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

2020 ◽  
Vol 54 (5) ◽  
pp. 643-663
Author(s):  
Sirje Virkus ◽  
Emmanouel Garoufallou
Keyword(s):  
Content Analysis ◽  
Data Science ◽  
Information Science ◽  
Web Of Science ◽  
Research Data ◽  
Library And Information Science ◽  
Content Type ◽  
Knowledge And Skills ◽  
And Training ◽  
The Web

PurposeThe purpose of this paper is to present the results of a study exploring the emerging field of data science from the library and information science (LIS) perspective.Design/methodology/approachContent analysis of research publications on data science was made of papers published in the Web of Science database to identify the main themes discussed in the publications from the LIS perspective.FindingsA content analysis of 80 publications is presented. The 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. The category of tools, techniques and applications of data science was most addressed by the authors, followed by data science from the perspective of health sciences, data science education and training and knowledge and skills of the data professional. However, several publications fell into several categories because these topics were closely related.Research limitations/implicationsOnly publication recorded in the Web of Science database and with the term “data science” in the topic area were analyzed. Therefore, several relevant studies are not discussed in this paper that either were related to other keywords such as “e-science”, “e-research”, “data service”, “data curation”, “research data management” or “scientific data management” or were not present in the Web of Science database.Originality/valueThe paper provides the first exploration by content analysis of the field of data science from the perspective of the LIS.

Data science from a library and information science perspective

2019 ◽  
Vol 53 (4) ◽  
pp. 422-441 ◽  
Author(s):  
Sirje Virkus ◽  
Emmanouel Garoufallou
Keyword(s):  
Computer Science ◽  
Data Science ◽  
Information Science ◽  
Web Of Science ◽  
Research Data ◽  
Library And Information Science ◽  
Content Type ◽  
Knowledge And Skills ◽  
Computer Science Research ◽  
The Web

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.

Subject analysis of LIS data archived in a Figshare using co-occurrence analysis

2019 ◽  
Vol 43 (2) ◽  
pp. 256-264 ◽  
Author(s):  
Jane Cho
Keyword(s):  
Open Access ◽  
Data Science ◽  
Information Science ◽  
Scholarly Communication ◽  
Research Data ◽  
Intellectual Structure ◽  
Library And Information Science ◽  
Content Type ◽  
Subject Analysis ◽  
Interdisciplinary Field

Purpose Based on the data from Figshare repositories, the purpose of this paper is to analyze which research data are actively produced and shared in the interdisciplinary field of library and information science (LIS). Design/methodology/approach Co-occurrence analysis was performed on keywords assigned to research data in the field of LIS, which were archived in the Figshare repository. By analyzing the keyword network using the pathfinder algorithm, the study identifies key areas where data production is actively conducted in LIS, and examines how these results differ from the conventional intellectual structure of LIS based on co-citation or bibliographic coupling analysis. Findings Four major domains – Open Access, Scholarly Communication, Data Science and Informatics – and 15 sub-domains were created. The keywords with the highest global influence appeared as follows, in descending order: “open access,” “scholarly communication” and “altmetrics.” Originality/value This is the first study to understand the key areas that actively produce and utilize data in the LIS field.

scholarly journals Introducing web components into the LIS graduate curriculum

2017 ◽  
Vol 118 (11/12) ◽  
pp. 660-668
Author(s):  
Judith Wusteman
Keyword(s):  
Design Methodology ◽  
Information Science ◽  
Graduate Programs ◽  
Library And Information Science ◽  
Web Development ◽  
Content Type ◽  
Graduate Curriculum ◽  
Seismic Impact ◽  
The Web

Purpose This paper introduces web components, one of the most exciting and potentially transformative of the technologies that comprise HTML5. Web components provide a standardised method of creating and sharing custom HTML elements. Design/methodology/approach This paper is a viewpoint. Findings The paper proposes that the web development curriculum in library and information science (LIS) graduate programs needs to expand to cover this important topic. Originality/value Despite the potentially seismic impact of web components on Web development, up until this point, there has not been a discussion of this technology within the LIS literature.

Exploring academic libraries’ use of Twitter: a content analysis

2015 ◽  
Vol 33 (6) ◽  
pp. 1002-1015 ◽  
Author(s):  
Sultan M. Al-Daihani ◽  
Suha A. AlAwadhi
Keyword(s):  
Content Analysis ◽  
Academic Libraries ◽  
Information Science ◽  
Descriptive Analysis ◽  
Academic Library ◽  
Library And Information Science ◽  
Science Literature ◽  
Content Type ◽  
Patterns Of Communication ◽  
Library Marketing

Purpose – This research aims to analyze academic libraries’ Twitter content and present a categorization framework for the study of their tweets. Design/methodology/approach – The research adopted a statistical descriptive analysis in addition to a content analysis of the tweets. Consequently, many categories and subcategories were created to classify the tweets according to different aspects. A total of 17 academic library accounts were examined. Findings – The findings show that academic libraries used Twitter as a multifaceted tool. “News and announcements” received the highest score as the type of information most often posted on Twitter by libraries, followed by “library collections” and “library services”. The subcategories that received the highest scores were “library marketing and news”, “answers and referrals” and “books”. Academic libraries showed a penchant for posting links more often than other content. Other results show different patterns of communication and interaction between libraries and their Twitter followers. Practical implications – The categorization of tweets provides a framework for understanding how academic libraries use Twitter. Originality/value – As little research can be found in the library and information science literature on Twitter content analysis, this research is expected to contribute significantly. It will also support academic libraries and librarians in using Twitter more efficiently and effectively.

Library and information science research in BRICS countries

2018 ◽  
Vol 119 (3/4) ◽  
pp. 183-202
Author(s):  
Manorama Tripathi ◽  
V.K.J. Jeevan ◽  
Parveen Babbar ◽  
Lohrii Kaini Mahemei
Keyword(s):  
South Africa ◽  
Information Science ◽  
Web Of Science ◽  
Research Output ◽  
Library Science ◽  
Library And Information Science ◽  
Content Type ◽  
Global Issues ◽  
Brics Countries

Purpose This paper aims to highlight the research output of library and information science of the BRICS (Brazil, Russia, India, China and South Africa) nations during the ten year period, i.e. 2005-2014, as reflected through the Web of Science database. Design/methodology/approach This study used Social Science Index (SSCI) of Web of Science (WoS) citation database to collect data for the ten year period. All records indexed in SSCI were refined by subject area of “Information Science and Library Science” and selected countries. The downloaded results were analyzed by using specific parameters. Findings WoS indexes different kinds of documents, such as articles, conference proceedings, biographical items, book reviews, corrections, editorial material, letters, reprints and reviews. Out of the BRICS output, almost 90 per cent of papers were articles. Other types of documents included conference papers, review papers and book reviews. China contributed nearly half of the documents followed by Brazil, South Africa, India and Russia. On an average, a document had cited 34 references. More than one-third of records did not receive any citations. It has been observed that the titles that had 11-16 words attracted the most number of citations. The top ten publishers in whose journals the researchers published included Emerald, Elsevier and Springer. The primary subject areas were information science and library science, information systems, interdisciplinary applications and management. About 85 per cent of the documents were published in English. Around 93 per cent of the non-English research publications were in Portuguese, the official language of Brazil. Originality/value There are not many studies on BRICS countries and that too about Library and Information Science (LIS) research output. This study may reveal insights into how LIS researchers interact with local and global issues in a specific spectrum of the world community.

Collaborative information seeking environments benefiting from holistic ergonomics

2015 ◽  
Vol 33 (3) ◽  
pp. 439-459 ◽  
Author(s):  
Anika Meyer ◽  
Ina Fourie
Keyword(s):  
Content Analysis ◽  
Information Seeking ◽  
Information Science ◽  
Library And Information Science ◽  
Research Approach ◽  
Science Literature ◽  
Content Type ◽  
Social Perspectives ◽  
Collaborative Information Seeking ◽  
Practical Implications

Purpose – The purpose of this paper is to explore the value of utilising a holistic ergonomic approach, covering engineering, cognitive and social perspectives, to cultivate beneficial and productive collaborative information seeking (CIS) systems and environments, specifically with regard to three main CIS pillars (control, communication and awareness). Design/methodology/approach – A qualitative research approach, based on a selective corpus of CIS literature, was utilised to perform a content analysis to note if terms and concepts normally associated with engineering, cognitive and social ergonomics can be used to eliminate terms reflecting issues related to three CIS pillars (control, communication and awareness) that can benefit from a holistic ergonomic approach. Findings – The content analysis revealed that a fairly extensive amount of holistic ergonomic terminology is prominent within the CIS literature, therefore establishing a connection between the two disciplines: CIS and ergonomics. This suggests that CIS system issues could benefit from the insights of a holistic ergonomic approach. Research limitations/implications – Since this is an exploratory study the scope of CIS literature utilised in the content analysis was limited to a selection considered most important by the authors; this should be supplemented by further research. Practical implications – Intended to instigate interest in further exploration of the beneficial and productive implications and practical application of holistic ergonomics in designing CIS systems and environments. Originality/value – This is the first research paper in the Library and Information Science literature that explores the potential of utilising holistic ergonomics to cultivate CIS systems and environments.

Informatics and data science: an overview for the information professional

2016 ◽  
Vol 32 (1) ◽  
pp. 7-10 ◽  
Author(s):  
H Frank Cervone
Keyword(s):  
Design Methodology ◽  
Data Science ◽  
Information Science ◽  
Information Environment ◽  
Library And Information Science ◽  
Content Type ◽  
Information Professional ◽  
Information Professionals ◽  
Traditional Approaches ◽  
Information Landscape

Purpose – This paper aims to describe the emerging field of data science, its significance in the larger information landscape and some issues that distinguish the problems of data science and informatics from traditional approaches in the information sciences. Design/methodology/approach – Through a general overview of the topic, the author discusses some of the major aspects of how work in the data sciences and informatics differ from traditional library and information science. Findings – Data science and informatics, as emerging fields, are expanding our understanding of how the massive amount of information currently being generated can be collected, managed and used. While these may not be traditional “library” problems, the contributions of the library and information science communities are critical to help address aspects of these issues. Originality/value – The emerging fields of data science and informatics have not been extensively explored from the perspective of the information professional. This paper is designed to help information professionals better understand some of the implications of data science in a changing information environment.

Scientometric Analysis of Library and Information Science Articles During the Year 2008-2017 Using Web of Science

2019 ◽  
Vol 9 (S1) ◽  
pp. 12-15
Author(s):  
P. Boopathi ◽  
P. Gomathi
Keyword(s):  
Research Productivity ◽  
Analytical Study ◽  
Information Science ◽  
Web Of Science ◽  
Research Process ◽  
Library Science ◽  
Library And Information Science ◽  
Scientometric Analysis ◽  
Academic World ◽  
The Web

This article highlights the research productivity and scholarly communication of library and information science articles during the year 2008–2017 indexed by the Web of Science database. This analytical study consisting of 56 reports and data downloaded from the Web of Science (Clarivate Analysis) database. Scientometric research mainly focused on the range of research productivity in the field of library science in a specific period. To evaluate the Publication years, to identify the authors who wrote, the more articles, which journals published most of the relevant subject articles, which institute and country have mostly involved in a particular subject; all these are to mainly discussed in this study. The present study considered as a useful tool for effective allocation of research funds in the research community and the academic world of library and information science to enhance the research process.

The structure of an innovation ecosystem: foundations for future research

2020 ◽  
Vol 58 (12) ◽  
pp. 2725-2742 ◽  
Author(s):  
Tomás Dias Sant´Ana ◽  
Paulo Henrique de Souza Bermejo ◽  
Marina Fiqueiredo Moreira ◽  
Wagner Vilas Boas de Souza
Keyword(s):  
Systematic Review ◽  
Content Analysis ◽  
Web Of Science ◽  
Future Research ◽  
Ecosystem Structure ◽  
Innovation Ecosystem ◽  
Content Type ◽  
Innovation Ecosystems ◽  
Triple Layer ◽  
The Web

PurposeThe concept of an innovation ecosystem, based on the idea of business ecosystem, has increasingly grown in the literature on strategy, innovation, and entrepreneurship. However, not all innovation ecosystems have the same architectural models or internal collaboration, and existing research rarely deconstructs an ecosystem of innovation and examines its structure. The objective of this article is to systematize the discussion about the structure of an innovation ecosystem and offer a foundation for future research.Design/methodology/approachUsing the Web of Science database as the source for the articles, this paper presents a systematic review of the literature on the structure of the innovation ecosystems. The period of analysis spanned from January 1993 to August 2019. Two methods, bibliometric analysis and content analysis, were used to structure the systematic review.FindingsThe results of the content analysis showed that the main classifications related to the structure of an innovation ecosystem are the ecosystem life cycle (birth, expansion, leadership, and self-renewal), the classification according to the ecosystem level (macroscopic, medium, and microscopic), and the layered structure (core–periphery structure, triple-layer structure, triple-layer core–periphery structure, and framework 6C). The results also showed that studies in the field are concentrated around a small group of authors, and few studies have discussed the structure of an ecosystem.Research limitations/implicationsThis study includes only peer-reviewed articles from the Web of Science database.Originality/valueThis article contributes to innovation ecosystem theory by exploring the characteristics that influence ecosystem structure. In addition to the theoretical contribution, the triple-layer core–periphery framework and the 6C framework set a benchmark for future research on innovation ecosystems.

Twinning data science with information science in schools of library and information science

2018 ◽  
Vol 74 (6) ◽  
pp. 1243-1257 ◽  
Author(s):  
Lin Wang
Keyword(s):  
Design Methodology ◽  
Data Science ◽  
Information Science ◽  
Mission Statement ◽  
Science Research ◽  
Library And Information Science ◽  
Data Quality Control ◽  
Control Data ◽  
Content Type ◽  
Quality Control Data

PurposeAs an emerging discipline, data science represents a vital new current of school of library and information science (LIS) education. However, it remains unclear how it relates to information science within LIS schools. The purpose of this paper is to clarify this issue.Design/methodology/approachMission statement and nature of both data science and information science are analyzed by reviewing existing work in the two disciplines and drawing DIKW hierarchy. It looks at the ways in which information science theories bring new insights and shed new light on fundamentals of data science.FindingsData science and information science are twin disciplines by nature. The mission, task and nature of data science are consistent with those of information science. They greatly overlap and share similar concerns. Furthermore, they can complement each other. LIS school should integrate both sciences and develop organizational ambidexterity. Information science can make unique contributions to data science research, including conception of data, data quality control, data librarianship and theory dualism. Document theory, as a promising direction of unified information science, should be introduced to data science to solve the disciplinary divide.Originality/valueThe results of this paper may contribute to the integration of data science and information science within LIS schools and iSchools. It has particular value for LIS school development and reform in the age of big data.

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