc B.; Chartash, David; Lipscomb, Elaine R.; Nelson, Tammie L.; Magee, Lauren A.; Fortenberry, J. Dennis; Aalsma, Matthew C.; School of Public and Environmental Affairs
    Introduction: Although researchers recognize that sharing disparate data can improve population health, barriers (technical, motivational, economic, political, legal, and ethical) limit progress. In this paper, we aim to enhance the van Panhuis et al. framework of barriers to data sharing; we present a complementary solutions-based data-sharing process in order to encourage both emerging and established researchers, whether or not in academia, to engage in data-sharing partnerships. Brief Description of Major Components: We enhance the van Panhuis et al. framework in three ways. First, we identify the appropriate stakeholder(s) within an organization (e.g., criminal justice agency) with whom to engage in addressing each category of barriers. Second, we provide a representative sample of specific challenges that we have faced in our data-sharing partnerships with criminal justice agencies, local clinical systems, and public health. Third, and most importantly, we suggest solutions we have found successful for each category of barriers. We grouped our solutions into five core areas that cut across the barriers as well as stakeholder groups: Preparation, Clear Communication, Funding/Support, Non-Monetary Benefits, and Regulatory Assurances. Our solutions-based process model is complementary to the enhanced framework. An important feature of the process model is the cyclical, iterative process that undergirds it. Usually, interactions with new data-sharing partner organizations begin with the leadership team and progress to both the data management and legal teams; however, the process is not always linear. Conclusions and Next Steps: Data sharing is a powerful tool in population health research, but significant barriers hinder such partnerships. Nevertheless, by aspiring to community-based participatory research principles, including partnership engagement, development, and maintenance, we have overcome barriers identified in the van Panhuis et al. framework and have achieved success with various data-sharing partnerships. In the future, systematically studying data-sharing partnerships to clarify which elements of a solutions-based approach are essential for successful partnerships may be helpful to academic and non-academic researchers. The organizational climate is certainly a factor worth studying also because it relates both to barriers and to the potential workability of solutions.