Title: The professionalisation of data science
Author: Michael A. Walker
Address: Data Science Practice, Rose Technologies, Denver, Colorado, USA
Abstract: Data science is establishing basic foundations to become a profession. Like the professionalisation of law and medicine in the past 100 years, the data science field is at the very beginning of becoming a profession - with competency standards, a code of professional conduct, specialised graduate-level curriculums, certification and licensure and self-regulation. All professions require highly specialised education and training, an ethical code, self-regulation by a professional association and certification and licensing. Data science should become a profession for the same reasons medicine and law became professions: each requires practitioners to have a specialised body of knowledge, a code of conduct and self-regulation by knowledgeable professionals to assure competency and protect the public. The data science community can follow a roadmap for how data science can be professionalised by reviewing the history of the medical and legal professions. Suggested is a seven-step process for the professionalisation of data science.
Keywords: data science profession; data science professionalisation; licensure; certification; regulation; self-regulation; code of professional conduct; specialised knowledge; code of ethics; data science education; competency standards; ethical codes.
Int. J. of Data Science, 2015 Vol.1, No.1, pp.7 - 16
Available online: 19 Apr 2015