Panel Descriptions

Breakout Session 1: 1-2pm

  • Walking the Tightrope: Patient Care, Security, and Medical Research | chaired by Linda Duska

The Electronic Health Record is providing clinicians and patients with access to unprecedented amounts of health care data. In medical research, translational medicine seeks to transform findings into clinical practice. This session will explore the delicate balance between managing patient data, analytics, and security currently driving change in the medical research community.

In an innovation economy, companies are always looking for their next competitive edge. Data and analytics are often at the center of these discoveries, and many industries are only beginning to scratch the surface of possibilities unearthed by data science. Come and explore how data and analytics are driving business decisions, while learning of specific use cases across a variety of industry domains.

  • Becoming a Data-Enabled University | chaired by Ron Hutchins

In this age of Amazon and Google, we are surrounded by data in our daily lives, for our own use and for others’. Our ‘Fitbits’ collect data on our personal exercise routines. Grocery stores collect our spending habits and issue coupons marketed to our personal tastes.  The University of the 21st century will use data in ways that we have not yet seen. In this panel we will discuss the uses of data in student education (both teaching and learning), the research enterprise, and in the administration of a university of the future: the Data-enabled University. Through these discussions we will explore opportunities, benefits, and risks.

Breakout Session 2: 2:15-3:15pm

  • Impact and Innovation: Partnerships with Government and Industry | chaired by Joan Bienvenue

We say data science is a team sport equipped with domain experts, computing specialists, statisticians, and business leaders. However, creating those teams and finding the right players is not always easy. In academia we rely on partnerships with external entities like government agencies and corporate relationships in order to answer the world’s most challenging data science questions. This panel will discuss the complexities and the rewards of reaching across boundaries to create partnerships with industry and government. This will include discussions around accessing data, creating incentives for all sides, IP and NDA issues when working with researchers and students, and other challenging topics.

  • Data Integrity: Storing and Managing your Data | coordinated by Andrew Grimshaw

Whether a researcher needs to store petabytes or gigabytes of data, she faces the same Quality of Service (QoS) issues. QoS issues include: 1) performance (bandwidth and latency for read and write); 2) availability; 3) data integrity; 4) access modalities; 5) versioning; 6) secure sharing with collaborators and communities outside of UVa; 7) meta-data management; 8) provenance management; and 9) cost. The researcher must consider all of these issues when deciding what type of storage solution to use: cloud storage services, centralized file systems, parallel file systems (such as Lustre), object stores, or another solution. In this session, Grimshaw will elaborate on the tradeoffs between the various QoS issues, after which the panelists will discuss the pros and cons of different approaches.

  • Presidential Fellows in Data Science | chaired by Phil Trella

The Presidential Fellowships in Data Science are designed to facilitate deep collaborations between students (and their advisors) from diverse areas who have defined a problem, or problem area that is related to Big Data, or Data Science, and that requires the application of their collective, diverse knowledge and expertise.  Projects often address large, complex problems, with significant social impact, while advancing the individual work of each fellow in a significant way.