학술논문

BD2K Training Coordinating Center's ERuDIte: The Educational Resource Discovery Index for Data Science
Document Type
Periodical
Source
IEEE Transactions on Emerging Topics in Computing IEEE Trans. Emerg. Topics Comput. Emerging Topics in Computing, IEEE Transactions on. 9(1):316-328 Jan, 2021
Subject
Computing and Processing
Videos
Data science
Training
Metadata
YouTube
Big Data
Standards
Machine learning
education
database design
modeling and management
data and knowledge visualization
ontology design
Language
ISSN
2168-6750
2376-4562
Abstract
Data science is a field that has developed to enable efficient integration and analysis of increasingly large data sets in many domains. In particular, big data in genetics, neuroimaging, mobile health, and other subfields of biomedical science, promises new insights, but also poses challenges. To address these challenges, the National Institutes of Health launched the Big Data to Knowledge (BD2K) initiative, including a Training Coordinating Center (TCC) tasked with developing a resource for personalized data science training for biomedical researchers. The BD2K TCC web portal is powered by ERuDIte, the Educational Resource Discovery Index, which collects training resources for data science, including online courses, videos of tutorials and research talks, textbooks, and other web-based materials. While the availability of so many potential learning resources is exciting, they are highly heterogeneous in quality, difficulty, format, and topic, making the field intimidating to enter and difficult to navigate. Moreover, data science is rapidly evolving, so there is a constant influx of new materials and concepts. We leverage data science techniques to build ERuDIte itself, using data extraction, data integration, machine learning, information retrieval, and natural language processing to automatically collect, integrate, describe, and organize existing online resources for learning data science.