Empowering the data science scientist

• Published in: BioData mining Vol. 14; no. 1; pp. 8 - 3
• Main Author: Moore, Jason H.
• Format: Journal Article
• Language: English
• Published: London BioMed Central 23.01.2021; BioMed Central Ltd; Springer Nature B.V; BMC
• Subjects: Algorithms; Artificial intelligence; Bibliometrics; Big Data; Bioinformatics; Biomedical and Life Sciences; Biotechnology; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Data Mining and Knowledge Discovery; Editorial; Empowerment; Engineers; Funding; Gastroenterology; Life Sciences; Machine learning; Mechanical engineering; Nanotechnology; Neurology; Science; Scientists; Subject specialists
• ISSN: 1756-0381; 1756-0381
• DOI: 10.1186/s13040-021-00246-x

[...]data scientists are experts at data and knowledge integration and analysis. [...]being able to see and understand the downstream analytics pipeline could help the data scientist articulate questions which can be answered thus improving the likelihood of success. [...]we must provide federal and private funding opportunities for data scientists to be able to collect, integrate, and synthesize the data and knowledge sources from across domains. [...]we need to provide the recognition and rewards to encourage data scientists to take on data science scientist roles.