Rebroadcast | Advances in Sports Analytics

Creating a Biased-Free Job Board with Matthew Thomas: This bonus episode features Matthew Thomas, a data scientist at Inclusively and a graduate of the UVA M.S. in Data Science program. He talks about how Inclusively works to create and maintain a job board designed specifically for job seekers with disabilities. Matthew explains how typical job boards come with many built-in biases that can screen out qualified individuals without them even knowing. He discusses the challenges of removing biases from algorithms and the importance of honesty and self-criticism when examining a data science project. As Cathy O’Neil challenged in Episode 1 of UVA Data Points, we should always ask ourselves, “For whom does this fail?” Matthew’s work is a good illustration of this sentiment in practice. In addition to discussing his work, Matthew also gives solid career advice for anyone seeking a similar career path in data science. by UVA Data Points

29 min listen

Ethical Data Science with Cathy O'Neil: UVA Data Points sits down with Cathy O'Neil, author of Weapons of Math Destruction, and Brian Wright, Assistant Professor of Data Science at the University of Virginia. The candid dialogue ranges from O'Neil's new book The Shame Machine to her work as an algorithm audit consultant. The two also draw comparisons between data science problems and knitting, as well as discuss educating future data scientists. Links: https://mathbabe.org (Cathy O'Neil's website) https://datascience.virginia.edu (UVA School of Data Science website) Books mentioned: The Shame Machine Weapons of Math Destruction by UVA Data Points

27 min listen

4 + 1 Model of Data Science: Before diving into the complex world of data science it seemed to wise to establish a shared definition of the field. Here at the UVA School of Data Science, we have defined data science with the 4 + 1 Model. This model serves an outline for the first series of UVA Data Points. It also serves as a guiding definition within the School of Data Science, touching everything from research to course planning. In this introduction trailer, host Monica Manney discusses the history, development, and function of the 4 + 1 Model of Data Science with its main author, Raf Alvarado. Below is a brief expect from An Outline of the 4 + 1 Model of Data Science by Raf Alvarado: “The point of the 4 + 1 model, abstract as it is, is to provide a practical template for strategically planning the various elements of a school of data science. To serve as an effective template, a model must be general. But generality if often purchased at the cost of intuitive understanding. The fol by UVA Data Points

8 min listen

WikiProject Biography: 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 expensive 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)Li by UVA Data Points

37 min listen

Advances in Sports Analytics: 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. by UVA Data Points

57 min listen

Future Home of the UVA School of Data Science: This bonus episode deviates from our central theme around the Domains of Data Science. 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 o by UVA Data Points

37 min listen

Exploring the Popol Vuh with Allison Bigelow and Raf Alvardo: Multepal Links: Digital Edition of the Popol Vuh: https://multepal.github.io/app-aanalte/xom-all-flat-mod-pnums-lbids.html Multepal Project: https://multepal.spanitalport.virginia.edu/ Multepal GitHub: https://github.com/Multepal Books Mentioned: Mining Language by Allison Bigelow by UVA Data Points

47 min listen

Fireside Chat with Kelli Palmer - Live from WiDS 2023 by UVA Data Points

60 min listen

Why Microservices Are Better Than Cloud Computing: This episode on Systems—one of the four Domains of Data Science UVA uses to define the field—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 by UVA Data Points

41 min listen

Brain Science is Data Science by UVA Data Points

45 min listen

Tik Tok, Data Governance, and the US China Landscape: A Conversation with Dr. Anne Kokas: 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 Sigh-no-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 by UVA Data Points

23 min listen

A Conversation with Virginia Eubanks: This episode features a conversation between Lane Rasberry, the Wikimedia-in-Residence at the UVA School of Data Science, and Virginia Eubanks, an author, journalist, and associate professor of political science at the University of Albany, SUNY. This conversation was recorded back in 2019, but it is still very relevant to our current moment. In many ways it is a discussion that looks towards the future, warning of the unintended, or at times intended, consequences of emerging technologies. The discussion largely focuses on the effects of algorithmic automation, as well as the practice, policies, and implementation of these algorithms. And, while the conversation lobs some heavy critiques at the tech world, it also provides many reasons for optimism. It’s a fascinating and multifaceted discussion. Virginia Eubanks is the author the 2018 book Automating Inequality, which is a detailed investigation into data-based discrimination. She is also the au by UVA Data Points

71 min listen

The Future of Academic Data Science: 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: Doug Hague, the Executive Director at UNC-Charlotte’s School of Data Science H.V. Jagadish, Director of the Michigan Institute for Data Science at the University of Michigan Phil Bourne, Dean of the UVA School of Data Science And Micaela Parker, Founder and Executive Director of the Academic Data Science Alliance. Micaela also serves as the moderator for this panel discussion. Links: Future of Academic Data Science video recording Michigan Institue of Data Science UNC Charlottes School of Data Science UVA School of by UVA Data Points

56 min listen

U.S. China Tech Competition | Apps, Platforms, and Surveillance: 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: Apps, platforms, and surveillance 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) by UVA Data Points

59 min listen

A View From Space | How LiDAR and Hyperspectral Imaging are Changing Science: The latest episode of UVA Data Points features Don Brown, the senior associate dean for research at the School of Data Science, and professor Bill Basener as they discuss remote sensing, which is the process of collecting data about an object without contacting it. The discussion traces the history of remote sensing, its many applications, and the challenges involved in gathering accurate information. The two take an in-depth look at Basener’s research, including his work with LiDAR and hyperspectral imaging. Basener also explains the one aspect of this burgeoning technology that keeps him up at night. by UVA Data Points

41 min listen

Swimming with Data | Diving into Student Life: This episode is a collaboration between UVA Data Points and Hoos in STEM. This episode of UVA Data Points features Ken Ono discussing the growth of data science at UVA and its increasing importance in various disciplines, including how he uses it to help swimmers improve performance. Ono is a professor of mathematics and STEM advisor to the provost, as well as a professor of data science by courtesy. He recently supported the women's team at the U.S. Olympic Trials in Japan.Ono speaks with three UVA swimmers who are pursuing graduate degrees in data science and statistics while also performing as student-athletes: August Lamb, Kate Douglass, and Will Tenpas. They discuss student life, balancing academics with swimming, and how data science and mathematics are helping them win championships. by UVA Data Points

47 min listen

Perspectives on the Meeting of Wikipedia & Artificial Intelligence: Excavating the Mother Lode of Human-Generated Text: A Systematic Review of Research That Uses the Wikipedia Corpus by UVA Data Points

76 min listen

A.I. Goes to School: The Future of Artificial Intelligence in Higher Ed: In this episode we’re looking at the past, present, and future of artificial intelligence in higher education. To explore this topics we’re featuring a conversation between Phil Bourne, the dean of the UVA School of Data Science, and Jeffrey Blume, the Associate Dean for Academic and Faculty Affairs, also at UVA Data Science. Jeffrey and Phil discuss the recent trends in artificial intelligence and they look at how this will impact the student experience, the faculty and staff experience, and the research landscape in higher education. by UVA Data Points

41 min listen

The AI Playbook | A Conversation with Eric Siegel: In his new book, “The AI Playbook: Mastering the Rare Art of Machine Learning Deployment,” Eric Siegel offers a detailed playbook for how business professionals can launch machine learning projects, providing both success stories where private industry got it right as well as cautionary tales others can learn from. Siegel laid out the key findings of his book in our latest episode during a wide-ranging conversation with Marc Ruggiano, director of the University of Virginia’s Collaboratory for Applied Data Science in Business, and Michael Albert, an assistant professor of business administration at UVA's Darden School. The discussion, featuring three experts in business analytics, takes an in-depth look at the intersection of artificial intelligence, machine learning, business, and leadership. http://www.bizML.comhttps://www.darden.virginia.edu/faculty-research/centers-initiatives/data-analytics/bodily-professorhttps://pubsonline.inform by UVA Data Points

73 min listen

Rebroadcast | Advances in Sports Analytics: 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. On behalf of everyone here at the School of Data Science, thank you and we’ll see you next year by UVA Data Points

54 min listen

Rebroadcast | Future Home of the UVA School of Data Science: 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 proc by UVA Data Points

37 min listen

The Future Impact of AI on Society Panel | Live from Datapalooza: Artificial intelligence has the potential to change our societies, economies, and political systems in both intentional and unintended ways. While it is difficult to understand the full extent of what the long-term impacts may be, we have enough shared knowledge and expertise to predict the likely shapes that these changes may take—both for better and for worse. More importantly, we should ask ourselves what kind of future we want AI to help us create: what we want from the future of AI should ultimately determine the future of AI. This panel will bring together experts to discuss the intersection of AI and society and offer suggestions for how AI might work within a just, inclusive, sustainable, and fair digital future. Panelist Farhana Faruqe, Assistant Professor of Data Science Sarah Lebovitz, Assistant Professor of Commerce Larry Medsker, Research Professor, George Washington University Mar Hicks, Associate Profes by UVA Data Points

58 min listen

The Story of Us: To view the full digital exhibition visit: https://story.datascience.virginia.edu/ The Story of Us is a digital brand showcase that chronicles the creation of a data science school at the University of Virginia. From an idea to an institute, and now to the first school of its kind in the nation, this bespoke, interactive website tells the story through written and spoken narrative supported by multimedia, archival documentation, and testimony from a diversity of voices. The result is a unique brand piece that combines technology with art, a retrospective of one school’s past and how it will inform its future. It was commissioned by the School of Data Science to mark the opening of its new building in April 2024. The Story of Us website was built by John Baxton, senior web developer for the School of Data Science, who worked in close collaboration with Sue Haas, the School’s information technology director. The designs for the site were created by the Charlottesville-ba by UVA Data Points

106 min listen

The Future of Data Science Education | Live from Datapalooza: This panel delves into how the faculty at UVA's School of Data Science are actively working to craft a liberal arts curriculum suitable for the digital age, one that not only adapts to but embraces changes in technology and practice. The panel discusses the future of data science education, including in K-12, the school’s guiding philosophy for its undergraduate and graduate programs (minor, B.S., online and residential M.S., Ph.D.), and the merits as well as challenges that arise when constructing a new educational curriculum for a new discipline. by UVA Data Points

62 min listen

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Rebroadcast | Advances in Sports Analytics

Rebroadcast | Advances in Sports Analytics

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