UVA Data Points

This episode was recorded during the Miller Center’s 2023 William and Carol Stevenson Conference, U.S. China Tech Competiton: Has Democracy Met its Match? 

For more info on this conference, as well as to watch the video versions, follow this link: https://millercenter.org/news-events/events/us-china-tech-competition-has-democracy-met-its-match

This episode features the first panel discussion from the conference entitled:

How might apps and other technology platforms play a role in Chinese government data-gathering efforts? What are potential policy responses to the increasingly complex data flows between the United States and China? This panel addresses the long-term stability of U.S. technology infrastructure and related concerns for U.S. national security. 

Josh Chin, Kara Frederick, Shanthi Kalathil, Aynne Kokas (moderator)

In this episode, we're thrilled to have Dr. Aynne Kokas, a C.K. Yen Professor at the Miller Center and an associate professor of media studies at the University of Virginia. Kokas’ research examines Sino-U.S. media and technology relations. Dr. Kokas is also the author of the critically acclaimed book "Trafficking Data: How China Is Winning the Battle for Digital Sovereignty," which we will be referring to frequently throughout this conversation. We will also touch on a few topics that were discussed in her recent conference at the Miller Center titled "U.S.-China Tech Competition: Has Democracy Met Its Match?"

During the event, Dr. Kokas and other experts discussed a variety of issues related to the ongoing tech competition between the US and China. For example, they explored the ways in which apps and other technology platforms may be used by the Chinese government for data-gathering purposes, and examined potential policy responses to the increasingly complex data flows between the two countries. Additionally, they discussed the long-term stability of US technology infrastructure and its implications for national security. In addition, there were panels that discussed the digital economy, climate, tech infrastructure, and political influence between China and the US.

In this episode we'll be discussing data policy for US-China technology, a topic that has become increasingly relevant in recent years as the two countries continue to compete for dominance in the tech industry. We'll delve into the differences in approach to data policy between China and the United States, the implications of these differences, and how China's digital silk road initiative is expanding its influence over the global digital economy.

We'll also discuss the challenges of balancing economic benefits against concerns about national security and human rights, and the future of the technology industry in light of these trends.

Links:

U.S.–China tech competition: Has democracy met its match?

Aynne Kokas website: https://www.aynnekokas.com/

Trafficking Data: How China Is Winning the Battle for Digital Sovereignty

This episode explores the intersection of neuroscience and data science with three experts in the field, Drs. John Darrell van Horn, Tanya Evans, and Teague Henry. As we know, the brain is complicated. People have been charting paths through the brain for decades, making breakthroughs and discoveries that have changed the world. In recent years though, new methodologies in brain research have made significant impacts. Advances in computing power, as well as techniques like machine learning, neural networks, and computer vision, have allowed researchers to ask questions and make discoveries that were not possible even ten years ago. Given these new approaches to studying the world’s most complicated organ, one could say that brain science is data science. Our guests make a compelling case.

This episode features a conversation between Lane Rasberry, Wikimedia-in-Residence at the University of Virginia School of Data Science, and Virginia Eubanks, author, journalist, and associate professor of political science at the University at Albany. 

The conversation was recorded in 2019 but the topics are still relevant today. Eubanks looks toward the future, warning of the unintended—or at times intended—consequences of emerging technologies. The discussion focuses on the effects of algorithmic automation, as well as the practice, policies, and implementation of these algorithms. Although she critiques the tech world, Eubanks also provides many reasons for optimism.

Virginia Eubanks authored the 2018 book Automating Inequality, which is a detailed investigation into data-based discrimination. She is also the author of Digital Dead End: Fighting for Social Justice in the Information Age and the co-editor, with Alethia Jones, of Ain’t Gonna Let Nobody Turn Me Around: Forty Years of Movement Building with Barbara Smith. She also writes for various outlets, including the Guardian, American Scientist, and the New York Times. Recently, Virginia began the PTSD Bookclub, an ongoing project that explores books about trauma and its aftermath. You can find this project and Virginia Eubank’s other projects at virginia-eubanks.com.

In this episode we’re bringing you a conversation on the future of academic data science recorded live at UVA Data Science’s Datapalooza 2022 event

Datapalooza is a flagship event for the School of Data Science. It’s typically held each year in November and features presentations by researchers here at UVA, as well as friends and collaborators of the School of Data Science.

In this episode we’re featuring a panel discussion between: 

Links:

Future of Academic Data Science video recording

Michigan Institue of Data Science 

UNC Charlottes School of Data Science

UVA School of Data Science

For our exploration of Analytics, we are diving into the world of sports. Because of advances in machine learning, wearable technology, and computer vision, the field of sport analytics is a whole new game. This episode gets into the details on what is new, the impact of analytics and technology on athletes and sports, as well as the ethics surrounding its implementation. Three experts from the University of Virginia School of Data Science met to discuss this exciting topic: Natalie Kupperman, Stephen Baek, and Don Brown.  

This bonus episode features a conversation between Lane Rasberry, Wikimedian-In-Residence at the UVA School of Data Science, and Lloyd Sy, a Ph.D. candidate in the UVA Department of English. In this conversation, Lane and Lloyd take a deep dive into the expansive world of Wikidata and ask the existential question, "What makes a person a person?" Or, more specifically, what data points make up a person? To help answer this question, Lloyd developed a large-scale data model of the biographical data contained within the Wikidata platform. This project serves as the foundation for their conversation. They also take a wide view of biographical data as it pertains to research and academia, including the process of gathering the data, the ethics of utilizing the data, personal ownership of the data, and much more. Anyone interested in these concepts should find this discussion valuable.

Links:

WikiProject Biography

Music:

"Screen Saver" Kevin MacLeod (incompetech.com)
Licensed under Creative Commons: By Attribution 4.0 License
http://creativecommons.org/licenses/by/4.0/

This episode on Systems explores the challenges of cloud computing within the framework of biomedical research. Phil Bourne, Dean of the UVA School of Data Science, speaks with computational biologist and associate professor Nathan Sheffield about a paper they co-wrote on systemic issues from cloud platforms that do not support FAIRness, including platform lock-in, poor integration across platforms, and duplicated efforts for users and developers. They suggest instead prioritizing microservices and access to modular data in smaller chunks or summarized form. Emphasizing modularity and interoperability would lead to a more powerful Unix-like ecosystem of web services for biomedical analysis and data retrieval. The two discuss how funders, developers, and researchers can support microservices as the next generation of cloud-based bioinformatics.

From Cloud Computing to Microservices: Next Steps in FAIR Data and Analysis

https://pubmed.ncbi.nlm.nih.gov/36075919/

The UVA School of Data Science was formed in September 2019 and has since grown in its collaborations, partnerships, program offerings, and teaching and research personnel. We are now constructing a new facility that will house the School of Data Science at the University of Virginia.

The new building is in the first phase of development and, once complete, will link the University's Central Grounds with the athletic fields and North Grounds. The 60,000-square-foot building is the future home of the UVA School of Data Science and will serve as the gateway to the new Emmet-Ivy Corridor and the Discovery Nexus.

This bonus episode is a conversation between UVA architect Alice Raucher and Mike Taylor, a principal with Hopkins Architects. Both Alice and Mike have been instrumental in the building’s design. Alice has also played a key role in the development of the Ivy Corridor. Mike and Alice take a deep dive into the thought process behind the building’s design, its relationship to the University and its history, the land's unique topography, and its significance to future projects along the Ivy Corridor. 

Links:

Hopkins Architects

School of Data Science New Building Website