Amelia Acker
National Science Foundation (NSF)
10/01/2020 to 01/31/2024
$461,085 was awarded over the project period. Of the total funding, $303,031 was awarded to UT Austin iSchool.
Collaborative Research: Data Afterlives: The long-term impact of NSF Data Management Plans on data archiving and sharing for increased access
In 2011, the National Science Foundation began requiring that all funded projects provide data management plans (DMPs) to ensure that project data, computer codes, and methodological procedures were available to other scientists for future use. However, the extent to which these data management requirements have resulted in more and better use of project data remains an open question. This project thus investigates the National Science Foundation's DMP mandate as a national science policy and examines the broad impacts of this policy across a strategic sample of five disciplines funded by the National Science Foundation. It considers the organization and structure of DMPs across fields, the institutions involved in data sharing, data preservation practices, the extent to which DMPs enable others to use secondary project data, and the kinds of data governance and preservation practices that ensure that data are sustained and accessible. Systematic investigation of the impact of DMPs and data sharing cultures across fields will assist funding agencies and research scientists working to produce reproducible and open science by identifying barriers to data archiving, sharing, and access. The principal investigators will use project findings to develop data governance guidelines for information professionals working with scientific data and to articulate best practices for scientific communities using DMPs for data management.
This project aims to enhance understanding of the role data management plans (DMPs) play in shaping data life-cycles. It does so by examining DMPs across five fields funded by the National Science Foundation to understand data practices, archiving and access issues, the infrastructures that support data sharing and reuse, and the extent to which project data are later used by other researchers. In phase I, the investigators will gather a strategic sample of DMPs representing a wide range of data types and data retention practices from different scientific fields. Phase II consists of forensic data analysis of a subset of DMPs to discover what has become of project data. Phase III develops detailed case studies of research project data life-cycles and data afterlives with qualitative interviews and archival documentary analysis to help develop best practices for sustainable data preservation, access, and sharing. Phase IV will translate findings into data governance recommendations for stakeholders. The project thus contributes to research about contemporary studies of scientific data production and circulation while assessing the effect of DMPs as a national science policy initiative affecting data management practices in different scientific communities. The comparative research design and mixed methods enables theory building about cross-disciplinary data practices and data cultures across fields and advances knowledge within data studies, information management studies, and science and technology studies.
Amelia Acker
Institute of Museum and Library Services (IMLS)
06/01/2018 to 01/31/2024
The collaborative award is $199,811 over the project period. The School of Information portion of the award is $38,932.
Investigating Platform Development for Mobile and Social Media Data Preservation
The information we generate on social media sites and in mobile device apps represents the fastest form of data creation and collection in the United States. However, these data traces are complicated to work with because they are varied, inter-dependent, and vulnerable to loss. In this Early Career Development project, Dr. Amelia Acker at the University of Texas at Austin, will conduct a three-year, qualitative investigation into the activities of engineers and designers at five institutions where social media software is being developed. This project to better understand developer cultures will aid archives, libraries, and museums as they develop and implement best practices for gathering and preserving social media collections.
Matthew Lease
Micron Technology Inc.
08/01/2019 to 07/31/2022
The award is $150,000 over the project period.
Tackling Misinformation through Socially-Responsible AI
While the broad goals of socially responsible artificial intelligence (AI) appear clear in the abstract, how can we translate such goals into practice for a real problem facing our society today? We consider the following challenge: How can we design responsible AI technologies to curb the digital spread of misinformation?
Exploring real use cases and interface designs, we develop prototype AI applications and user-centered evaluations to remedy situations in which misinformation circulates online.
Kayla Booth
Jose Sanchez, Queens College, City University of New York;
Lynnette Yarger, The Pennsylvania State University;
Elizabeth Eikey, University of California San Diego
Institute of Museum and Library Science (IMLS)
04/01/2023 to 03/31/2024
The collaborative award is $246,588 over the project period. The School of Information portion of the award is $150,180.
Built-In Belonging: Scaling and Fostering Diverse and Inclusive Intergenerational Communities of Practice
The team has completed focus groups with iSchool Inclusion Institute participants where we piloted interview questions, tested and adjusted the questions, and gathered preliminary information on how community and belonging are cultivated. During the pandemic, we pivoted to longitudinal surveys where we used the theoretical framework and findings from the focus groups to investigate sense of belonging and community over time not only with LIS recruitment programs, but also compared to experiences in other institutions. We aim to now expand on the data collected primarily to complete interviews and disseminate findings. Interviews will provide nuanced data on how underrepresented students develop community within LIS recruitment programs, how this sense of community changes over time, which programmatic elements play a role in this evolution, how sense of community compares to experiences in other institutions, and how feelings in recruitment can scale to address isolation and gaps in support.
Amelia Acker
Megan Finn, University of Washington;
Ryan N. Ellis, Northeastern University
National Science Foundation (NSF)
02/01/2021 to 01/31/2024
The collaborative award is $199,811 over the project period. The School of Information portion of the award is $38,932.
RAPID International Type I: Collaborative Research: COVID Data Infrastructure Builders: Creating Resilient and Sustainable Research Collaborations
The COVID-19 pandemic has sparked thousands of new large-scale data projects globally. These COVID data infrastructures are essential: they enable the public, policymakers, public health officials, and others to see and comprehend particular aspects of the global health crisis. This research compares COVID data infrastructures in the U.S. and India, countries that share extremely high COVID infection rates as well as electoral democracy that encourages transparency; 'Data for Social Good' rhetoric; and large IT workforces. The project seeks to reveal how project leaders and contributors confront and manage the disruptions, hardships, and conflicts created by the pandemic. Working across different geographies and institutional settings, the research project will highlight how the pandemic impacts different communities in different ways. The research project will provide policymakers, technologists, and other leaders with insights and recommendations on how to improve the creation and maintenance of emergency data infrastructures. By understanding the dynamics of current COVID data infrastructures, we can be better prepared for the next emergency.
This RAPID research project investigates the creation, maintenance, and real-time transformation of novel critical data infrastructures. It uncovers the debates, conflicts, orderings, and important decisions that shape and define COVID data-tracker systems. At a time when the pandemic is disrupting ongoing research across the globe, these data-trackers can provide insights into how to create and maintain resilient and sustainable research-enabling infrastructure under conditions of significant stress. This RAPID project uses cross-national comparative analysis of public COVID data projects in the U.S. and India in order to identify the key factors that enable data infrastructures to endure the social and material disruptions associated with the pandemic. The project's cross-national and comparative research design ensures that research findings are generalizable. COVID data infrastructures are dynamic: the information, practices, tools, and collaborators that populate these systems constantly evolve. Often, the important adaptations that shape critical data infrastructures are not easily preserved using current web archiving and cumulative public data preservation methods. Additionally, the project's research design will capture this otherwise ephemeral data--allowing the project to analyze and interpret how these infrastructures are created and maintained under adverse conditions. The project is informed by and will contribute to the scholarly literature on ethnographies of technology development, infrastructure studies, and crisis informatics. Research findings will support concrete recommendations for how these and future data infrastructure can be made (1) sustainable; (2) accountable to different publics; and (3) improved in order to help save lives.