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Impact of Open Science on Academic Libraries of Educational Institutions in
Rivers State
Ify Evangel Obim, Victor Wagwu & Eruchi Brown Akpelu
1Department of Library and Information Science,
University of Nigeria, Nsukka
ify.obim@unn.edu.ng
2Dame Patience GoodLuck Jonathan Automated Library, Ignatius Ajuru University of Education
Rumuorlumeni, Port-Harcourt, Rivers State, Nigeria
victor.wagwu@iaue.edu.ng
3Library Department, Pamo University of Medical Sciences, Rivers State
eakpelu@pums.edu.ng
Abstract
The study examined the impact of Open Science on academic libraries of educational institutions
in Rivers State. The study adopted a descriptive survey research design and was guided by three
objectives, three research questions and three hypotheses. The sample size of the study was one
hundred and five (105) librarians comprising of all librarians (practising & teaching staff) working
in five (5) academic institutions in Rivers State, Nigeria. A questionnaire and interview guide were
used to gather data. Data collected were analysed using descriptive statistics of arithmetic mean
(X) and standard deviation (SD) while the Pearson Product Moment Correlation was used to
test the hypotheses at 0.05 level of significance. The findings show that respondents accepted that
Open Science promotes transparency in experimental methodology, observation, and collection of
data (x
3.64 & ±.912). It enhances public availability, reproduction and reusability of scientific data
(x
3.92 & ±.981); Open Access Journals give permission to users to read, download, copy,
distribute, print, search, or link to the full texts of journal articles without financial, legal, or
technical barriers (x
3.92 & ±.991). The study recommended that there should be an
increase in acceptance and use of open sciences and open access resources in academic libraries.
Keywords: Open Science, Academic Libraries, Educational Institutions, Open Access, Nigeria
Introduction
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Library has remained an environment of learning and knowledge creation in every
academic institution. While this is so for centuries, the way its missions and objectives are met is
constantly evolving due to technological advancements in knowledge production, processing and
dissemination cycle. This shift has been accelerated over the past two decades by digital
technology and the changes it has brought about, to the point where evolution is beginning to
resemble a revolution. (Oberländer & Reimer, 2019). This revolution is the presence of big data;
open science and open access journals which are already having profound impacts not just in the
development of academic libraries alone but also in various educational institutions at large. This
is a result of the numerous technological tools that students and researchers utilize and the massive
amounts of data that are generated by them every single second. (Shorfuzzaman, Hossain, Nazir,
Muhammad, & Alamri, 2019).
Big data is an essential innovation component that has lately received a lot of attention
from academics and practitioners. In the realm of education, everything is data. Every action,
statement, and observation a person makes creates new data (Baig et al., 2020). Information was
sporadic and unrecorded for a substantial chunk of human history. Data could be saved for later
use, thanks to the discovery of writing, but it was a time-consuming procedure. The ability to
collect and analyze data has only recently really taken off as more and more aspects of daily life
are connected to computers and the Internet. Previously transient data is now being collected,
stored, and analyzed, often with shocking outcomes (Baig et al, 2020). The "petabyte age," often
known as "the era of large data," was previously mentioned by Anderson in Baig et al. (2020). Big
data in this context refers to a sizable amount of data with vast production and exponential growth
that cannot be processed or evaluated using conventional analytical techniques or kept in
conventional storage (Kiran, 2019). Big data has been categorized by Xu & Duan (2019) into the
three Vs of volume, variety, and velocity. The term "volume" is used to describe large or increasing
amounts of data. The variety of data refers to the type or heterogeneity of data. Structured (found
in databases) or unstructured (images, videos, emails) data formats are both possible. Velocity
describes how quickly big data is accessed. Volume, Velocity, Variety, Valence, Veracity,
Variability, and Value are the seven Vs of today replacing the original three Vs (Saggi & Jain,
2018).
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In a broader sense, open access and open science are related. To remove obstacles to the
sharing of scientific research output and raw data, "open science" is frequently defined as a
multifaceted concept encompassing open access to publications, open research data, open source
software, open collaboration, open peer review, open notebooks, open educational resources, open
monographs, citizen science, and research crowd funding (FOSTER in Tzanova, 2019). According
to the "open science" philosophy, all scientific discoveries should be openly given from the outset.
Study data, lab notes, and other research methods must be made publicly available under terms
that permit reusing, redistributing, and duplicating the research in order for others to join and
contribute. By altering the way information is created and shared within society, Open Science
seeks to address the issue of constraints. Open Access refers to making information accessible to
users and information searchers without any kind of restriction. To maintain the integrity of their
work and to ensure that they are properly credited and attributed, writers in open-access journals
are either given the option to keep their copyright or are asked to relinquish it to the publisher
(Ivwighreghweta & Onoriode, 2012).
The term "open access" is usually used to describe online publishing, however it is also
applicable to print publications for journals that also publish in print. Although open access does
not preclude paying for access to print editions of the same work, it does make reading the online
version of a work cost-free for readers (Ricardo & Mercè in Adeyokun, Adebowale & Yaya, 2015).
Ivwighreghweta & Onoriode (2012) assert that from the early 1990s, the open access movement
has freed libraries and information hubs all across the world. Librarians are more respected than
ever because of their contributions to the digital management of information, which was partly
threatened by commercial information providers in the Internet era (Swan & Chan, 2010). Some
authors have worried that making open access more widely available could lead to an increase in
plagiarism; nevertheless, open access actually serves to lower plagiarism and tackles issues with
journal cost, currency exchange, and the delay in receiving overseas subscription journals. Big
data, open science, and open access journals' availability will therefore improve access to research
outputs and encourage the creation of a culture of increased scientific education and literacy, which
in turn may directly affect the growth of academic libraries and educational institutions.
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Statement of the problem
Scholars and researchers have historically relied heavily on academic libraries to get access
to the necessary scientific and technology journal publications for their own research. As part of
the subscription model, libraries were required to purchase or obtain licenses for content on behalf
of their patrons before serving as gatekeepers to control access on behalf of the content owners.
Academic libraries are currently struggling to keep up with the rising costs of journal subscriptions
due to shrinking budgetary resources. Libraries are now moving beyond licensing and distribution
to facilitating and supporting (Panitch & Michalak, 2005) the publishing processes in order to
remain relevant to their user community. As a result of technological improvement and changes in
the ecology of scholarly communication, big data, open science, and open access journals have
been embraced to increase the exposure and accessibility of academic works without restrictions.
In addition, authors are urging universities all over the world to use big data technology and open
access platforms to increase the visibility, accessibility, and reach of their scholarly outputs both
inside and outside of institutional and governmental boundaries, according to Tapfuma & Hoskins
(2019). Academic libraries and educational institutions in this region of the world cannot be
ignored in this situation. This is owing to the widespread issue that many libraries might not be
aware of how this significant transition has affected the growth of academic libraries. Hence, the
study seeks to examine the impact of open science on academic libraries of educational institutions
in Rivers State in order fill the knowledge gap and add to the existing scholarly works.
Objectives
The objectives of the study are to:
1. Identify the impact of Big data on academic libraries of educational institutions in Rivers
State
2. Identify the impact of Open science on academic libraries of educational institutions in
Rivers State
3. Identify the impact of Open Access Journals on academic libraries of educational
institutions in Rivers State
Research Questions
1. What are the impacts of big data on academic libraries of educational institutions in Rivers
State?
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2. What are the impacts of Open science on academic libraries of educational institutions in
Rivers State?
3. What are the impacts of Open Access Journals on academic libraries of educational
institutions in Rivers State?
Hypothesis
HO1: Big data does not significantly impact on academic libraries of educational institutions
HO2: Open science does not significantly impact on academic libraries of educational institutions
HO3: Open access journals does not significantly impact on academic libraries of educational
institutions.
Review of related literature
Academic libraries have a long history of gathering data, analyzing it, and then putting it
all together to create library statistics. Because of computational techniques and the ease of data
collection provided by educational technology, big data studies are now feasible. Recent advances
in big data have sped up and simplified certain data collection procedures while also incorporating
libraries into complex data analysis (Chen et al., 2015). Many information specialists believe that
the full integration of the library with big data will advance both the library and its parent
institutions. Since 2012, the phrase "big data" has been used more frequently in media headlines,
advertisements, and academic journals across a variety of subject areas (Reinhalter & Wittman,
2014). Because of its numerous capacities, uses, and applications, which could result in unexpected
conclusions, big data is helpful in most fields of study (Hoy, 2014).
Big Data is prevalent in this new digital era, often known as the fourth industrial revolution,
yet the word has no precise definition. The phrase first appeared in the 1990s (Sriramoju, 2017).
Data that cannot be managed by conventional data management methods was how Laney defined
Big Data in 2001 (Laney, 2001). Theoretically, Dumbill defined big data as "data that is too large,
moves too quickly, or does not fit the structures of database designs; one must find another
approach to analyze it to derive advantage from it" (Dumbill in Garoufallo & Gaitanou, 2021).
(Dumbill in Garoufallo & Gaitanou, 2021). Consequently, it is data that is quickly, automatically,
and continually created.
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In Garoufallo & Gaitanou, De Mauro et al. provide a very intriguing definition of the phrase
"Big Data" (2021). Three types of "datafication" were used to split up big data: I intentionally
collected data, such as surveillance data, automated data, like data generated by devices, and
voluntarily provided data, like social network data. Big data sets may contain unstructured data
from sources such as email messages, images, and forum posts. The image below displays De
Mauro et al. definitions of "big data":
(Source: Extracted from Garoufallo & Gaitanou, 2021).
According to Saggi & Jain (2018), the concept of "big data" has evolved to include the seven Vs
of volume, velocity, variety, value, veracity, variability, and value. Volume refers to the enormous
volumes of data that social networking and e-commerce websites, as well as online training,
learning, and evaluation, regularly produce (Adegbija et al., 2012). New technologies will do the
difficult task of storing these data more effectively. The "big data velocity" dimension describes
the rate at which large amounts of data are produced, particularly how frequently data arrives and
when decisions must be made in response to it. For instance, Facebook produces 2.5 million pieces
of content per day, including 300 million photos and 2.7 billion likes, but Google already handles
more than 1.2 trillion inquiries annually (Mukherjee & Show, 2016). When it comes to data kinds,
formats, and semantic interpretation, variety frequently signifies variability. Papers, databases,
excel tables, images, films in countless formats, social networking sites, sensors, and satiates are
just a few of the tools and techniques used to create a wide range of data.
Big data are intimately related to educational data mining, structured and unstructured data,
and supervised and unsupervised learning, claim Esomonu et al (2019). Techniques, tools, and
research in educational data mining are used to automatically extract meaning from enormous
databases of data produced by or pertinent to people's learning activities (learning assessments) in
educational environments (Nithya et al, 2016). With the development of big data, the relevance of
the educational sector has not decreased. The amount of data in the field of education has increased
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substantially since the invention of the Internet, enabling academics to evaluate numerous topic
groups without necessarily relying on challenging measurement methodologies. In the past, study
and learning kits have been utilized to help students expand their understanding of psychology and
provide more helpful information (Winne, 2006). In the age of big data, which provides
educational academics with complete approaches to re-conceptualize research concerns and assess
educational data, technological technologies are employed to obtain pertinent data quickly and
reasonably inexpensively (Daniel, 2015).
Software technologies in education significantly contribute to big data, enhance learning,
and advance school reform, in accordance with the three philosophies of educational psychology:
"Learners construct knowledge (cognitive operations), learners are agents (the capacity to exercise
choices with regard to preferences), and data include randomness" (Winne, 2006). The
implementation of innovative teaching, learning, and assessment approaches at multiple
institutions, which is producing a ton of data, was motivated by the need for students to develop
21st century abilities. The information generated comprises electronic evaluation comments from
students, student term results, teacher-created formative test results, and performance test
indicators from classroom assessment techniques (Esomonu et al., 2019).
Thanks to the growth of big data, teachers may now assess students' academic performance
and learning patterns and provide timely feedback (Black & Wiliam, 2018). The prompt and
constructive feedback inspires and satisfies the students, which improves their performance
(Zheng & Bender, 2019). Academic data can be used by teachers to evaluate their pedagogy and
make changes in response to the needs and desires of their students. A variety of educational
websites have been created, and courses have been made accessible that are specifically catered to
the needs of different students (Holland, 2019). The application of technology and acquisition
could enhance the educational industry. Utilizing extensive administrative data could greatly
improve how many different educational difficulties are handled (Sorensen, 2018). Information
workers need to understand how big data may improve education in order to cut costs and improve
the educational system.
The "open science" school of thought holds that all scientific discoveries should be made
available to the public right away. When study data, lab notes, and other research procedures are
made publicly available with limits that allow reuse, redistribution, and replication of the research,
it is done in a way that encourages other people to collaborate and contribute. According to
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Burgelman et al. (2019), open science will increase science's effectiveness, dependability, and
openness to societal challenges. Furthermore, they asserted that the European Commission has
worked diligently and comprehensively to advance open science policy since its establishment,
covering each stage of the research cycle, from information exchange and publication to scientific
discovery and review. Thus, the idea of open science is not new, and several terms have been used
to characterize the development of scientific techniques, including "Science 2.0." (Burgelman et
al., 2015). The many approaches to the transition to open science that are currently in use are built
on the tradition of openness in research (Fecher et al., 2015). The European Commission coined
the term "open science" as a result of the public consultation on Science 2.0: Science in Transition
in 2014. (European Commission, 2015).
The following are the four primary goals of open science: Using web-based tools to
encourage interdisciplinary research 1. Openness in the observation, data collection, and
experimental procedures 2. Making scientific data accessible to the general public and usable. 3.
The openness and accountability of scientific communication (Gezelter, n.d.). According to Smith,
who has a similar perspective, open science must be connected to the openness of scientific
observations, techniques, data gathering, and access, as well as communication, cooperation, and
research instruments. The complete scientific process should be made available to potential
consumers, collaborators, and extenders of the work rather than restricting sharing of the practice
of research to the publishing of selected products (Smith, n.d.). The open scientific taxonomy is
shown below, however:
(Source: Extracted from www.fosteropenscience.eu )
Two benefits of open science include the ability to share knowledge, particularly publicly funded
knowledge, and the capability to use and re-use scientific research discoveries for new research and
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teaching objectives outside of higher education institutions. While open science has numerous
benefits, it also has certain drawbacks, many of which are tied to the funding of scientific research
in the private sector, where results are typically delayed from publication or public disclosure until
they can produce a profit for the entity that financed them.
In recent years, open access journals have developed a strong reputation because of their
capacity to connect with a larger prospective audience and so create the conditions for potentially
greater influence. Higher education institutions are increasingly substituting fee-based information
sources for open access resources for research and instruction (Vrana, 2014). As a result, more
people, both inside and outside the academic community, are learning about the open access effort
and the advantages it may have for their personal and professional lives. Due to the high yearly
membership costs for scientific journals, which are too expensive for many university libraries,
fee-based (paid) information resources have become one of the primary obstacles to the operation
of higher education institutions across the globe (Krishnamurthy, 2008). Students, teachers, and
researchers require access to information resources that are free, contain peer-reviewed material,
are simple to use, use common file formats, are compatible with a variety of electronic devices,
etc. The open access project gained popularity as a way to make it easier for people to access the
scientific information resources needed for research and teaching when financial conditions at
universities and academic libraries throughout the world deteriorated.
Open access to scientific information resources, such as journal articles, refers to their
accessibility to all users via the internet with no restrictions on how they may read, copy, distribute,
print, link to the full texts of these articles, crawl them for indexing, pass them as data to software,
or use them for any other lawful purpose (Sawant, 2013). According to definitions of "open
access," "access" includes not only basic freedoms like the ability to read, download, and print but
also the freedoms to copy, distribute, search, link, crawl, and mine, according to the European
Commission. In open access literature, which is digital, online, free, and digital, there are few
copyright and license restrictions. "The right of a reader of a scientific article to access it without
charge or restriction online, print it out, and distribute it further for non-commercial reasons" is
the definition of open access. All of these definitions strive to give the most thorough explanation
of open access in order to increase the public's and the scientific community's support of this
initiative (Björk, 2004). By virtue of Horizon 2020, open access to publications is already required.
Researchers must guarantee open access to their publications via the repository within six months
of publication, or twelve months in the case of the social sciences and humanities, and must deposit
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a copy of the published version or the final peer-reviewed manuscript there at the latest on
publication (Burgelman et al, 2019).
However, making scientific data and papers from peer-reviewed journals accessible is open
access' primary objective. A growing number of open access information sites offer educational
content that is freely accessible to the public with few or no limitations in addition to scientific
data. For open access to higher education to become more broadly recognized, this is necessary.
A few of the opportunities and advantages that open access provides the general public include the
lack of passwords or other forms of authentication, increased access to funding for academic
research for researchers who work both inside and outside of academia, and the assurance that
those who actually provide the funding for publicly-funded research are held accountable (Koutras
& Bottis, 2013). Researchers may benefit from open-access articles in the following ways: Anyone
may copy and distribute their writings as long as suitable citations are made because they are freely
available online. The authors still have the rights to their creations, nonetheless. The full text of
every open access article is permanently stored in a database separate from the journal,
guaranteeing that the broadest audience is accessible to it; the availability of articles will increase,
fostering literature research. All readers who are interested in the findings of publicly financed
research will have access to them, not just those who are members of libraries; the capacity of a
nation's scientists to publish publications is mostly unaffected by economic conditions (Burgelman
et al., 2019).
Methodology
The study evaluated the effects of big data, open science, and open access publications on
academic libraries of educational institutions in Rivers State. All librarians (teaching and
practicing personnel) employed by five academic institutions in Rivers State made up the study's
population (Rivers State University, Ignatius Ajuru University of Education, University of Port
Harcourt, Ken Sarowiwa Polytechnic, Bori and Captain Elechi Amadi Polytechnic). A purposeful
sample of 105 (one hundred and five) state librarians were chosen. Various points of view and
opinions were gathered using the questionnaire and interview methods. While the hypothesis was
examined using the Pearson product-moment correlation coefficient, the acquired data was
analyzed using the descriptive statistics of arithmetic mean (X) and standard deviation (SD).
Therefore, RQ1, 2, and 3 responses with mean scores over 2.5 were scored positively, while those
with mean scores below 2.5 were assessed negatively.
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Analysis and Discussions of Findings
Table 1: Impacts of Big data on the development of academic libraries and educational institutions
RQ1: What are the impacts of big data on development of academic libraries and educational
institutions in Rivers State?
Impacts of Big data and Academic library development
x
±
Decision
It promotes innovative services, teaching, learning and
strategic assessments in various academic libraries and
educational institutions
3.61
.932
Accept
It enhances immediate evaluation of users’ e-feedback in
academic libraries
3.03
.912
Accept
It helps to generate and store large amount of users’ data in a
readable format
3.92
.951
Accept
Big data helps to analyze the library pedagogy and effect
changes according to students’ needs and requirements
3.97
.998
Accept
It improves the speed of data access and retrieval in academic
libraries
3.99
.999
Accept
N=105, Decision rule: x
=2.50 and above is Significant
Table 1 above shows the impacts of big data on the development of academic libraries in Rivers
State. According to the respondents as represented in the table, all items in the table were
significant. This was based on the decision rule that “x
=2.50 and above is Significant”, therefore
the respondents accepted that Big data promotes innovative services, teaching, learning and
strategic assessments (x
3.61 & ±.932); enhances immediate evaluation of users’ e-feedback (x
3.03
& ±.951); It generates and stores large amount of users’ data in a readable format (x
3.92 & ±.932);
It helps to analyze library pedagogy and effect changes according to students’ needs and
requirements (x
3.97 & ±.998); and improves the speed of data access and retrieval in academic
libraries (x
3.99 & ±.999). This however, indicates that big data and its technologies however
greatly impacts on the development of academic libraries and their parent institutions at large,
With big data, librarians can now access, analyse, store, preserve student’s data and provide instant
e-feedback at a greater speed as identified by Black & Wiliam (2018) and Esomonu et al (2019).
It is also clear that many educational sites have been created for use in the library, and the data
generated from those sites are quite enormous and resulting to big data as they are constantly,
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automatically and rapidly generated. Hence, Librarians are expected to acquaint themselves with
big data knowledge and its impacts on developing and improving academic libraries and the
system of education in Rivers State.
Table 2: Impacts of Open Sciences on the development of academic libraries and educational
institutions
RQ2: What are the impacts of Open Sciences on the development of academic libraries and
educational institutions in Rivers State?
Impacts of Open Science and Academic library
development
x
±
Decision
It helps to make researches more efficient, reliable, and
responsive to societal challenges in various academic libraries
2.99
.792
Accept
It promotes transparency in experimental methodology,
observation, and collection of data in academic libraries
3.64
.912
Accept
It enhances public availability, reproduction and reusability of
scientific data in various academic institutions
3.92
.981
Accept
It encourages public accessibility and transparency of
scientific communication and collaboration without
restrictions
2.87
.798
Accept
It enhances scientific data visibility and curation in various
academic institutions
3.09
.899
Accept
N=105, Decision rule: x
=2.50 and above is Significant
Table 2 above shows the impacts of Open Science on the development of academic libraries in
Rivers State. According to the table, all items were significant. This was based on the decision rule
that “x
=2.50 and above is Significant”, therefore the respondents accepted that Open Science
promotes transparency in experimental methodology, observation, and collection of data (x
3.64 &
±.912); It enhances public availability, reproduction and reusability of scientific data (x
3.92 &
±.981); It enhances scientific data visibility and curation (x
3.09 & ±.899); makes researches more
efficient, reliable, and responsive to societal challenges (x
2.99 & ±.792); and encourages public
accessibility and transparency of scientific communication and collaboration without restrictions
(x
2.87 & ±.798). This finding is in corroboration with an earlier study of Burgelman et al (2019).
They emphasized that materials of all kinds should be openly available both at its discovery
process and use. The sciences in educational works should be organized so that other people can
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collaborate and contribute, with conditions that allow reuse, redistribution, and free reproduction
of the research. Openly disseminated scientific data, however, improves data accessibility,
visibility, and utilization, hence growing and effectively advancing bodies of knowledge. As a
result, there is a huge need for academic libraries to embrace an open scientific strategy given the
great impact of open sciences on the development of academic libraries and academic institutions.
Table 3: Impacts of Open Access Journals on the development of academic libraries and
educational institutions
RQ2: What are the impacts of Open Access Journals on the development of academic libraries and
educational institutions in Rivers State?
Impacts of Open Access Journal and Academic library
development
x
±
Decision
It facilitates access and use of scholarly works for research
and teaching without restrictions in academic libraries
3.41
.832
Accept
It allows for increased user community consultation and
article adaptation for non-commercial uses in academic
libraries.
3.03
.912
Accept
It permits users to access full-text journal articles and read,
download, copy, share, print, search for, or link to them
without facing any financial, legal, or technological obstacles.
3.92
.991
Accept
It serves as alternative learning materials to Fee base
information resources in libraries
3.07
.898
Accept
It curtails the cost of researches and increases the quality
learning in academic institutions
3.89
.979
Accept
N=105, Decision rule: x
=2.50 and above is Significant
Table 3 above shows the impacts of Open Access Journal on the development of academic libraries
in Rivers State. As represented in the table, all items were significant based on the decision rule
that “x
=2.50 and above is Significant”. Hence, the respondents agreed that Open Access Journal
gives permission to users to read, download, copy, distribute, print, search, or link to the full texts
of journal articles without financial, legal, or technical barriers (x
3.92 & ±.991); It curtails the cost
of researches and increases the quality learning (x
3.89 & ±.979); It facilitates access and use of
scholarly works for teaching and learning without restrictions (x
3.41 & ±.832); It serves as
alternative learning materials to Fee base information resources in libraries (x
3.07 & ±.898); and
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gives room for wider consultation and adaptation of articles by a community of users for non-
commercial purposes (x
3.03 & ±.912). This however indicates that open access journal is currently
gaining its premises for greater impact on the advancement of academic libraries in every academic
institution as a result of its extensive used in teaching, learning and researches in higher education
institutions as an alternative for fee-based information resources. Hence, scholars (Sawant, 2013;
Burgelman et al, 2019) are advocating for open access initiative where there is no passwords
requirement or other forms of authentication to journal articles and ensuring that those who need
them have greater access free or charge.
Table 4: HO: There is no significant impact between Big Data; Open Sciences; Open-
Access Journals and development of academic libraries and educational institutions in Rivers State
Table 4: Pearson correlation of Big Data; Open Sciences; Open-Access Journals and
the development of academic libraries and educational institutions
SN
Variable
N
Mean
Std. Dev
r
Df
Sig
Remark
HO1
Big Data
105
12.01
4.64
0.942
104
0.000*
Significant
HO2
Open Sciences
105
11.13
4.56
0.814
104
0.000*
Significant
HO2
Open-Access Journal
105
12.08
4.85
0.953
104
0.000*
Significant
*Significant at p < .05
It is assumed that there is no significant impact between Big Data; Open Sciences; Open-Access
Journals and development of academic libraries and educational institutions in Rivers State. The
study attempted to find out the strength of this assumption. It was found, as presented in table
4(HO1) that there is a strong relationship between Big Data and development of academic libraries
and educational institutions significant at (r-0.942; p<.05); The result in table 4(HO2) also shows
there is a positive relationship between Open Sciences and development of academic libraries and
educational institutions significant at (r=0.814; p<.05); and in table 4(HO3), the result also shows
there is a positive relationship between Open-Access Journals and development of academic
libraries and educational institutions significant at (r=0.953; p<.05). Hence, HO 1, 2 & 3 that was
assumed that there is no significant impact between Big Data; Open Sciences; Open-Access
Journals and development of academic libraries and educational institutions in Rivers State is
hereby rejected. Therefore, Big Data; Open Sciences; Open-Access Journals significantly impact
on the development of academic libraries and educational institutions in Rivers State.
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Summary of findings
The study does note, however, that the development of academic libraries and educational
institutions in Rivers State is profoundly impacted by big data, open sciences, and open-access
journals. The main benefits of big data include the following: the promotion of novel services,
instruction, learning, and strategic assessments; the immediate evaluation of user e-feedback; the
generation and storage of significant amounts of user data in a readable format; and an increase in
the speed of data access and retrieval. On the other hand, open science promotes open public
communication and collaboration in science without boundaries. It also promotes transparency in
experimental methodology, observation, and data collection; improves public availability,
reproduction, and reusability of scientific data; and enhances scientific data visibility and curation.
Additionally, open access journals remove barriers to accessing scholarly works for teaching and
learning and allow users to read, copy, distribute, print, search, or link to the full texts of journal
articles without incurring any costs or facing any legal, technical, or financial repercussions. They
also offer an alternative source of educational materials to libraries' fee-based information
resources and lower the cost of research while improving learning quality.
Conclusion and Recommendations
In conclusion, it is impossible to overstate the influence of big data, open sciences, and
open access journals on the growth of academic libraries and educational institutions. They are
essential for almost all activities in academic institutions because numerous new digital forms of
knowledge have emerged and academic publishers and libraries have started corresponding with
one another about the most important factors that would enable academic institutions, researchers,
and students to publish, access, and use a wide range of educational content without so many
financial and legal restrictions, or with as few restrictions as possible.
The report urges academic institutions to adopt and employ big data, open sciences, and open
access resources more widely. There should also be ongoing training and campaigning to increase
librarians' awareness of the many effects of big data, open research, and open access publications
in academic institutions as well as implementing the open science policy which was launched by
the Federal Government of Nigeria in 2017 in all our academic institutions.
16
REFERENCES
Adegbija, M.V., Fakomogbon, M.A. & Daramola, F.O. (2012). The new technologies and the
conduct of e-examinations: A case study of National Open University of Nigeria. British
Journal of Science, 3(59), 34-47.
Adeyokun, B.O., Adebowale, T.O., & Yaya, J. A. (2015). The prospects and challenges of open
access educational resources (OAER) in the library retrieval system. Asian Journal of
Education and e-Learning, 3(4), 234-241.
Baig, M.I., Shuib, L., & Yadegaridehkordi, E. (2020). Big data in education: a state of the art,
limitations, and future research directions. International Journal of Educational
Technology in Higher Education, 17(44), 1-23. https://doi.org/10.1186/s41239-020-
00223-0
Björk, B.C. (2004). Open access to scientific publications - an analysis of the barriers to change?
Information research, 9(2), http://www.informationr.net/ir/9-2/paper170.html
Black, P., & Wiliam, D. (2018). Classroom assessment and pedagogy. Assessment in Education:
Principles, Policy & Practice, 25(6), 551–575.
https://doi.org/10.1080/0969594X.2018.1441807
Burgelman, J., Pascu, C., Szkuta, K., Schomberg. R.V., Karalopoulos, A., Repanas, K., &
Schouppe, M. (2019). Open Science, Open Data, and Open Scholarship: European Policies
to Make Science Fit for the Twenty-First Century. Frontiers in Big Data, 2(43), 1-6.
Https//doi: 10.3389/fdata.2019.00043
Chen, H. (2015). Library Assessment and Data Analytics in the Big Data Era: Practice and Policies
[Proceedings of the 78th ASIST Annual Meeting]. St. Louis, Missouri, 1–4.
Daniel, B. (2015). Big data and analytics in higher education: opportunities and challenges. Br. J.
Educ. Technol., 46, 904–920. https://doi.org/10.1111/bjet
De Mauro, A., Greco, M., & Grimaldi, M. (2016). A Formal Definition of Big Data Based on Its
Essential Features. Library Review, 65(3), 122–35.
Esomonu, N.P., Esomonu, M.N., & Eleje, L.I. (2019). Assessment big data in Nigeria:
Identification, generation and processing in the opinion of the experts. International
Journal of Evaluation and Research in Education (IJERE), 9(2), 345-351.
European Commission (2015). Validation of the Results of the Public Consultation on Science
2.0: Science in Transition [EUROPA]. http://ec.europa.eu/ research/consultations/science-
2.0/science_2_0_final_report.pdf
Fecher, B., Friesike, S., & Hebing, M. (2015). What drives academic data sharing? [PLoS ONE]
Doi: 10.1371/journal.pone.0118053
Garoufallo, E. & Gaitanou, P. (2021). Big Data: Opportunities and challenges in libraries, a
systematic literature review. Association of College and Research Libraries, 82(3), 32-45.
Gezelter, D. (2009). What, exactly, is Open Science? [OPENSCIENCE].
http://www.openscience.org/blog/?p=269
17
Holland, A. A. (2019). Effective principles of informal online learning design: A theory-building
metasynthesis of qualitative research. Computers & Education, 128, 214–226.
https://doi.org/10.1016/j.compedu.2018.09.026
Hoy, M.B. (2014). Big Data: An Introduction for Librarians. Medical Reference Services
Quarterly 33(3), 320–26.
Ivwighreghweta, O. & Onoriode, O. K. (2012).Use of Open Access Journals by Lecturers at
Western Delta University, Oghara, Nigeria. Library Philosophy and Practice.
http://unllib.unl.edu/LPP/
Kiran, R. (2019). What are the Characteristics of Big Data? 5V’s, Types, Benefits [EDUREKA].
https://www.edureka.co/blog/big-data-characteristics/
Koutras, N. & Bottis, M. (2013). Institutional repositories of open access: a paradigm of innovation
and changing in educational policies. Procedia - Social and behavioral sciences, 106,
1499-1504.
Krishnamurthy, M. (2008). Open access, open source and digital libraries: A current trend in
university libraries around the world. Electronic library and information systems, 42(1),
48-55.
Laney, D. (2001). 3-D Data Management: Controlling Data Volume, Velocity and Variety. META
Research Note
Mayer-Schönberger, V. (2016). Big data for cardiology: novel discovery? Eur. Heart J. 37, 996–
1001. https://doi.org/10.1093/eurheartj/ehv648
Mukherjee, S. & Show, R. (2016). Big data: Concepts, applications, challenges and future scope.
International Journal of Advanced Research in Computer and Communication
Engineering, 5(2), 66-74.
Nithya, P., Umamaheswari, B., & Umaderi, A. (2016). A survey on educational data mining in
field of education. International Journal of Advance Research in Computer Engineering
and Technology (IJARCET), 5(1), 69-78, 2016.
Oberländer, A. & Reimer, T. (2019). Open Access and the Library. Publications,7(3),
http://www.mdpi.com/journal/publications
Panitch, J. M., & Michalak, S. (2005). The serials crisis: A white paper for the UNC-Chapel Hill
Scholarly Communications Convocation [UNC].
http://www.unc.edu/scholcomdig/whitepapers/panitch-michalak.htm
Reinhalter, L. & Wittman, R.J. (2014). The Library: Big Data’s Boomtown. Serials Librarian:
From the Printed Page to the Digital Age, 67(4), 363–72.
Saggi, M. K., & Jain, S. (2018). A survey towards an integration of big data analytics to big insights
for value-creation. Information Processing & Management, 54(5), 758–790.
https://doi.org/10.1016/j.ipm.2018.01.010
Sawant, S. (2013). Open access resources useful in LIS educatio. Library Hi Tech News, 30(7),
16-20.
18
Shorfuzzaman, M., Hossain, M. S., Nazir, A., Muhammad, G., & Alamri, A. (2019). Harnessing
the power of big data analytics in the cloud to support learning analytics in mobile learning
environment. Computers in Human Behavior, 92(1), 578–588.
https://doi.org/10.1016/j.chb.2018.07.002
Smith, K. (2010). What is Open Science? [LIBRARY].
http://blogs.library.duke.edu/scholcomm/2010/09/13/what-is-open-science/
Sorensen, L. C. (2018). Big data in educational administration: An application for predicting
school dropout risk. Educational Administration Quarterly, 45(1), 1–93.
https://doi.org/10.1177/0013161x18799439
Sriramoju, S.B. (2017). Introduction to Big Data: Infrastructure and Networking Considerations.
Horizon Books.
Swan,S. & Chan, A. (2010). Open access for librarians in developing countries.
http://76.12.54.203/work/openaccess/access/open20%access/introduction
Tapfuma, M.M. & Hoskins, R.G. (2019). Open science disrupting the status quo in academic
libraries: A perspective of Zimbabwe. The Journal of Academic Librarianship, 45, 406-
412. https://www.elsevier.com/locate/jacalib
Tzanova, S. (2019). Changes in academic libraries in the era of Open Science. Education for
Information, 1, 1–19. https://doi/10.3233/EFI-190259
Vrana, R. (2014). Access to digital information resources as a support to academic achievement
[Presented at Central European Conference on Information and Intelligent Systems].
Faculty of Organization and Informatics, University of Zagreb.
Winne, P. H. (2006). How software technologies can improve research on learning and bolster
school reform. Educ. Psychol, 41, 5–17. https://doi:10.1207/s15326985ep4101_3
Xu, L. D., & Duan, L. (2019). Big data for cyber physical systems in industry 4.0: A survey.
Enterprise Information Systems, 13(2), 148–169.
https://doi.org/10.1080/17517575.2018.1442934
Zheng, M., & Bender, D. (2019). Evaluating outcomes of computer-based classroom testing:
Student acceptance and impact on learning and exam performance. Medical Teacher,
41(1), 75–82. https://doi.org/10.1080/0142159X.2018.1441984
