Data science from a library and information science perspective

Abstract

Purpose Data science is a relatively new field which has gained considerable attention in recent years. This new field requires a wide range of knowledge and skills from different disciplines including mathematics and statistics, computer science and information science. The purpose of this paper is to present the results of the study that explored the field of data science from the library and information science (LIS) perspective. Design/methodology/approach Analysis of research publications on data science was made on the basis of papers published in the Web of Science database. The following research questions were proposed: What are the main tendencies in publication years, document types, countries of origin, source titles, authors of publications, affiliations of the article authors and the most cited articles related to data science in the field of LIS? What are the main themes discussed in the publications from the LIS perspective? Findings The highest contribution to data science comes from the computer science research community. The contribution of information science and library science community is quite small. However, there has been continuous increase in articles from the year 2015. The main document types are journal articles, followed by conference proceedings and editorial material. The top three journals that publish data science papers from the LIS perspective are the Journal of the American Medical Informatics Association, the International Journal of Information Management and the Journal of the Association for Information Science and Technology. The top five countries publishing are USA, China, England, Australia and India. The most cited article has got 112 citations. The analysis revealed that the data science field is quite interdisciplinary by nature. In addition to the field of LIS the papers belonged to several other research areas. The reviewed articles belonged to the six broad categories: data science education and training; knowledge and skills of the data professional; the role of libraries and librarians in the data science movement; tools, techniques and applications of data science; data science from the knowledge management perspective; and data science from the perspective of health sciences. Research limitations/implications The limitations of this research are that this study only analyzed research papers in the Web of Science database and therefore only covers a certain amount of scientific papers published in the field of LIS. In addition, only publications with the term “data science” in the topic area of the Web of Science database were analyzed. Therefore, several relevant studies are not discussed in this paper that are not reflected in the Web of Science database or were related to other keywords such as “e-science,” “e-research,” “data service,” “data curation” or “research data management.” Originality/value The field of data science has not been explored using bibliographic analysis of publications from the perspective of the LIS. This paper helps to better understand the field of data science and the perspectives for information professionals.

Quality of Open Research Data: Values, Convergences and Governance

“…This is in accordance with the opinion that it is fundamental to understand the principles of design and information architecture [31]. All in all, data scientists can play an important role in quality control [32].…”

Data science and its relationship to library and information science: a content analysis

“…The search strategy discovered 80 publications published from 1980-2019. A statistical descriptive analysis of these papers provided answers to the first research question and was presented by Virkus and Garoufallou (2019a). The methodology and research approach were also tested in another paper by Virkus and Garoufallou (2019b), which dealt with data science from a perspective of computer science.…”

“…Researchers have discussed the concept and nature of data science, its origins, main areas, related concepts, relations to other disciplines, knowledge and skills required from data scientists, business value as well as potentials and limitations and data science-related activities. Virkus and Garoufallou (2019a) provided a bibliographic analysis of data science publications reflected in the Web of Science database in the research area of information science and library science and a literature review. In the following sections of this paper, a content analysis of the publications in the Web of Science database is provided.…”

“…For example, the Web of Science database has recorded 2,350 publications in the topic area "data science" in the period 1980-2019 by April 2019. And, 44.8% of publications came from the subject area of computer science, followed by engineering (18.2%), mathematics (7.4%), science technology and other topics (5.6%), business economic (4.6%), education and educational research (3.6%), information science and library science (3.4%), physics (2.9%), telecommunications (2.9%), medical informatics (2.7%), materials science (2.6%) and operations research and management science (2.6%) (Virkus and Garoufallou, 2019a). At 3.4%, the library and information science (LIS) contribution to data science in the period 1980-2019 was limited.…”

La informetría y el análisis del discurso aplicados a la producción científica en la Ciencia de Datos y Ciencia de la información

“…Sí existen trabajos que abordan la temática de manera amplia, es decir, sumando la búsqueda y análisis de los documentos científicos que tratan la CI y la CBI con la CD. Por ejemplo, se localizaron los artículos, "Data science and its relationship to library and information science: a content análisis" (Virkus y Garoufallou, 2020) y "Data science from a library and information science perspective" (Virkus y Garoufallou, 2019); y, una editorial, "Ciência de Dados e Ciência da Informação" (Freire y Freire, 2019).…”