Latest trends in open science and big data analytical study: a decade of scientometric analysis
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This document presents a scientometric analysis focused on research trends in open science and big data analytics, emphasizing its importance in scientific evaluation and knowledge growth. Utilizing data from the Web of Science, the study investigates productivity, geographical distribution, and key institutions involved in this field over the period from 2009 to 2019. The findings highlight significant issues in data preservation and scholarly communication that accompany the rise of big data and open science initiatives.
![INTRODUCTION •Scientometrics has been
one of the most essential
methods for the
evaluation of scientific
findings. According to
[Lolis, 2009]
•Scientometric indicators have
become important to the
academic community in order
to assess and predict the trends
of a given area of research.
•Scientometrics
has a symbiosis
relationship with
Bibliometrics.
Bibliometric analysis
refers to mixture of
several frameworks,
tools and procedures
to study and analyze
citations of scholarly
publication [Hodonu-
Wusu, et al., 2018].
Scientometrics has
been used in life
sciences [Williams, etal.,
2019], Education [20],
Preventing Sciences
[21], Library Science
[22], [23] and [24], but
none has investigated
the trends of open
science and big data
analytics as a field.
As research system is spreading,
and the scientific landscapes are
changing toward openness. Open
Science is a movement that makes
repositories available online and
freely accessible via the internet
[Foster, 2015].
Big Data on the other hand, is
the explosion of large – scale
streaming data that is
beginning to change scientific
research topology which has
the potential to impact
researchers, their funders as
well as impacts the society on
the availability of the
information within their reach.
Today, new discoveries are
trending towards research
openness and researchers need
to be aware of this fact, and key
into the vision and mission of
open science initiatives which
among others is to provide
resources in order to boost the
growth of scientific knowledge.](https://image.slidesharecdn.com/latesttrendsinopenscienceandbigdataanalysiswusu-200206070233/85/Latest-trends-in-open-science-and-big-data-analytical-study-a-decade-of-scientometric-analysis-3-320.jpg)
![REFERENCES
[1] . Lewis, S. C., and Westlund, O. (2015). Big data and journalism. Epistemology, expertise, economics and ethics. Digital Journalism 3(3):
447-66. Doi:10.1080/21670811.2014.976418.
[2]. Parasie, S. (2015). Data –driven revolution? Epistemological tensions in investigative journalism in the age of “big data”. Digital
Journalism, 3(3). 364-80.
[3]. Ferreras-Rodriguez, E, M. (2012). Nuevos perfiles professionals: El periodista de datos. In Actas –IV conngreso International Latina de
Communicacion Social –IV CILCS –Universidad de La Laguna, Diciembre 2012, 1-19.
[4]. Kuipers, T., & Van der Hoeven, J. (2009). Insight into digital preservation of research output in Europe: Survey report (D3.4). Didcot, UK:
PARSE.Insight p.37. Retrieved from http://www.parse-insight.eu/downloads/PARSE-Insight_D3-SurveyReport_final_hq.pdf
[5]. Sclater, N (2017). Learning Analytics Explained. Routledge.
[6] Lolis, S. F. & et. al. (2009). Scientometric analysis of energetic ecology: Primary production of aquatic macrophytes. Maringá, 31 (4),
363-369.
[7]. Hodonu-Wusu., James Oluwaseyi., and Gift Nneka Lazarus. “Major Trends in LIS Research: A Bibliometric Analysis.” Library Philosophy
& Practice. (2018).
[8]. Mukhlif, Fadhil., James Oluwaseyi Hodonu-Wusu, Kamarul, Arinffin Bin Noordin, and Zarinah Mohd Kasirun. “Major trends in device to
device communications research: A bibliometric analysis.” In 2018 IEEE Student Conference on Research and Development (SCOReD),
pp.1-6. IEEE, 2018.
[9] Williams, Jason, J., Drew, Jennifer C, Pauley, Mark A. & etal., (2019). Barriers to integration of bioinformatics into undergraduate life
sciences education: A national study of US life sciences faculty uncover significant barriers to integrating bioinformatics into undergraduate
instruction. PLoS ONE 14(11):e0224288.
[10]. Riahi, Y., and Riahi, Sara (2018). Big data and Big Data Analytics: Concepts, Types and Technologies. International Journal of Research
and Engineering. Vol.5, No.9, pp- 524-528.](https://image.slidesharecdn.com/latesttrendsinopenscienceandbigdataanalysiswusu-200206070233/85/Latest-trends-in-open-science-and-big-data-analytical-study-a-decade-of-scientometric-analysis-20-320.jpg)
Latest trends in open science and big data analytical study: a decade of scientometric analysis
- 1. James Oluwaseyi Hodonu-Wusu, Olayiwola Taofeek Tokunbo, Peter Alaba, Lazarus, G. Nneka, Fadhil Mukhlif, Shapla, Khanam, & Hellen Auma Mbotela. 2nd February 2020 BY
- 2. PRESENTATIONOUTLINE 1. INTRODUCTION 2. OBJECTIVES 3. LITERATURE REVIEW 4. METHODOLOGY 5. SOFTWARE USED IN ANALYSING THE DATA 6. RESULTS & DISCUSSIONS 7. CONCLUSION 8. REFERENCES
- 3. INTRODUCTION •Scientometrics has been one of the most essential methods for the evaluation of scientific findings. According to [Lolis, 2009] •Scientometric indicators have become important to the academic community in order to assess and predict the trends of a given area of research. •Scientometrics has a symbiosis relationship with Bibliometrics. Bibliometric analysis refers to mixture of several frameworks, tools and procedures to study and analyze citations of scholarly publication [Hodonu- Wusu, et al., 2018]. Scientometrics has been used in life sciences [Williams, etal., 2019], Education [20], Preventing Sciences [21], Library Science [22], [23] and [24], but none has investigated the trends of open science and big data analytics as a field. As research system is spreading, and the scientific landscapes are changing toward openness. Open Science is a movement that makes repositories available online and freely accessible via the internet [Foster, 2015]. Big Data on the other hand, is the explosion of large – scale streaming data that is beginning to change scientific research topology which has the potential to impact researchers, their funders as well as impacts the society on the availability of the information within their reach. Today, new discoveries are trending towards research openness and researchers need to be aware of this fact, and key into the vision and mission of open science initiatives which among others is to provide resources in order to boost the growth of scientific knowledge.
- 4. • The aim of this paper is to present the research trends in respect to the productivity of researchers using Web of Science database, top authors in open science and big data analytical study, Geographical distribution on the topic, most productive research institutions, top journals on open science and big data, subject areas in the literature, publication year, document type, and funders agencies. RESEARCH OBJECTIVES LITERATURE REVIEW
- 5. Six Vs of Big Variety: Different types of data (structure and unstructured data) Veracity: degree of trusting the data Velocity : Speed at which data is generated Data Volume: Amount/Size of the data Value: Usefulness of the data collected Variability: Use and Reused of data Big Data Volume Variety Velocity Varacity Value Variability LITERATURE REVIEW CONT’D Dimension of Big Data Analytics Descriptive Big Data Analytics Diagnostics Big Data Analytics Predictive Big Data Analytics Prescriptive Big Data Analytics Types/Dimension of Big Data Analytics
- 6. BIG DATA ANALYTICS USES CASES Text Analysis e.g. Social Media Data Human Resources Analytics Customer Lifetime Value: Health Care Analytics Institutional/ Funders Analytics Open Government Analytics Lewis, 2015
- 7. The data was collected from the Web of Science Core Collection Consisting of: Methodology • The Social Sciences Citation Index “SSCI” • Science Citation Index Expanded “SCI EXPANDED” • Conference Proceeding Citation Index – Science “CPCI-S” • Conference Proceeding Citation Index – Social Science & Humanities “CPCI-SSH” • Arts & Humanities Citation Index – “A&HCI” • Emerging Sources Citation Index “ESCI” that comes From Standard and Acceptable articles and quality 2009-2019Duration • Boolean Search of Keywords ”OPEN SCIENCE,” “BIG DATA” “BIG DATA ANALYTICS” 664 ARTICLESRETURNS OF SEARCH
- 8. SOFTWARE USED IN ANALYSING THE DATA
- 9. SEARCH RESULTS ANALYZE RESULTS & CITATION REPORTS SOFTWARE USING FOR ANALYSING • Rstudio Software • Gephi
- 10. RESULTS & DISCUSSION • ANALYSIS BASED ON WEB OF SCIENCE CATEGORIES • ANALYSIS BASED ON KEYWORDS • ANALYSIS BASED ON AUTHORS • ANALYSIS BASED ON COUNTRIES • ANALYSIS BASED ON PUBLICATION TYPES AND YEARS • ANALYSIS BASED ON RESEARCH AREA • ANALYSIS BASED ON DOCUMENT TYPE • ANALYSIS BASED ON JOURNALS • ANALYSIS BY ORGANIZATION
- 13. ANALYSIS BASED ON MOST CITED AUTHORS AND YEAR
- 14. ANALYSIS BASED ON COUNTRIES
- 15. ANALYSIS BASED ON RESEARCH AREAS/YEAR OF PUBLICATION
- 16. ANALYSIS BASED ON DOCUMENT TYPE 0 50 100 150 200 250 300 350 400 450 ARTICLE PROCEEDINGS PAPER REVIEW BOOK CHAPTER EDITOTIAL MATERIAL EARLY ACCESS DATA PAPER BOOK CHAPTER MEETING ABSTRACT CORRECTION RETRACTED PUBLICATION RECORD COUNT % OF 664 DOCUMENT TYPE RECORD COUNT % OF 664 ARTICLE 375 56.732 PROCEEDINGS PAPER 192 29.047 REVIEW 76 11.498 BOOK CHAPTER 22 3.328 EDITOTIAL MATERIAL 20 3.026 EARLY ACCESS 9 1.362 DATA PAPER 4 0.605 BOOK CHAPTER 2 0.303 MEETING ABSTRACT 2 0.303 CORRECTION 1 0.155 RETRACTED PUBLICATION 1 0.155
- 19. CONCLUSION Top Research funders/Institutions are Chinese Academy, University of Cambridge, University of Winconsin, University Calif Berkeley, Indiana University etc Top Research disciplines/areas are in Computer Science Information Systems, Computer Science Theory Methods, Engineering, Electrical and Electronics among Others Most of the influential journals are PLoS ONE, SCIENTOMETRI CS, BIG DATA & SOCIETY, GIGASCIENCE. It was found out that the top three major problems of data are data preservation (data curation), which includes accountability for publicly funded research, inspiration for scientific advancements and reanalysis of previously generated data Due to the increase in digital interference which led the big data era, scholarly communication and data- driven researchers have become popular. This research is a first attempt to carry out a Scientometric study about Open Science and Big Data Analytics.
- 20. REFERENCES [1] . Lewis, S. C., and Westlund, O. (2015). Big data and journalism. Epistemology, expertise, economics and ethics. Digital Journalism 3(3): 447-66. Doi:10.1080/21670811.2014.976418. [2]. Parasie, S. (2015). Data –driven revolution? Epistemological tensions in investigative journalism in the age of “big data”. Digital Journalism, 3(3). 364-80. [3]. Ferreras-Rodriguez, E, M. (2012). Nuevos perfiles professionals: El periodista de datos. In Actas –IV conngreso International Latina de Communicacion Social –IV CILCS –Universidad de La Laguna, Diciembre 2012, 1-19. [4]. Kuipers, T., & Van der Hoeven, J. (2009). Insight into digital preservation of research output in Europe: Survey report (D3.4). Didcot, UK: PARSE.Insight p.37. Retrieved from http://www.parse-insight.eu/downloads/PARSE-Insight_D3-SurveyReport_final_hq.pdf [5]. Sclater, N (2017). Learning Analytics Explained. Routledge. [6] Lolis, S. F. & et. al. (2009). Scientometric analysis of energetic ecology: Primary production of aquatic macrophytes. Maringá, 31 (4), 363-369. [7]. Hodonu-Wusu., James Oluwaseyi., and Gift Nneka Lazarus. “Major Trends in LIS Research: A Bibliometric Analysis.” Library Philosophy & Practice. (2018). [8]. Mukhlif, Fadhil., James Oluwaseyi Hodonu-Wusu, Kamarul, Arinffin Bin Noordin, and Zarinah Mohd Kasirun. “Major trends in device to device communications research: A bibliometric analysis.” In 2018 IEEE Student Conference on Research and Development (SCOReD), pp.1-6. IEEE, 2018. [9] Williams, Jason, J., Drew, Jennifer C, Pauley, Mark A. & etal., (2019). Barriers to integration of bioinformatics into undergraduate life sciences education: A national study of US life sciences faculty uncover significant barriers to integrating bioinformatics into undergraduate instruction. PLoS ONE 14(11):e0224288. [10]. Riahi, Y., and Riahi, Sara (2018). Big data and Big Data Analytics: Concepts, Types and Technologies. International Journal of Research and Engineering. Vol.5, No.9, pp- 524-528.
- 21. This Photo by Unknown Author is licensed under CC BY TERIMA KASIH