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2 October 2023

Towards Data Storage, Scalability, and Availability in Blockchain Systems: A Bibliometric Analysis

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1
School of Computer Engineering, Kalinga Institute of Industrial Technology Deemed to Be University, Bhubaneswar 751024, India
2
School of Computer Applications, Kalinga Institute of Industrial Technology Deemed to Be University, Bhubaneswar 751024, India
3
Department of CSE, C.V. Raman Global University, Bhubaneswar 752054, India
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Author to whom correspondence should be addressed.
Data2023, 8(10), 148;https://doi.org/10.3390/data8100148
This article belongs to the Special Issue Blockchain Applications in Data Management and Governance
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Abstract

In recent years, blockchain research has drawn attention from all across the world. It is a decentralized competence that is spread out and uncertain. Several nations and scholars have already successfully applied blockchain in numerous arenas. Blockchain is essential in delicate situations because it secures data and keeps it from being altered or forged. In addition, the market’s increased demand for data is driving demand for data scaling across all industries. Researchers from many nations have used blockchain in various sectors over time, thus bringing extreme focus to this newly escalating blockchain domain. Every research project begins with in-depth knowledge about the working domain, and new interest information about blockchain is quite scattered. This study analyzes academic literature on blockchain technology, emphasizing three key aspects: blockchain storage, scalability, and availability. These are critical areas within the broader field of blockchain technology. This study employs CiteSpace and VOSviewer to understand the current state of research in these areas comprehensively. These are bibliometric analysis tools commonly used in academic research to examine patterns and relationships within scientific literature. Thus, to visualize a way to store data with scalability and availability while keeping the security of the blockchain in sync, the required research has been performed on the storage, scalability, and availability of data in the blockchain environment. The ultimate goal is to contribute to developing secure and efficient data storage solutions within blockchain technology.

1. Introduction

Blockchain, the new emerging technology, has captivated the interest of many researchers. It is a technology that can solve many different issues of security, safety, storage, confidentiality, and accessibility within diverse sectors of medicine, land, finance, IoT, etc., [1]. This technology has proved itself in the health sector which is one of the most concerned sectors. It helps maintain patient information confidentiality while providing secure access to required authorities. A blockchain with IoT can take technology use to another level. Blockchain is a digitally distributed database that stores data electronically in blocks linked together by cryptography (a method of protecting information and communication through code) [2]. The blocks are repositories of information having specific storage capacities. These blocks maintain a chronology in the chain by adding each fresh bit of knowledge that arrives after a newly added block in that block. When the block is filled, it is then sealed and joined to the block that came before it to complete the chain of data on the blockchain network [3,4,5].
Blockchains are also known as distributed ledger technology (DLT) because they function as immutable ledgers or transaction records that cannot be edited, erased, or annihilated. This infrastructure allows concurrent access, validation, and record updating across a distributed and connected database [6,7,8,9]. A network of nodes maintains the ledgers, each with a copy of the ledger, verifies the data, and aids in establishing consensus. All blockchains are distributed ledgers, but all distributed ledgers are not blockchains. Although it is simple to read the records and add fresh data to the chain of transactions, every fresh transaction must pass numerous security checks before being put in the blockchain. Nobody can alter or delete existing data. Any effort to interfere with the ledger may be easily tracked back to the prospective hacker, who normally loses network access. Blockchains manage a large-scale record of transactions and data protected by various security levels. As a result, these systems are often considered to be reliable and secure. The most common utilization of blockchains is in cryptocurrency systems such as Bitcoin, which have a significant function as decentralized blockchains [10]. In this case, the control is shared by all users, not just a select few. Every transaction leaves a permanent record accessible, making the data entered into the system irreversible.
There are two types of individuals involved in processing a blockchain transaction; one is the user, while the other is the miner or validator. Users are regular people who want to initiate a trade through blockchain. Miners or validators are people who validate or verify the authenticity of the incoming transaction of the blockchain system. Every transaction is first initiated by a user and broadcasted to all the computers in a network that operates on a peer-to-peer basis [11]. These computers are known as nodes. Further, the transaction is sent to wait in the memory pool in the pending state. This is where the miners come into play. The miners or validators verify the transactions by checking them against some transaction rules established by the network’s designers on each computer. Every fresh block must be validated by a specified number of validator nodes, achieving a consensus and creating a new token to correspond with the newly minted data block. They are rewarded for doing so by the gas fees paid by the user during the initiation of the transaction. After being validated, transactions are kept in locked blocks (hash). The permanent history is then created by connecting these blocks together. As a result, the transaction is concluded [12].
As a new technology, it has some parts that can be improvised to exponentially increase the use of blockchain in the future. These aspects are mainly blockchain storage, scalability, and availability. Many researchers have considered blockchain a new technology, including its storage, scalability, and availability as a scope [13].
Blockchain technology provides a solid data storage foundation. Unlike a traditional centralized server controlled by a single entity, blockchain data storage offers a technique that breaks data into pieces and distributes it over multiple cloud-based storage devices. As a result, a robust blockchain-based data storage system is being developed. In short, using blockchain as data storage makes it easier to transfer files without having to bounce requests all over the network to only a few data centers. Data duplication among nodes causes storage issues, worsening as networks expand. As a result, there are issues with availability, performance, and scalability. One of the most frequently brought-up difficulties facing blockchains today is storage [14].
Scalability in blockchain is the capability of any object to handle increasing numbers of data. It refers to handling increasing transactions and network nodes in a blockchain network. Scaling options are nonexistent due to the capacity investments made in security and decentralization. As a result, blockchains experience slow throughput and lengthy queues. The problem of scalability has been introduced previously. Since then, developers have developed scaling solutions to increase transactional speed [15,16]. The leading cause of this scalability problem is that all the participants in the blockchain must concurrently agree to the validity of a transaction.
Dependability properties, like availability, are critical for many applications, but the guarantees offered by blockchain technology still need to be clarified, especially from an application perspective. We demonstrate that while the read availability of blockchains is typically high, write availability—for transaction management—is low. One of the hottest topics of recent times, blockchain has a lot of scope for future expansion and improvement, including its storage, scalability, and availability. Many researchers from around the world have already been working on it to improve this new rising technology. A bibliometric study is necessary to understand the interest and progress in blockchain scalability, storage, and availability in recent years.
The bibliometric analysis is the quantitative study of research papers, books, and articles to give the researcher a clear idea and understanding of the research topic. This technology is recently being used in many fields for this purpose. Bibliometric analysis is a valuable research methodology for gaining insights into the evolving field of blockchain technology. This quantitative approach allows researchers to examine academic publications’ growth, impact, and interconnections in the blockchain domain. Tools like CiteSpace and VOSviewer enable researchers to visualize patterns, identify influential papers, and map the intellectual structure of blockchain research. This helps to draw a clear picture of the topic’s current status and allows the researcher to identify the direction of further investigation. This paper uses VOSviewer to plot the graphs for conducting detailed research on blockchain and its scalability, storage, and availability. Thus, it provides some clear directions for future research.

1.1. Research Questions

RQ1: Which authors actively participate in blockchain research and which country or institution do they belong to?
The answer to this question would provide researchers with the scope of collaboration with other researchers and professionals interested in this field. It may help them find answers to some of their deep questions by connecting with researchers or exploring other articles or papers under the same domain.
RQ2: What are the most discussed blockchain topics in recent years?
Answering this question would help researchers narrow their research direction by understanding the future scope and demand in the field.
RQ3: What recent trends and categories have emerged in this field during these years?
Answers to this question will give researchers insight into the prioritized trends and status of the research in this field.
RQ4: Which journals are cited the most in these recent blockchain publications?
Knowing the answer will help researchers narrow the search for accurate journals in this field.
RQ5: Which journals are cited highly as per the citation number?
This answer will help researchers know about particular papers and give further insights about countries and institutes that have been dedicated to this field of research.

1.2. Contributions

The current research paper is organized with the following contributions, which are as follows:
i.
It performs a systematic review to investigate the research trend and the current state of the art on blockchain storage, scalability, and availability.
ii.
It presents the popular research subjects and emerging trends related to blockchain storage, scalability, and availability using VOSviewer and CiteSpace tools.
iii.
Finally, it provides an in-depth analysis of blockchain storage, scalability, and availability solutions through a wide range of graphs with comparison analysis of existing work.

1.3. Organizations

The structure for the rest of this paper is as follows: Section 2 explains the data extraction and the methods used in the present research. Section 3 outlines the related work on data storage, scalability, and availability in a blockchain environment. Section 4 offers the results and discussion. Section 5 provides the popular research subjects and emerging trends on various characteristics of data storage—scalability and availability in a blockchain environment. Section 6 discusses the comparison analysis of existing work along with the present work. Section 7 draws the summary and concluding remarks of the present research paper.

2. Data Extraction and Methods

2.1. Data Extraction

We used Dimensions.ai to collect many professional and scientific publications to comprehensively cover information about blockchain storage, scalability, and availability worldwide. Exported records from dimensions.ai included extensive and detailed data on publication year, author, institution, and source journal (complete records and cited references exported to text files). Dimensions.ai has the setting of search types like exclusive data, title, and abstract or DOI that helps researchers to know whether we want to extract only data on blockchain technology and storage separately or data on blockchain storage, scalability, and availability. The different sorts of searches mostly focused on keywords, titles, and abstracts to study correlation hypotheses and research material. Dimensions.ai produced 2002 valid papers for blockchain storage, 1298 for blockchain scalability, and 282 for blockchain availability research. The data was exported to the Dimensions.ai export center of the user account in the form of CSV (VOSViewer, Citespace) and RIS format. It was then downloaded from the export center of the user account. We also collected the analysis of publication output from the overview of the analytical view in Dimensions.ai.

2.2. Methods

CiteSpace, a popular tool created by Dr. Chen Chaomei, is written in Java. CiteSpace was used in this paper to create visual knowledge maps that included countries, institutions, authors, journals, keyword grouping, and reference citation bursts. Furthermore, Eck and Waltman’s VOSviewer is a powerful visualization tool. The co-occurrence network was loaded into VOSviewer for further examination. Some knowledge map classification techniques and parameters were used in the bibliometric analysis results which will be detailed in subsequent paragraphs. Furthermore, a node denoted an item (country, institution, journal, author, or keyword) and links characterized by co-citation or co-occurrence between these nodes.
The terms “blockchain storage”, “blockchain scalability”, and “blockchain availability” were chosen through preliminary study and comparison, and the retrieval publication period was set to run from 2012 to 2022, along with the top 10 researcher’s publications for blockchain storage, blockchain scalability, and blockchain availability.
To obtain the visualization maps of essential authors, co-cited authors, journals, nations, institutions, etc., we could insert the data into CiteSpace and pick the data we needed to input.

4. Results and Discussion

4.1. Analysis of Publication Outputs

Exploring the development phase, knowledge accumulation, and maturity of blockchain is made more accessible by the annual pattern of publishing activity that characterizes blockchain research. Table 4 presents the yearly research paper publications from 2012 to 2022. As presented in Figure 1a, the number of publications about blockchain storage was at an initial stage between 2012 and 2015, but there was a slight increase in the number of publications between 2016 and 2018, and it reached its peak in 2020. Later, the number of publications decreased slightly during 2021–2022. Similarly, in Figure 1b, the number of publications about blockchain scalability is at an initial stage between 2012 and 2015. Still, there was a slight increase in publications between 2016 and 2018, which peaked from 2012 to 2022. Moreover, in Figure 1c, the number of publications about blockchain availability was at an initial stage between 2012 and 2016. Still, there was a slight increase in the number of publications between 2017 and 2018, and it peaked in 2021. Later, the number of publications will decrease in 2022. In the present studies, we have taken the data source from Scopus database for the bibliometric analysis.
Table 4. Annual publication per year.
Figure 1. (a): Annual output of blockchain storage research per year; (b): Annual output of blockchain scalability research papers; (c): Annual output of blockchain availability research papers.

4.2. Analysis of Countries and Institutions

Table 5 had 406 publications with India having the highest number of publications in blockchain storage research. However, blockchain scalability had 225 publications, whereas India had the highest number of publications. Moreover, blockchain availability had 65 publications, whereas the United States had the highest number of publications.
Table 5. List of top 10 countries based on publications.
According to Table 6, the most productive institutions based on several publications were shown. Nirma University was found to be the most influential institution related to blockchain storage and blockchain scalability; however, the Federal University of Pernambuco was the most productive institution from a blockchain availability research perspective.
Table 6. List of top 10 institutions based on publications.
The country cooperation network of blockchain storage research is displayed in Figure 2a, blockchain scalability in Figure 2b, and blockchain availability in Figure 2c (parameter settings: year(s) per slice: 1; node type: country; pruning: pathfinder and pruning the merged network; top N per slice: 50; top N%: 10%), with the size of nodes denoting the number of articles that were published in each country. The more nodes there were, the more papers were published.
Figure 2. (a): Mapping of major countries involved in blockchain storage research; (b): Mapping of major countries involved in blockchain scalability research; (c): Mapping of major countries involved in blockchain availability research.
Several research institutions were substantially concentrated, as seen in Figure 3a–c, (factor settings: year(s) per slice: 1; node type: institution; pruning: pathfinder and pruning the merged network; top N per slice: 50; top N%: 10%). The visualization map of institutions/countries involved in blockchain storage, blockchain scalability, and blockchain availability research: Mapping of central countries involved in blockchain storage, blockchain scalability, and blockchain availability research; Mapping of institutions engaged in blockchain storage, blockchain scalability, and blockchain availability research (the table above lists the top 10 publishing institutions).
Figure 3. (a): Mapping of institutions involved in blockchain storage research; (b): Mapping of institutions involved in blockchain scalability research; (c): Mapping of institutions involved in blockchain availability research.

4.3. Analysis of Author Cooperative and Author Co-Citation Network

According to Table 7, related to blockchain storage, the most productive author was Salah Khaled, with 54 publications from Khalifa University of Science and Technology, UAE. The second most productive author was Tanwar Sudeep from Nirma University, India, with 47 publications. It was then preceded by Jayaramam Raja, Yaqoob Ibrar, Javaid Nadeem, Kumar Neeraj, Kanhere Salil, Omar Mohammed, and Jurdak Raja, and at the tenth position was Gupta Rajesh from Nirma University, India. The most productive author in blockchain scalability was Gupta Rajesh, with 25 publications from Nirma University, India. The second most productive author was Dorri Ali from the Queensland University of Technology, Australia, with 24 publications. It was then preceded by Kumari Aparna, Wang Yuyi, Tanwar Sudeep, Bhattacharya Pronaya, Kakkar Riya, and Xi, and at the tenth position was Decker Christian from Cornell University, United States. However, regarding blockchain availability, the most productive author was Park Jong Hyuk, with nine publications from Seoul National University of Science and Technology, South Korea. The second most productive author was Tauz Lev from the University of California, United States, with eight publications. It was then preceded by Dolecek Lara, Mitra Debarnab, Aloqaily Moayad, Guizani Mohsen, Mahmoud Mohamed, Maciel Paulo, Dantas Jamilson, and at the tenth position was Melo Carlos from the Federal University of Pernambuco, Brazil.
Table 7. List of top 10 most productive authors participating in blockchain storage, blockchain scalability, and blockchain availability research perspectives.
Based on extracted data for Figure 4a–c (parameter settings: year(s) per slice: 1; node type: author; pruning: pathfinder and pruning the merged network; top N per slice: 50; top N%: 10%) from 2012 to 2022, the topmost productive authors were found in the form of mapping. Each node includes the name of a specific author, and this diagram shows Salah Khaled as the most influential author related to blockchain storage research. Moreover, Gupta Rajesh is the most influential author of blockchain scalability research, and Guizani Mohsen is the most influential author of blockchain availability research.
Figure 4. (a): Mapping of prominent authors in blockchain storage research; (b): Mapping of prominent authors in blockchain scalability research; (c): Mapping of prominent authors in blockchain availability research.
Table 8 shows the most cited authors and their highly cited articles on blockchain storage, blockchain scalability, and blockchain availability for 2012–2022. In blockchain storage, the most cited author was Gupta Rajesh with 28 articles, and this author’s most highly cited article was in IEEE Systems Journal. Zhang Zijian was the second most cited author with 22 articles, and their highest cited article was in IEEE Transactions on Network Science and Engineering. It was preceded by Kumari Aparna, R. Hasan Haya, Dorri Ali, Tanwar Sudeep, Zhang Yan, O. Novo, Salah Khaled, and S. Wang. Moreover, in the top cited authors and their highly cited articles on blockchain scalability for 2012–2022, the most cited author was Kakkar Riya, with 13 articles, and this author’s most highly cited article was in IEEE Systems Journal. Decker Christian was the second most cited author with nine articles, and their highest cited article was in Lecture Notes in Computer Science. It was preceded by Gupta Rajesh, Dorri Ali, Kumari Aparna, Luu Loi, Croman Kyle, Liu Mengting, and Kang Jieng. However, in the top cited authors and their highly cited articles on blockchain availability for 2012–2022, the most cited author was Anonymous with ten articles, and this author’s most highly cited article was in IEEE Access. Dorri Ali was the second most cited author with six articles, and their highest cited article was in Journal for General Philosophy of Science. It was preceded by Garg Shiva Raj, Sharma Pradip Kumar, Hu Xiao-Yu, Ridhawi Ismaeel, Yuntao Mondal, Christidis Konstantiros, Baza Mohamed, and Aitzhan NZ.
Table 8. List of most cited authors and their highly cited articles on blockchain storage, blockchain scalability, and blockchain availability for 2012–2022.
In terms of the co-authorship analysis in Figure 5a–c, each node represents one author (parameter settings: year(s) per slice: 1; node type: cited author; pruning: pathfinder and pruning the merged network; top N per slice: 50; top N%: 10%). In the charts generated by CiteSpace, mapping showed the most co-cited authors related to blockchain storage as Tanwar Sudeep and Gupta Rajesh between 2012 to 2022, along with their journals as Computers and Industrial Engineering and 2022 IEEE Globecom Workshops (GC Wkshps). Mapping in blockchain scalability showed the most co-cited authors as Kakkar Riya and Gupta Rajesh between 2012 to 2022 along with their journals as IEEE Systems Journal and IET Communications. Mapping in blockchain availability showed the most co-cited authors as Anonymous and Dorri Ali between 2012 to 2022 along with their journals as IEEE Access and Journal for General Philosophy of Science.
Figure 5. (a): Mapping of co-cited authors contributing in blockchain storage; (b): Mapping of co-cited authors contributing in blockchain scalability; (c): Mapping of co-cited authors contributing in blockchain availability.

4.4. Analysis of Co-Citation of Journals

As per Table 9, the most productive journals in blockchain storage for 2012–2022 saw IEEE Access leading with 134 papers that covered 6.69% of papers. Future Generation Computer Systems, IEEE Internet of Things Journal, IEEE Transactions on Industrial Informatics, and Lecture Notes in Computer Science preceded it. Also, the most productive journals in blockchain scalability for 2012–2022 saw IEEE Access leading with 67 papers that covered a total of 5.16% of papers. It was preceded by the IEEE Internet of Things Journal, IEEE Transactions on Industrial Informatics, IEEE Network, and Lecture Notes in Computer Science. Here too, the most productive journals in blockchain availability for 2012–2022 saw IEEE Access leading with 23 papers that covered 8.15% of papers. It was preceded by Lecture Notes in Computer Science, IEEE Transactions on Industrial Informatics, IEEE Communications Magazine, and IEEE Transactions on Dependable and Secure Computing.
Table 9. List of top five productive journals in blockchain storage, blockchain scalability, and blockchain availability for 2012–2022.
The time zone perspective of the co-citation journals network is portrayed in Figure 6a–c (parameter settings: year(s) per slice: 1; node type: cited journal; pruning: pathfinder and pruning the merged network; top N per slice: 50; top N%: 10%). IEEE Access was the leading journal and preceded by Future Generation Computer Systems, IEEE Internet of Things Journal, IEEE Transactions on Industrial Informatics, and Lecture Notes in Computer Science in blockchain storage. IEEE Access was the leading journal preceded by IEEE Internet of Things Journal, IEEE Transactions on Industrial Informatics, IEEE Network, and Lecture Notes in Computer Science in blockchain scalability. IEEE Access was the leading journal preceded by Lecture Notes in Computer Science, IEEE Transactions on Industrial Informatics, IEEE Communications Magazine, and IEEE Transactions on Dependable and Secure Computing in blockchain availability.
Figure 6. (a): Co-citation journal time zone view in blockchain storage for 2012–2022; (b): Co-citation journal time zone view in blockchain scalability for 2012–2022; (c): Co-citation journal time zone view in blockchain availability for 2012–2022.

4.5. Analysis of Cited References

The method of burst detection is a powerful analytical tool that may be used to spot urgent situations or significant information within a given window of time. Figure 7 shows the top 30 strongest references identified by CiteSpace from 2012 to 2022 (parameter settings: year(s) per slice: 1; node type: reference; pruning: pathfinder; top N per slice: 50; top N%: 10%). In 2017, the largest citation burst strength, 4.87, came from a paper by Dorri Ali. The burst initiated in 2017 and completed in 2019. The author worked on the Proceedings of the Second International Conference on Internet-of-Things Design and Implementation. In 2018, the two largest citations burst strengths derived from the papers by Tschorsch Florian (7.67) and Christidis Konstantinos (7.21), respectively.
Figure 7. List of top 10 references with the strongest citation bursts.
As noticed, ten references were cited from 2017 to 2019. It was documented that the most extended citation period was two years, and the shortest was one year. It was surprising, however, to notice that all the papers were available after 2014, considering newly published studies tend to display citation burst analysis.
Table 10 lists the top ten reference articles in terms of citation frequency. Examining cited references helped academics understand the internal linkages between countries, organizations, and authors. Since blockchain research was quite mature and its application was broadened in 2018, the most widely referenced references were published in 2018. In the field of blockchain research, Khan Minhaj Ahmad’s article “IoT Security: Review, Blockchain Solutions, and Open Challenges” was a reference that was quoted rather frequently.
Table 10. List of top 10 citation references.

6. Comparative Analysis

In this section, the findings of the present bibliometric study are compared to the findings of earlier bibliometric analyses in order to offer information regarding the tools employed for both CiteSpace and VOSviewer, data storage, scalability, and availability of the blockchain system [67,68,69,70]. Recently, Sanka and Cheung [40] reviewed blockchain scalability challenges and solutions, analyzes research trends, and discusses adoption, serving as a guide for blockchain scalability research. Liu et al. [56] analyzes blockchain research from 2013 to 2020, highlighting key topics and trends. China leads in this field, focusing on computer science and engineering. Emerging areas include management, blockchain technology, energy, machine learning, and smart homes, with a call for regulatory standards. Firdaus et al. [71] analyzes blockchain research from 2013 to 2018, emphasizing its diverse applications in IoT and healthcare, top research countries, and its versatility beyond digital currency.
Guo et al. [72] presented the bibliometric analysis and visualization of blockchain and discussed in many areas. Further, Luo et al. [73] uses bibliometrics to analyze blockchain research evolution from 2014 to 2020. It highlights key contributors, like China, and reveals that blockchain research is expanding into various areas. Future directions include integrating blockchain with cloud tech, smart contracts, and authentication. Whereas Kuzior and Sira [74] focused on how Scopus-based bibliometric analysis of blockchain literature from 2007 to 2021 highlights the rapid growth in publications since 2016, China’s leading role in blockchain research, and shifting research priorities from Bitcoin to various blockchain applications. It also identifies three primary clusters of topics. Alam et al. [75] analyzes blockchain research from 2012–2020 using Web of Science data. Major findings include China and the USA as leaders in blockchain research, a focus on computer science, and a growing interest in blockchain research in Pakistan. It underscores blockchain’s multidisciplinary impact and the importance of global collaboration and language diversity in research.
In our research work, VOSviewer and CiteSpace were used for bibliometric analysis. We obtained the data in CSV and RIS formats from the Dimensions.ai database. From 2012 to 2022, the search includes blockchain storage, scalability, and availability, as well as the top ten authors of each search result. While extracting visualization maps from CiteSpace, we had to export the CSV data in the form of Web of Science data in the CiteSpace Java application, and all of the selection criteria for extracting visualization maps were given in the application, including author, institution, country, reference, cited author, journal, and so on. We utilized VOSviewer software for bibliometric networks, importing data from RIS files and selecting the method of visualization of bibliometric networks.

7. Conclusions

In conclusion, this paper represents a crucial bridge between theoretical insights and practical applications in the ever-evolving realm of blockchain technology. Throughout our research, we have meticulously examined the complex interplay of blockchain storage, scalability, and availability, shedding light on the current research landscape and the pressing challenges practitioners and researchers face.
Sia, Storj, and IPFS are some prominent companies that have launched their cryptocurrencies, like Siacoin, Storjcoin X, and Filecoin, to create a market for buying and selling decentralized storage and encouraging its use. In recent years, several trends have emerged, and innovations to enhance transaction throughput, reduce latency, and improve user experience can shape the future of blockchain scalability. Blockchain availability can provide the finance sector with a transparent ledger system that may eliminate the need for intermediaries and lower transfer costs.
Using bibliometric analysis tools, CiteSpace and VOSviewer, has allowed us to distill a wealth of academic literature into meaningful insights. By identifying the prevailing research priorities and mapping the intellectual structure of the field, we have contributed to theoretical advancements and provided actionable takeaways for real-world implementations. The practical significance of our work lies in its potential to guide and inform the development of blockchain-based solutions that seamlessly balance data storage, scalability, and availability while upholding the paramount importance of security. By visualizing pathways to achieve these objectives, we have opened doors for innovators, businesses, and policymakers to make informed decisions in the rapidly evolving blockchain landscape.
Using Dimensions.ai data from 2012 to 2022, this bibliometric study examined 2002 valid papers on blockchain storage, 1298 proper papers on blockchain scalability, and 282 valid papers on blockchain availability. Since 2016, the quantity of publications on blockchain storage and scalability has steadily expanded, while the number of publications has steadily grown since 2017 on blockchain availability. India held a conspicuous leadership position among all nations, according to the examination of national and institutional cooperation. At the same time, China, South Korea, UAE, Australia, and the United States accomplished worthwhile projects and made significant contributions. Most productive institutions were from India, making up the leading institutions in the study of blockchain storage, blockchain scalability, and blockchain availability. Nirma University was the most influential institution in this field.
According to the authors’ analysis, several authors tended to work with a limited group of colleagues, resulting in numerous prominent author groups, such as Gupta Rajesh and Kakkar Riya. The number of articles and citations found in the journal IEEE Access indicated that it was both an influential and productive publication, as stated by the co-citation journals network. In recent years, the IEEE Internet of Things Journal has attracted significant attention and encouraged the production of articles related to blockchain technology. Most journals focused on the IEEE Transactions on Industrial Informatics publication, attracting the most innovative academics and practitioners worldwide.
The research hotspots provided by VOSviewer have supplied specific information on the relevant literature. Conceptual knowledge and popular research subjects on blockchain were primarily distributed in the following categories: (a) intelligent contracts, (b) vehicle, (c) industry, and (d) proof. Further comprehension of conceptual knowledge and hot research themes is required, which will be a promising answer to different types of blockchain challenges. CiteSpace’s evolving trends and patterns have provided a fresh, engaging, and complete understanding of how to perform research subject searches. More emphasis should be placed on the potential of smart contracts and machine learning, which will be promising blockchain research fields. Overall, this study used CiteSpace and VOSviewer to understand blockchain research fields better and stay current with the blockchain sector.
While using CiteSpace, the limitations occur in the case of the amount of data being extracted because if we take data of only blockchain storage or scalability or availability, then the references with the most robust citation bursts might not be possible to extract due to a lack of data availability. While showing visualization maps, it might only be possible to show some countries, institutions, journals, primary authors, etc. Still, it is possible only to show the value of a single node and its nearby nodes. The analysis also varies concerning the g-index, as each insight becomes a different map when its value changes. However, it could be more accurate and thorough on how research is performed and publishing works. Therefore, all the limitations were reduced by taking the value of the g-index to be constant, leading us to obtain valid results.

Author Contributions

Conceptualization, M.K. and V.G.; writing—review and editing, V.G., R.K.B., and R.P.; Methodology, M.K. and R.K.B.; Software, M.K. and V.G.; Validation, R.K.B. and V.G.; Formal analysis, V.G. and R.P.; Resources, V.G. and R.K.B.; Visualization, M.K. and R.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The authors gratefully credit the Research Lab, School of Computer Applications, KIIT Deemed to be University, Bhubaneswar, India for providing computational resources.

Conflicts of Interest

The authors declare no conflict of interest.

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