8 min listen
Reshaping Cloud Platforms with Microservices
FromUVA Data Points
ratings:
Length:
41 minutes
Released:
Nov 1, 2022
Format:
Podcast episode
Description
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 Microservices: Next Steps in FAIR Data and Analysis
https://pubmed.ncbi.nlm.nih.gov/36075919/
From Cloud Computing to Microservices: Next Steps in FAIR Data and Analysis
https://pubmed.ncbi.nlm.nih.gov/36075919/
Released:
Nov 1, 2022
Format:
Podcast episode
Titles in the series (24)
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