Data Science versus Information Science
informetrics and textual analysis
DOI:
https://doi.org/10.54886/scire.v27i2.4731Keywords:
Information Science, Data Science, Interdisciplinary relations, Scientific Documentation, Web of Science, Scopus, InformetricsAbstract
The aim of this paper is identifying the characteristics of the scientific literature located in the superposition of Data Science (DC) and Information Science (IS). For this, a descriptive study with informetric applications, and, as a first approximation, textual analysis was carried out. 58 and 49 records were recovered in Scopus and WoS, respectively, for the period 1900-november, 2020. Scopus documents were the most cited and with a greater typological variety. Conceptually, data is the element that connects both domains. Both are conceived as transversal areas of knowledge, that is, they are intra, multi and transdisciplinary. DS and IS are recent disciplines, in their process of definition, reconceptualization and conformation of their methods and categories of analysis of large amounts of data and information. The sum of studies that appears in WoS and Scopus show us that DS and IS complement themselves and intersect with other areas of scientific knowledge. They are also communicated in other languages than English: Italian, French, Portuguese and Japanese
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
© 1996- . Authors retain their copyright, but transfer the exploitation rights (reproduction, distribution, public communication and transformation) to the journal in a non-exclusive way and guarantee the right to the first publication of their work to the journal, which will be simultaneously subjected to the license CC BY-NC-ND. Authors take whole personal responsibility on fulfilling all the appropiate ethical codes and laws, and obtaining all the necessary copyright permissions regarding their articles. Institutional and self- archiving is allowed and encouraged.
