The professionalisation of data science. (2015)

• Record Type: Journal Article
• Authors: Walker, Michael A.
• Is Part Of: International journal of data science. Volume 1:Number 1(2015)
• Page Start: 7
• Page End: 16
• Publication Date: 2015
• Subjects: 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; Big data -- Periodicals; Data mining -- Periodicals; Information storage and retrieval systems -- Periodicals; Decision making -- Data processing -- Periodicals; 005.7
• Languages: English
• ISSNs: 2053-0811

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.