Whether or when: The question on the use of theories in data science

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Data Science can be considered a technique or a science. As a technique, it is more interested in the “what” than in the “why” of data. It does not need theories that explain how things work, it just needs the results. As a science, however, working strictly from data and without theories contradicts the post-empiricist view of science. In this view, theories come before data and data is used to corroborate or falsify theories. Nevertheless, one of the most controversial statements about Data Science is that it is a science that can work without theories. In this conceptual paper, we focus on the science aspect of Data Science. How is Data Science as a science? We propose a three-phased view of Data Science that shows that different theories have different roles in each of the phases we consider. We focus on when theories are used in Data Science rather than the controversy of whether theories are used in Data Science or not. In the end, we will see that the statement “Data Science works without theories” is better put as “in some of its phases, Data Science works without the theories that originally motivated the creation of the data.”.

Original languageEnglish (US)
Pages (from-to)1593-1604
Number of pages12
JournalJournal of the Association for Information Science and Technology
Issue number12
StatePublished - Dec 2021

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Networks and Communications
  • Information Systems and Management
  • Library and Information Sciences


Dive into the research topics of 'Whether or when: The question on the use of theories in data science'. Together they form a unique fingerprint.

Cite this