Open AccessData, Information, Evidence, and Knowledge: A Proposal for Health Informatics and Data Science
Author(s) -
Olaf Dammann
Publication year - 2019
Publication title -
online journal of public health informatics
Language(s) - English
Resource type - Journals
ISSN - 1947-2579
DOI - 10.5210/ojphi.v10i3.9631
Subject(s) - raw data , computer science , data science , informatics , robustness (evolution) , relevance (law) , knowledge management , health informatics , hierarchy , information retrieval , medicine , engineering , public health , political science , nursing , biochemistry , chemistry , law , electrical engineering , gene , programming language
In this commentary , I revisit and modify Ackoff’s data-information-knowledge-wisdom (DIKW) hierarchy. I suggest to de-emphasize the wisdom part and to insert evidence between information and knowledge (DIEK). This framework defines data as raw symbols, which become information when they are contextualized. Information achieves the status of evidence in comparison to relevant standards. Evidence is used to test hypotheses and is transformed into knowledge by success and consensus. As checkpoints for the transition from evidence to knowledge I suggest relevance, robustness, repeatability, and reproducibility.