Document Type


Publication Date


Publication Title

Foundations of Data Science






During the emergence of Data Science as a distinct discipline, discussions of what exactly constitutes Data Science have been a source of contention, with no clear resolution. These disagreements have been exacerbated by the lack of a clear single disciplinary 'parent.' Many early efforts at defining curricula and courses exist, with the EDISON Project's Data Science Framework (EDISON-DSF) from the European Union being the most complete. The EDISON-DSF includes both a Data Science Body of Knowledge (DS-BoK) and Competency Framework (CF-DS). This paper takes a critical look at how EDISON's CF-DS compares to recent work and other published curricular or course materials. We identify areas of strong agreement and disagreement with the framework. Results from the literature analysis provide strong insights into what topics the broader community see as belonging in (or not in) Data Science, both at curricular and course levels. This analysis can provide important guidance for groups working to formalize the discipline and any college or university looking to build their own undergraduate Data Science degree or programs.


Archived as published. Open access paper.

First Page


Last Page


Digital Object Identifier (DOI)




To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.