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Introduction to Scopus and Web of Science

Scopus and Web of Science are the two largest interdisciplinary abstract and citation databases of peer-reviewed literature in the sciences.  They both contain 10s of thousands of articles, book chapters, and conference proceedings. 

Not everything contained in Scopus or Web of Science is full-text or comes from a scholarly publication. This guide will show you how to find full-text articles and how to identify the scholarly publications.

Scopus and Web of Science overlap a great deal in the publications they cover, but there are differences in their content.  If you are not finding what you want in one of the databases, try your search with the other.

Scopus and Web of Science are very similar in the way they function and how they direct you in your search for articles.  This guide will focus on searching for articles in Scopus, but the same method can be used when searching Web of Science. 

Finding Scopus and Web of Science

To use Scopus and Web of Science, you have to go to the University of Toronto Library's website.  You can access our webpage from www.library.utoronto.ca.

From the library page, go to Advanced Search and select "Databases".  Links to Scopus and Web of Science can be found at the bottom the "Popular Databases" page.

Start your Search

When you are starting your search, think of the terms you might use to locate articles of interest to you. 

NOTE:  The broader the search term, the more results you will get.  For instance, in the example shown below, if only the search term "economics" was used, over 60,000 articles would have appeared on the "document results" list.

Making your search more specific brings up a more manageable set of search results.  In this instance, using the search terms "economics" and "farming" directed Scopus to narrow down the search to articles dealing only with the economics of farming.

For the purposes of this assignment, it will serve you best to limit your search to the "Title, Abstract, Keyword" option.  This will instruct Scopus to look for your search terms in the title of the article, in the abstract of the article, and the in keywords of the article.  The abstract of the article is a short summary of what the article is about and the keywords are search terms connected to the article that are often supplied by the author.

Further Refining your Search

In this example, using the search terms "economics" and "farming" still resulted in almost 5,000 records. Scopus gives you options to further refine your search and narrow down the results.  For your purposes, you can further refine your search to years the articles were published (you might just want search through the 5 most recent years); subject areas to further focus your search on your area of interest; and/or document type to limit your results to articles only.

After Identifying an Article of Interest

Neither Scopus nor Web of Science will allow you to search for differential equations or integrals within an article, so when you have identified an article of interest you will have to skim the text of the article to see if it includes the math you need for this assignment.  You can only have access to the full-text of articles if you see the "full-text" button under the title of the article.  If the article you are looking at does not contain differential equations or integrals, you can access articles similar to the one you have chosen by clicking on the title of the article or clicking on the "related documents" link. 

References and Citations

When you click on the title of the article, you will be taken to a page that shows you the abstract and keywords of the article.  This page also features links to the articles that the author used for her/his own research (references) and articles published more recently that have used the paper as a reference (cited by).  If the article you have chosen does not have the necessary math within it, you might find what you are looking for by scanning the papers included in the references and cited by links.

Web of Science

Searching for articles in Web of Science is fundamentally the same as searching in Scopus.  Like Scopus, Web of Science allows you to limit your search results, retrieve full-text articles, and have access to "references" and "cited by" links. 

Note: There is difference in some of the terminology used by the two databases.  In Web of Science, " Topic " will perform the same search that " Title/Abstract/Keywords " performs in Scopus.

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A tale of two databases: the use of Web of Science and Scopus in academic papers

• Published: 22 February 2020
• Volume 123 , pages 321–335, ( 2020 )

Cite this article

• Junwen Zhu 1 &
• Weishu Liu   ORCID: orcid.org/0000-0001-8780-6709 2  

14k Accesses

517 Citations

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Web of Science and Scopus are two world-leading and competing citation databases. By using the Science Citation Index Expanded and Social Sciences Citation Index, this paper conducts a comparative, dynamic, and empirical study focusing on the use of Web of Science (WoS) and Scopus in academic papers published during 2004 and 2018. This brief communication reveals that although both Web of Science and Scopus are increasingly used in academic papers, Scopus as a new-comer is really challenging the dominating role of WoS. Researchers from more and more countries/regions and knowledge domains are involved in the use of these two databases. Even though the main producers of related papers are developed economies, some developing economies such as China, Brazil and Iran also act important roles but with different patterns in the use of these two databases. Both two databases are widely used in meta-analysis related studies especially for researchers in China. Health/medical science related domains and the traditional Information Science and Library Science field stand out in the use of citation databases.

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Comparison of self-citation patterns in WoS and Scopus databases based on national scientific production in Slovenia (1996–2020)

The journal coverage of web of science and scopus: a comparative analysis.

The journal coverage of Web of Science, Scopus and Dimensions: A comparative analysis

http://wokinfo.com/nextgenwebofscience?elq=4e2a3b0638fb400cae0565fc0e03a24e&elqCampaignId=8201 .

https://www.thomsonreuters.cn/zh/about-us/company-history.html .

The search strategy used in this study is a bit different to that used by Li et al. ( 2018 ), both these two search strategies may introduce a very small percentage of records which have only mentioned some regional citation indexes such as Chinese Social Sciences Citation Index.

Although Web of Science’s topic search (search in title, abstract, author keywords and keywords plus fields) is widely used in practice, the search in the keywords plus field may introduce some noise. Besides, records which only mention the data sources in the data and methods section will also be omitted in this study.

According to Wikipedia, Scopus also has some other meanings. This study excluded these ambiguous records manually.

Two records published in 2004 are related to Scopus, however, one of them is news item and another one is editorial material which are excluded from this study.

Echoing the finding of Liu et al. ( 2017 , 2018 ), a small percentage of country/region information omission is also identified. This study merges England, Scotland, Wales and North Ireland into the UK.

For information about meta-analysis, please refer to Gurevitch et al. ( 2018 ). A similar search method was also used by Guilera et al. ( 2013 ).

The decease of relative shares (columns: % within WoS/Scopus studies) in Information Science and Library Science is due to faster growth rates in some other categories where literature mentions WoS/Scopus.

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Lei, L., & Liu, D. (2019). The research trends and contributions of System’s publications over the past four decades (1973–2017): A bibliometric analysis. System, 80, 1–13. https://doi.org/10.1016/j.system.2018.10.003 .

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Liu, W. (2019). The data source of this study is Web of Science Core Collection? Not enough. Scientometrics , 121 (3), 1815–1824. https://doi.org/10.1007/s11192-019-03238-1 .

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Acknowledgements

This research is supported by the National Natural Science Foundation of China (#71801189 and #71904168) and Zhejiang Provincial Natural Science Foundation of China (#LQ18G030010 and #LQ18G010005). The authors would like to thank the referee for his/her insightful suggestions which have significantly improved the manuscript.

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School of Information Management and Engineering, Zhejiang University of Finance and Economics, Hangzhou, 310018, Zhejiang, China

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Correspondence to Weishu Liu .

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Zhu, J., Liu, W. A tale of two databases: the use of Web of Science and Scopus in academic papers. Scientometrics 123 , 321–335 (2020). https://doi.org/10.1007/s11192-020-03387-8

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Received : 14 September 2019

Published : 22 February 2020

Issue Date : April 2020

DOI : https://doi.org/10.1007/s11192-020-03387-8

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Using Web of Science to Find Highly Cited Articles

Open http://library.ucmerced.edu in another browser window to work through this tutorial side by side.

Introduction

Accessing web of science, key word searching in web of science, re-sorting results by times cited, use uc-elinks for full-text, evaluating seminal articles, vpn reminder.

UC MERCED LIBRARY TUTORIALS

This tutorial will show you how to find highly cited articles in Web of Science, a library database.

Use the right arrow at the bottom of this window to move through the tutorial.

When you’re doing a literature review, or trying to familiarize yourself with the most important articles in a research area, you need to find the seminal works in that field of study.

What is a seminal work?

One way to identify seminal works is to find out how many times other scholars have cited a publication in their own research articles. Generally speaking, when a work is highly cited, it is regarded as an important, or seminal publication.

Use the active webpage on your right to complete the tutorial.

Web of Science, a popular library database, can help you find seminal articles.

Access Web of Science from the library’s homepage:

• Click on the Databases tab in the search box on the library’s homepage.

• Cut and paste or type in Web of Science .
• Scroll down, and click the link to Web of Science.

• Enter your terms (keywords) in the search boxes.

What are keywords?

• Example: sleep AND memory (or use terms for your topic)
• Be sure to select Topic for each keyword search from the drop-down menu(s) on the right.

• Click Search .
• Articles in the results list are sorted by date, newest to oldest.
• Re-sort the list to find the articles with the highest number of citations using the Sort by feature above the search results in the middle of the page.)

• Sort by: Times Cited -- highest to lowest

• The results list is now ranked by the number of times the articles have been cited, with the article with the highest number of times cited at the top.
• The number next to Times Cited links to all of the citing articles.

Additional tip :

• Click on the title of a highly cited article.
• Notice the author(s) names are active links.
• Click on an author's name to see other publications by this scholar.

There are two possible ways to obtain an article when you use UC-eLinks .

NOTE: When you click UC-eLinks , the page will open in a new tab or window, and you won't see the tutorial in the left sidebar. Clicking the tutorial tab will bring you back to the tutorial.

What is UC-eLinks?

• For some articles, clicking on UC-eLinks will take you to a page where you can request the article through I nterlibrary Loan .

What is Interlibrary Loan (ILL)?

Using Web of Science to identify highly cited articles is only the first step in finding seminal works in your field of study. Critical reading of the work should also be a part of evaluating the importance of any publication.

REMINDER : You must be on the UC Merced campus or connected to the campus network with the VPN to access the full-text of articles as demonstrated in this tutorial.

What is the VPN?

This concludes the Using Web of Science to Find Highly Cited Articles tutorial. Now that you’ve finished:

• Complete the short 2-question quiz on the next page.
• Enter your email and your professor’s email when prompted.
• Send the email.
• Print your quiz results if desired.
• Let us know what you think about the tutorial by clicking on the feedback link (What did you think of this tutorial?).

Questions? Contact the library at [email protected] or 209.228.4444.

A seminal work is one that:

Which feature in Web of Science allows you to rank articles in a results list by the number of times they have been cited?

Certificate

Please enter your name and email address to retrieve a copy of your completed quiz.

You can enter multiple email addresses separated by commas, with no spaces (for example, [email protected],[email protected] ). If you are doing this for a class, you may need to enter your instructor's email address also.   Note: It could take up to 10 seconds to generate the certificate. Please do not click the Print/Send button more than once.

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Getting the Most Out of Web of Science

• How to Use Web of Science

Basic Search

Refine results, find full text, open access.

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The default search is set to All Fields.  Sometimes All Fields search is too broad, as it will also search information like author addresses, leading to unexpected results. By selecting Topic from the drop down menu , you can search the title, abstract, author keywords and Keywords Plus . You can also change the Index Date .

The default search is the Web of Science Core Collection. You can search other databases * , or all databases.   Hover over the database for a description.

* UH Manoa currently subscribes to the following databases in Web of Science: Web of Science Core Collection, Biological Abstracts, FSTA the food science resource, KCI Korean Journal Database, Medline, Russian Science Citation Index, SciELO Citation Index, and Zoological Record.

You can rearrange the order of your results. The default is set to sort by Relevance . You can change this by selecting the drop down menu to the right of the Export button.

On the left sidebar of your results, you can find options to refine your results:

You can select from many options, and scroll down the page to find a link to refine by even more options:

You will be directed to another page within Hamilton library's system showing a source record for that result. This source record will show you if Hamilton library holds that item in its physical collection, if it is in an online journal we subscribe to, or if it is online in another form. You may also need to do an Interlibrary Loan.

In some cases, UH Manoa may not provide access to the resource. In these cases, you can request the resource through Interlibrary Loan (ILL).

To find Open Access articles, which means articles you can access without needing to pay for them, and without your institution needing to pay a subscription for access, navigate to the left-side panel to refine your results by selecting either the Open Access option in the Quick Filters box or using the Open Access tab, which provides even further options to refine for open access articles by type.

Using the Open Access tab, you can narrow your results further by selecting different types of Open Access. Gold means the resource is identified as having a Creative Commons license in a database with no paywall. Gold Hybrid refers to a resource identified as having a Creative Commons license but is found in a journal not listed as Gold. Free to Read refers to resources that are free to read or public access articles on a publisher's website. Green Published are resources that are final published versions hosted on an institutional repository or subject based repository. Green Accepted refers to a peer reviewed and final resource but might not have been copy-edited. Green Submitted are manuscripts submitted for publication but may not be peer reviewed. For more information you can look at the Web of Science Help section on Open Access .

You can also see if an article is Open Access if it contains a link that says Free Full Text from Publisher .

• Boolean Operators
• "Phrase Searching"
• Boolean Proximity  search can help you find specific words that are  NEAR  each other.
• Parentheses  can be used in  Boolean  search expressions to override the search operator precedence.
• Wildcards  can also help refine your search by including other possible variations of the words in your search. They represent unknown characters or letters in a word.
• "Phrase Searching"  is searching for exact phrases by including them in "quotation marks."

You can also check out the  Web of Science Core Collection Search Rules Help .  This page is straight from the Web of Science and provides examples and explanations for how to use these search tools in the Web of Science.

AND can be used to include two or more search terms. Results will include both search terms. For example, if you search  climate change AND global warming , results will include results of items that contain both climate change and global warming.

OR can be used to find results with one or the other search terms. For example, if you search for  climate change OR global warming , results will include results of items that contain only climate change, only global warming, or both climate change and global warming.

NOT will exclude a search term from your results. For example, if you search for climate change NOT global warming , then your results will include items that contain climate change, and no articles that contain global warming.

NEAR  is a proximity operator you can use to indicate that you want words that are near each other. In Web of Science you can narrow the search by writing NEAR/x to indicate how many words are between the search term words. For example, "climate change" NEAR/8 ocean will yield results that contain the phrase "climate change" within 8 words of the word "ocean." In Web of Science you cannot use an AND operator with the NEAR operator, but you can include "phrase searching" by putting quotations around the exact phrase you want to include in your search.

SAME  is a limiter you can only use in the Address field of Web of Science, and it will include both addresses in the search results.

You can check out our LibGuide on Boolean Operators for more help or you can go directly to the Web of Science Search Operators Help page.

The  asterisk *  can be used in place of a character or letter when any number of characters or letters, or no character, might be in its place.

• cha*ing matches characterizing, chasing, or changing
• rede* matches redefine, redesign, or redemption
• kel*man* would include Kellermann, Kelman, or Kelerman in Author search.

Using a question mark ? will represent a single character. For example wom?n matches woman or women.

The dollar sign $ represents a single character or no characters. The dollar sign is often used to search for different spellings of the same word. Searching with the word humo $ r retrieves both humor and humour, which are the American and British spellings of the same word.

The Web of Science Core Collection Wildcards Help page is straight from the source and also provides examples and explanations for how to use wildcards in the Web of Science.

Using "quotations" around phrases in your search will yield results with those specific phrases. For example, if you want to find articles with the specific phrase "climate change" putting quotations around this phrase will yield those results.

This can narrow your results in combination with other Boolean operators. For example, searching for climate change AND ocean yields 515 results while searching for "climate change" AND ocean yields 372 results.

The Web of Science Search Rules page contains information on phrase searching with examples and explanations specific to the Web of Science.

Search Tips from the Source!

Refine Results Tutorial

Open access in web of science.

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Web of Science

Getting started, web of science databases.

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The Web of Science (WoS) is a suite of multidisciplinary databases from Clarivate Analytics, part of its Web of Knowledge. Access it through a Harvard Library  website in order to connect to the full-text articles that Harvard has licensed.

Below are more details and a list of the databases within Web of Science.

When you open the Web of Science , first choose which databases to search. The default is the Core Collection (a multi-disciplinary science database), but you can use the pull-down menu to select All Databases for a broad search or a specific database for more focused research.

The databases are listed below, with their Web of Science descriptions.  Note that the years of coverage for each database are different. 

• BIOSIS Citation Index   (1926-present). Life sciences and biomedical research covering pre-clinical and experimental research, methods and instrumentation, animal studies, and more. 
• BIOSIS Previews   (1969-present). Life sciences and biomedical research covering pre-clinical and experimental research, methods and instrumentation, animal studies, and more. 
• CABI : CAB Abstracts®   (1910-present). Provides authoritative research information on agriculture, environment and related applied life sciences. 
• Current Contents Connect   (1998-present). Complete tables of contents and bibliographic information from the world’s leading scholarly journals and books; also includes relevant, evaluated Web sites and documents. 
• Data Citation Index   (1900-present). Discover research data, including data studies, data sets from a wide range of international data repositories and connect them with the scientific literature to track data citation. 
• Derwent Innovations Index   (1963-present). Value-added patent information from  Derwent World Patent Index ® as well as patent citation information from  Patents Citation Index ®. 
• KCI-Korean Journal Database   (1980-present). Provides access to articles from multidisciplinary journals covered in KCI. KCI is managed by the National Research Foundation of Korea and contains bibliographic information for scholarly literature published in Korea. 
• MEDLINE®   (1950-present). The U.S. National Library of Medicine® (NLM®) premier life sciences database. This is the database featured in PubMed .
• Russian Science Citation Index   (2005-present). Access bibliographic information and citations to scholarly articles from Russian researchers in over 500 science, technology, medical, and education journals. Leading publications have been carefully selected and provided by the Scientific Electronic Library (eLIBRARY.RU), Russia's largest research information provider. 
• SciELO Citation Index   (1997-present). Access to scholarly literature in sciences, social sciences, arts and humanities published in leading open access journals from Latin American, Portugal, Spain and South Africa. 
• Web of Science Core Collection (1900-present) Search the world’s leading scholarly journals, books, and proceedings in the sciences, social sciences, and arts and humanities.
• Zoological Record   (1864-present). The world’s leading taxonomic reference and oldest continuing database of animal biology. 
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Search catalog, geog 641: research design.

• Getting Started
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Activity: Evaluating a scientific article

Directions: On your own or in pairs, skim the article "Using GIS-based spatial analysis to determine urban greenspace accessibility for different racial groups in the backdrop of COVID-19: A case study of four US cities" and answer the following questions for your assigned group number. 

Group 1: 

• What are the research questions and/or objectives? 
• Which references in the literature review do you think are most important?  

Group 2: 

• What methods are used in this article?
• What are some of the study's limitations? 

Group 3: 

• What is one of the study's key findings? 
• How many times has this article been cited in Google Scholar?

Author H-index

One way authors can measure research impact is through the h-index.  This metric combines measures of productivity with measures of impact and is designed to reflect research quality over time.  It is defined as follows: "a researcher has an h-index if they have at least h publications for which they have received at least h citations."  For example, if a researcher has an h-index of 12, they have 12 publications that have received at least 12 citations over time.  Authors can find their h-index via Web of Science or Google Scholar. 

Web of Science

On the main page of the Web of Science database, select the Reseachers tab.  Enter the first and last name of the researcher.  You may also search by affiliated organizations or by researcher ID (e.g., ORCID ID, Web of Science ResearcherID).

On the right side of the author's profile page, you will find the Metrics information, which contains the author's H-index.

• Finding Author H-index in Web of Science A step-by-step guide to finding author H-index in Web of Science.

Google Scholar

Researchers can also use Google Scholar to locate their author H-index.  You can search for individual author pages by using the Profiles search box:

Each researcher profile will contain a list of citations and links to each article, as well as a list of co-authors, in addition to author metrics, including the author H-index.

• Creating Your Google Scholar Profile A step-by-step guide to creating your researcher profile in Google Scholar.

Journal Impact Factor

The journal impact factor (JIF)  of an academic journal helps you determine the importance of a journal within its field. 

This number is calculated by dividing the number of current year citations indexed in the Web of Science Core Collection to the source items published in that journal during the previous two years.

For example, the journal impact factor of  Analytical Chemistry  is 8.008. This means, on average, articles published by this journal in the last two years have been cited 8 times. 

You can find a journal's impact factor and compare impact factors across journals in your field in Web of Science's Journal Citation Reports .

JIF is proprietary and there is a lack of transparency in how it is calculated by Web of Science. It has also been criticized for being skewed by a few high impact articles, only counting the most recent two years of citations, its broad definition of "citable items," and disciplinary differences ( Larivière & Sugimoto, 2018 ). 

• Finding Journal Impact Factors in Web of Science A step-by-step guide to finding journal impact factors in Web of Science.
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REVIEW article

Research on digital governance based on web of science—a bibliometric analysis.

• Faculty of Social Sciences and Humanities, Universiti of Kebangsaan Malaysia, Kuala Lumpur, Malaysia

Exploring digital governance is essential for grasping how technology can be employed to enhance public services, boost efficiency, and foster transparency and engagement. This study aims to conduct a systematic review of digital governance research in order to explore its development, emerging research trends, network of leading researchers, countries and institutions that contribute greatly to this field. A bibliometric study was conducted on digital governance works using the following terms: “digital governance,” “E-governance,” “digital government,” and “E-government” as the keywords. VOSviewer and CiteSpace were two tools used for the bibliometric analysis. Results showed that the United States played a dominate role in digital governance studies, followed by China, the United Kingdom, India, and Spain. Brunel University, University at Albany, and University of Johannesburg were the top three research institutes for digital governance. Reddick C.G., Weerakkody V., Dwivedi, Y. K., Mensah, I. K., and Jaeger, P.T. served as the representative researchers in this field. In addition, topics including usability and reliability of digital governance system, quality assurance under the framework of digital governance, the quality of digital service, impact of digital governance on public perception, effects of digital transformation on public value perceptions were the focal points in recent years.

1 Introduction

Just as the term E-Commerce came into existence during the rapid expansion of the Internet, the term E-Government also emerged in response to the technological advancements and increased connectivity facilitated by the Internet boom. The concept of E-Gov (Electronic Government or Electronic Governance) originated in the late 1990's as a platform for practitioners to exchange experiences. This period witnessed the integration of digital technologies into governmental processes, giving rise to the concept of leveraging electronic means for more efficient and accessible government operations.

Various institutions and scholars have provided distinct definitions for E-Government. As articulated by the U.S. Congress in 2002, it refers to the government's strategic use of web- based Internet applications and other information technologies. This, coupled with associated processes, serves the dual purpose of enhancing access to and delivery of government information and services to the public, other agencies, and government entities, while concurrently fostering improvements in government operations—encompassing effectiveness, efficiency, service quality, and overall transformation.

Expanding on this perspective, Grönlund (2010) and Grönlund and Horan (2005) described E-Government as the transformative integration of information technologies by government agencies, which is aimed at revolutionizing interactions with citizens, businesses, and various governmental sectors, thus enhancing the delivery of government services to citizens, improving interactions with businesses, empowering citizens through information access, and building a more efficient process in government management.

Initially, E-Government primarily concentrated on developing citizen-centric services and improving government operations without considering factors outside of the public sector ( Janssen and Estevez, 2013 ). Contemporarily, E-Government research presents a multifaceted exploration of the evolution, implementation, challenges, and future prospects of digital governance. Digital government, originating in the late twentieth century, involves the use of information and communication technologies to enhance the efficiency, accessibility, and quality of public sector operations. The evolution of digital government reflects a shift toward networked, transparent, and user-oriented governance models, influenced by internet-era technological capabilities and changing expectations of citizens and businesses ( Dunleavy and Margetts, 2006 ). Stages of development range from basic information spreading to complex integration and transactional capabilities ( Layne and Lee, 2001 ). Globally, digital government implementation varies due to technological, political, and socio-economic factors. Developed countries lead in rankings, while developing countries make strides with innovative models ( Richard, 2002 ). Comparative studies offer insights and lessons applicable in different contexts ( Andersen et al., 2010 ). In China, a comprehensive digital transformation strategy includes significant investments in digital infrastructure, innovation, and technology-led development. Initiatives like smart cities, digital identity systems, and nationwide e-service platforms demonstrate the government's ambition to enhance state capacity and public service delivery ( Ma, 2015 ; Zheng L., 2017 ). Despite progress, challenges persist, including the digital divide, privacy concerns, and institutional resistance. Disparities in technology access hinder service effectiveness and equity ( Norris, 2001 ), and privacy and security issues are of paramount importance with government transactions ( Bertot et al., 2010 ). Transforming bureaucratic structures faces resistance, requiring investment in technology, infrastructure, human capital, and policy frameworks ( Dawes, 1996 ; Schöll and Scholl, 2014 ). The future of digital government will be shaped by ongoing technological innovations and public expectations. Emerging technologies like AI, blockchain, and IoT offer possibilities for personalized, predictive, and participatory government services ( Bertot et al., 2010 ). The emphasis is growing on using digital government to achieve broader societal goals, including sustainability, social inclusion, and economic development ( Meijer and Bolívar, 2016 ). Over time, E-government policies and research have moved away from a predominantly technology-centered approach. Instead, there has been a shift toward seeing citizens as customers and prioritizing the creation of services driven by customer needs and preferences ( Janssen and Estevez, 2013 ).

E-Government pertains specifically to activities within government organizations, with its use in IS (Information Systems) research often limited to those government entities offering services to citizens or companies. In contrast, E-Governance encompasses the entire societal management system. This broader system involves activities not only by government organizations but also by companies, voluntary organizations, and, notably, citizens—a facet often overlooked ( Grönlund and Horan, 2005 ). E-Governance can be defined as the provision of government services and information to the public through electronic methods. Enhanced informational capabilities could greatly improve the interactions between the government and citizens ( Christine and John, 1998 ). Numerous governments and companies hold the belief that technology can replace traditional governance and human accountability ( Gil et al., 2019 ). The utilization of Information Technology (IT) facilitates an efficient, rapid, and transparent process for sharing information with the public and other agencies, as well as for conducting government administrative activities. With digital transformation, governance now encompasses more than just the decision-making rights and responsibilities of the IT department. Technology has become integral to the entire organization and its operations, rather than being merely an organizational unit ( Jewer and Van Der Meulen, 2022 ).

Dunleavy and Margetts (2006) and Meijer et al. (2012) , used the term digital governance, defining it as a transformative concept, covering mechanisms, processes, and traditions determining power exercise, stakeholder engagement, and decision-making in the digital age. It presents the impact of rapidly evolving digital technologies over traditional governance structure, where policy- making, regulation, and service delivery are all adapted. Technologies have profound influence on digital governance. Technologies such as blockchain, AI, and big data play a transformative role in reshaping governance expectations, presenting opportunities for transparency and citizen engagement. However, challenges related to privacy and security occurred simultaneously, as noted by Bertot et al. (2010) and Wirtz and Müller (2018) . Governments should prioritize improving infrastructure in rural areas and provide free or subsidized access to e-government services, while also implementing digital skills training programs, particularly for older and less educated individuals, to bridge the digital divide ( Sharma and Soliman, 2003 ). Ranging from the digital divide to concerns about data privacy, these obstacles require targeted policies, infrastructure development, and education investments. Ethical considerations emerge as paramount in ensuring public trust and legitimacy in the ongoing efforts toward digital governance, as highlighted by Jaeger and Thompson (2003) and Norris (2001) . In addition, Bellamy and Taylor (1998) and Bovens and Zouridis (2002) believed that the establishment of adaptive and responsive governance structures is of great importance, since it is crucial for effectively harnessing the benefits of technology while navigating and mitigating associated risks.

The diverse political, social, and technological dynamics of each country significantly influence the construction of global digital governance. It is evident as leading nations such as Estonia and Scandinavia adopt citizen-centric approaches and innovative digital services, while larger countries like the United States and China concentrate on expanding digital initiatives. These endeavors encounter challenges associated with access and regulatory intricacies, as discussed by Margetts and Dunleavy (2013) and Zheng Y. (2017) . In China, digital governance initiatives strategically target transparency, public sector efficiency, and citizen engagement. The most typical one is the “Internet Plus” strategy, where internet-based technologies are integrated, reflecting China's distinctive political and regulatory emphasis on state-led governance, as stated by Zhang and Cheng (2019) and Ma (2015) . The future of digital governance is shaped by technological innovations and societal shifts. Networked governance models, citizen-led initiatives, and cross-border collaborations suggest a move toward open, flexible structures ( Luna-Reyes and Gil-García, 2014 ; Meijer and Bolívar, 2016 ).

E-governance offers critical improvements to the efficiency and effectiveness of governance. It enhances government processes by automating and streamlining internal operations, thereby reducing costs and increasing productivity. E-governance also serves to connect citizens with their government more directly by providing online services and information, which improves the quality and convenience of public services and fosters a more transparent and accountable government. Furthermore, it builds external interactions by strengthening the ties between government and other institutions, including businesses and civil society organizations, which can lead to better policy-making and more responsive governance. By leveraging ICTs, E-governance can empower local communities, support decision-making with timely and accurate data, and contribute to broader societal goals such as sustainable development and social inclusion. E-governance extends beyond the realm of E-government. E-government focuses on delivering government services and information to the public through electronic means. In contrast, E-governance facilitates direct citizen involvement in political activities, surpassing traditional government functions. Kar et al. (2017) highlighted that the transformative impact of digital tools and platforms on citizen engagement, emphasizing their role in fostering participatory governance. By shifting from traditional top-down models to inclusive digital platforms, and through initiatives like e-participation tools, innovative engagement models, and open data, governments can enhance transparency, accountability, and citizen involvement in decision-making processes. It encompasses aspects like e-democracy, e-voting, and online political participation. Governance is influencing governments, prompting consideration of social contracts within a digital governance framework ( Idzi and Gomes, 2022 ). Essentially, E-governance includes government functions, citizen engagement, political parties and organizations, as well as parliamentary and judicial roles ( Jayashree and Marthandan, 2010 ).

Although studies on digital governance are increasing, there is a relative scarcity of systematic reviews, including its development, emerging research trends, leading researchers, and countries and institutions that have made significant contributions to this field. Therefore, this study serves as a supplement to systematic reviews of digital governance. Additionally, through a systematic analysis, this study highlights that digital governance is an interdisciplinary field involving multiple disciplines such as computer technology, public administration, political science, and economics. However, current research may not fully explore the intersections and integrations among these different fields. Furthermore, while digital governance brings many opportunities, it also comes with challenges such as privacy, security, and the digital divide. These challenges require more attention and research.

2 Materials and methods

2.1 data collection.

To ensure the scientific credibility and reliability of the data origin, this scholarly literature is derived from the primary collection of the Web of Science (WOS) database. WOS is recognized as the most extensively utilized and authoritative database for academic publications and citations.

The data were obtained by searching the topic terms “digital governance,” “E-governance,” “E-government,” and “digital government” from 2000 to 2023. The document type specified for retrieval was journal articles. Following the retrieval process and the elimination of duplicated and irrelevant articles, this research ultimately gathered 2,876 published papers within the 24-year timeframe.

2.2 Research method

Bibliometric approaches have been employed for a quantitative examination of written publications, offering valuable insights into the intellectual terrain of particular research domains. This method allows for a systematic literature review, aiding in the extraction of information and recognition of patterns within the scholarly field. Up to now, there are many visualization software tools, with notable attention given to CiteSpace developed by Chen (2006) from Drexel University in the United States and VOSviewer developed by CWTS at Leiden University in the Netherlands. Both tools excel in generating comprehensive visualizations, offering excellent visual effects, and providing research perspectives from different angles ( Song and Chi, 2016 ).

This research utilized VOSviewer for analyzing keywords concurrence, cooperation networks, presenting hotspots, collaborations among researchers, nations and institutions in the field of digital governance. Additionally, CiteSpace, known for its trend depiction and customizable parameters, was employed to visualize keywords time zone and burst detection, through which the focal areas, and prospective trends within the realm of digital governance will be explored. Figure 1 is the technical road map of this study, which generally presents the process of the research including data collection, data screening, the use of analytical tools as well as the specific analytical framework.

Figure 1 . Technical road map (source: authors' illustration).

3 Discussion

3.1 literature development trends.

Based on statistical analysis obtained from the Web of Science, the total number of publications in the field of digital governance or digital government is 2,876 articles. Figure 2 illustrates the annual publication volume in this field from 2000 to 2023. Overall, it shows an increasing trend, indicating that over the past two decades with the development of information technology, research on digital governance and digital government has gained more attention. Findings suggest that initial interest in this field was rare before 2001, followed by a rapid increase in attention after 2002, with publication volumes surpassing 100 annually since 2007. The highest publication volume was observed in 2012, and although there was a subsequent decline, there has been a steady increase since 2020. To some extent, this is closely related to the impact of the COVID-19 pandemic on government digital governance. The pandemic accelerated the adoption of digital government, prompting governments worldwide to swiftly implement digital solutions to address the challenges posed by the crisis. This indicates that the transformation of government, digital government, and digital governance have been significantly influenced by the combination of public emergencies and the development of digital technologies.

Figure 2 . Diagram of publication (source: authors' illustration).

3.2 Cooperation network

3.2.1 contribution and cooperation on national level.

VOSviewer enables researchers to visually represent co-authorship networks on a country level, offering valuable insights into collaborative patterns among nations. This facilitates the identification of both robust and less pronounced connections between countries, providing a holistic comprehension of international cooperation across diverse research domains. In this section, “country” was chosen as the node for research to get the cooperation network among countries in the field of digital governance. A total of 125 countries were involved, where 42 countries came to a threshold of 20 or more publications. As can be seen in Figure 3 , the size of the node represents the contribution of each country in this field, of which the biggest is the USA, proving its leading role of the research in this field. Table 1 presents the top ten countries that contribute to digital governance. In addition to USA, the other top countries are China, England, India, Spain, Australia, South Korea, Greece, South Africa and Canada, showing that scholars in these countries also have strong interest in the field of digital governance. The other top countries are China, England, India and Spain, showing that scholars in these four countries also have strong interest in the field of digital governance. As can be seen from the depth and complex connection between countries, the USA has a close relationship with China, South Korea and Mexico, while China as a super power in digital technology, keeps close a cooperation with USA, Pakistan and Malaysia.

Figure 3 . Diagram of cooperation among nations (source: authors' illustration).

Table 1 . Top 10 contributed nations (source: authors' illustration).

For the overlay visualization, there is a bar on the bottom right of Figure 4 , with the colors that illustrate the time when each country engaged in the study of digital governance. It is evident that the USA, England, Greece, Canada were the earliest ones. Regarding the top five contributing countries, China and India were the later ones, demonstrating the rapid development of digital technology and implementation of it on governance of the two big countries.

Figure 4 . Overlay visualization of cooperation among nations (source: authors' illustration).

3.2.2 Contribution and cooperation on institutional level

A total of 2,300 research institutions were involved in the digital governance study. Among them, 60 research institutions reached a threshold of 10 or more publications in this field. Based on Figures 5 , 6 , together with the summary from Table 2 , it can be seen that the most influential research institution is Brunel University with a total number of publications of 45, and a total link strength of 16. The next two are the University at Albany and the University of Johannesburg with a total number of publications of 42 and 33, respectively. The map also illustrates that institutional collaboration in digital research exhibits regional characteristics, with key institutions primarily located in countries that contribute greatly in this field including the United States and the United Kingdom. Notably, based on the top five institutions, the University of Johannesburg, South Africa and the National University of Singapore, Singapore, rank third and fifth, albeit in terms of nation contributors, South Africa ranks ninth and Singapore is not listed in the top ten. In addition, as for the second nation contributor, China, Tsinghua University, Huazhong University of Science and Technology and Shanghai Jiaotong University, rank 12, 16, and 19, respectively. As can be seen from the overlay visualization, the institutions from South Africa and China are colored green and yellow, showing that they recently started their interest with digital governance, which to some extent, matches with the overlay visualization of nation cooperation.

Figure 5 . Diagram of cooperation among institutions (source: authors' illustration).

Figure 6 . Overlay visualization of cooperation among institutions (source: authors' illustration).

Table 2 . Top 10 contributed institutions (source: authors' illustration).

3.2.3 Contribution and cooperation on researchers' level

A total of 5,267 researchers were involved in the digital governance study. Among them, 97 different pieces of research reached a threshold of 5 or more publications in this field. Through the analysis of Figure 7 on researchers' contribution, it can be found from the Table 3 that the top five contributors on publication in this field are Reddick C.G., Weerakkody V., Dwivedi, Y. K., Mensah, I. K. and Jaeger, P.T. According to the index of citations, the top five are Jaeger Paul T., Reddick C.G., Weerakkody V., Bertot, J. C., and Kassen, M. Furthermore, it can be seen from the density visualization that there are 46 clusters of author cooperation, of which 14 of them derive from more than three authors in a group. Since the deeper the color is, the more active the author will be in this field. Therefore, it can be seen that Weerakkody V., Dwivedi, Y. K., Reddick C.G., Gil-García, J. R., Mensah, I. K., Joseph, B. K., and Jaeger, P.T. are the most active researchers in this field and maintain close cooperation with other researchers.

Figure 7 . Diagram of cooperation among researchers (source: authors' illustration).

Table 3 . Top 10 contributed researchers (source: authors' illustration).

3.3 Researching hotspots and emerging trends

3.3.1 keyword: co-occurrence.

Analyzing keywords in VOSviewer is a crucial tool for researchers seeking to comprehend the composition of a research domain, identify emerging patterns, and enhance collaboration with fellow researchers. The VOSviewer software possesses unique advantages in the field of keyword co-occurrence clustering technology. The author utilized VOSviewer software, choosing the fractional counting method, with the total number of keywords at 5,726, a threshold of 20, to create a keyword co-occurrence weighted graph for the study of digital governance ( Figure 8 ). The size of the circle representing a keyword indicates its frequency, with larger circles denoting higher frequencies, signifying more popular topics in the field of digital governance. The placement of keywords toward the center of the graph indicates their greater importance, highlighting them as crucial concepts within the research field. The TOP 30 keywords in digital governance research were organized and ranked, as presented in Table 4 .

Figure 8 . Diagram of keywords co-occurrence (source: authors' illustration).

Table 4 . Top 30 keywords (source: authors' illustration).

Figure 8 and Table 4 reveal that keywords such as “E-government,” “adoption,” “trust,” “service,” and “model” hold a central position in the study of digital governance trends. These keywords have a certain representation and have gained high attention within the academic community around the globe. Xanthopoulou et al. (2023) show how digital governance adoption integrates digital technologies and methods into organizational or government operations. Digital adoption enhances internal efficiency, meets regulatory requirements, enables data- driven decision-making, and improves public services, leads to more efficient service delivery and resource utilization for government agencies and businesses, thus making it an important topic for researchers to explore. Establishing digital trust is a crucial element for organizations to facilitate and safeguard their digital transformation. Institutional trust pertains to the confidence that citizens have in government and political institutions, serving as a significant indicator of the vitality of democracy in contemporary nations ( Chen et al., 2023 ). It can be found that digital governance and trust is closely intertwined, with trust being a pivotal element in the acceptance and prosperity of digital initiatives. According to Milakovich (2012) , the adoption of digital information and communication technologies (ICTs) to reform governmental structures and public services is widely perceived as an enlightened strategy for the twenty-first century. It is seen as a potential solution to reinvigorate democracy, reduce costs, and enhance the quality of public services. The digital governance models are constantly changing and adapting to leverage the capabilities of emerging technologies, and there are no fixed or definitive models for digital governance. In terms of “model,” numerous digital governance models exist, and they are consistently adapting to leverage the capabilities of emerging technologies. These models are not fixed or limited, and their examination should be contextualized within discussions surrounding the concept of digital governance. Additionally, topics including information technology, user acceptance for digital platforms, management of digital governance, and framework for digital governance, have also become research hotspots in this field.

3.3.2 Keyword: clustering

Figure 9 illustrates a clustering view of keywords in digital governance research, where the same color represents a cluster, indicating a specific theme within digital governance studies. As depicted in Figure 9 , digital governance research primarily encompasses seven clustered themes.

Figure 9 . Diagram of keywords clustering (source: authors' illustration).

3.3.2.1 Cluster 1: E-government adoption and trust

The keywords in this cluster include adoption, trustworthy, service, etc. E-government relies significantly on adoption and trust, as they play a pivotal role in motivating citizens to embrace E-government services. They contribute to diminishing perceived risks, fostering civic engagement, surmounting initial obstacles, and establishing enduring relationships between citizens and the government. According to Papadopoulou et al. (2010) , trust is a fundamental component of E-government, and therefore, it should not be considered as an afterthought. Instead, it should be carefully considered early in the process, integrated with the design and deployment of an E-government system. Warkentin et al. (2002) believed that to achieve cost reduction, enhance services, and enhance responsiveness to citizens, it is crucial for both national and local governments to instill trust in the online services they currently offer or plan to offer in the future. Dashti et al. (2010) suggested that feeling trust, distinct from conventional adoption models, centers not only on users' beliefs about the e-service provider but specifically on how the provider perceives them. This will enhance our understanding of user evaluation and the use of E-government while elucidating the reciprocal nature of user interactions with E-government and other e-service providers.

3.3.2.2 Cluster 2: digital governance and citizen participation

The high frequency keywords in this cluster cover digital governance, transparency, citizen participation, etc. In digital governance, citizen participation plays a crucial role by promoting a feeling of shared ownership, collective responsibility, and accountability. It entails involving citizens in public affairs through the utilization of digital tools and platforms like social media, mobile applications, and online digital platforms. Muhlberger (2006) explored citizen involvement in local governance to gauge the adequacy of current information and communication technology (ICT) in meeting community communication and information requirements. Luciano et al. (2018) first identified strategies and barriers for the adoption of digital governance (DGO) in the Brazilian public administration, specifically focusing on strategic objectives related to social participation outlined in the Brazilian Digital Governance Policy (DGP), then proposed three strategic objectives related to social participation, including promoting collaboration in the public policy cycle, expanding and encouraging social participation in enhancing public services, and enhancing direct interaction between the government and society. Rodriguez-Hevía et al. (2020) , by reviewing citizen's involvement in E-government of the European Union, proposed that while many citizens have access to the Internet, it does not automatically imply that they will extensively use e- government services. Digital literacy appears to be the most critical factor influencing overall E-government usage. In addition, Matheus et al. (2023) pointed out that transparency is only created when open data is useful to the public. Functionality can enhance transparency, thereby increasing perceived efficiency and perceived usefulness. Special attention should be paid to the diverse needs of citizens and ensuring efficiency, as the time of citizens and other users is limited. Transparency can enhance the credibility of open government, but usefulness may not always necessitate transparency, therefore it is suggested to create classifications for transparency initiatives.

3.3.2.3 Cluster 3: digital governance framework and digital transformation

The high frequency keywords in this cluster include digital transformation, framework, management, innovation, etc. Digital governance provides a strategic framework for developing and enacting innovative approaches to transition from bureaucracy-oriented to citizen-focused public services ( Milakovich, 2014 ). Al-Badi et al. (2018) proposed that a comprehensive framework for Big Data governance is essential for establishing guidelines, procedures, and criteria to efficiently manage and safeguard the availability, usability, integrity, consistency, auditability, and security of Big Data. Jia and Chen (2022) expanded the “issue-actor-mechanism (IAM)” model into an analytical framework for delineating global digital governance. Tannou et al. (2012) suggested that governance plays a pivotal role in the success of digital transformation, ensuring that digital initiatives are coordinated and shared appropriately within the company, aligning with its structure, culture, and strategic objectives. Gil-Garcia et al. (2018) addressed that the scholarly communities of Digital Governance (DG) and Public Management (PM) exhibit variations across multiple dimensions while also sharing significant similarities. Importantly, there is evidence of potential for collaborative efforts that could benefit both fields of study.

3.3.2.4 Cluster 4: digital divide

The high frequency keywords in this cluster include digital divide, e- government implementation, developing countries, etc. The digital divide significantly affects digital governance, leading to adverse outcomes for individuals in underdeveloped regions and those with lower socio-economic status. Limited access to digital technologies and the Internet can create obstacles in utilizing E-government services, resulting in disparities in resource access and public service utilization. Yigitcanlar and Baum (2008) indicate that the term “global divide” signifies the gap in Internet accessibility between advanced and developing nations, while the “social divide” pertains to the disparity in information access within individual countries, separating the affluent from the disadvantaged. Mariscal (2005) , Ogunsola and Okusaga (2006) , and Acilar (2011) , analyzed the situation of digital divide in developing countries by reviewing the facts in Mexico, African countries, and Turkey.

3.3.2.5 Cluster 5: digital governance and sustainability

The high frequency keywords in this cluster cover sustainability, corruption, sustainable development, public policy, etc. Barbosa (2017) pointed out that digital transformation serves as a tool to promote sustainable development and more inclusive societies. From a practical standpoint, digitization presents the opportunity to enhance governmental operations and, if properly orchestrated, can play a role in advancing the imperative sustainable development agenda in the foreseeable future. Xu et al. (2022) believed that the bolstering of digitization contributes to sustainable development, as evidenced by the broad array of literature and theoretical frameworks. The belief that notable advancements in digital governance inevitably result in improved sustainable governance is erroneous. The dynamics between digital governance and sustainable governance are complex, involving various potential moderating and mediating factors that warrant additional investigation ( Durkiewicz and Janowski, 2021 ). In terms of corruption and digital governance, Martins et al. (2018) highlighted a significant finding: the correlation between digital government and corruption differs among income groups, suggesting that policymakers in the least developed nations should not view E-government as a definitive remedy for combating corruption.

3.3.2.6 Cluster 6: smart city and information security

The high frequency keywords in this cluster cover smart city, information security, privacy, etc. According to Sucupira Furtado et al. (2023) , the connection between smart cities and digital governance is substantial, as digital governance serves as a fundamental element of the smart city initiative and a crucial avenue for realizing sustainable development objectives through digital transformation. Smart city governance has evolved from the wider realm of E-governance and seeks to improve the effectiveness of public institutions by leveraging digital technologies and institutional innovation ( Myeong and Bokhari, 2023 ). By reviewing the situation of smart city in Belgium, Esposito et al. (2023) provided fresh insights into the multifaceted nature of the smart city concept, revealing that local authorities can flexibly employ smart city initiatives as tools to address various location-specific environmental, social, and economic challenges. Singh and Karaulia (2011) suggested that information security is crucial in E-governance initiatives, ensuring the confidentiality of transactions and data, protecting government documents from unauthorized access, and integrating robust security systems to ensure successful project implementation. In digital governance, safeguarding information security and integrity is paramount, as any security loopholes may result in severe repercussions, undermining public trust and government credibility, necessitating comprehensive measures spanning policy, processes, and training for successful implementation.

3.3.2.7 Cluster 7: public administration under digital governance

The high frequency keywords in this cluster cover public administration, infrastructure, efficiency, etc. Digital governance provides a framework and approach to leveraging digital technologies to enhance the efficiency and transparency of public administration while promoting the development and maintenance of public infrastructure. Margetts (2008) explored the relationship between E-government and public management reform, suggesting that “digital-era governance” (DEG), which challenges or transcends the managerial styles of New Public Management (NPM), is a valuable approach to understanding contemporary administrative reform, outlining three main themes of DEG: reintegration, needs-based holism, and digitization, illustrating how the widespread use of digital technologies by governments, businesses, and society at large triggers organizational responses in government entities. As public administrations are still in the process of transitioning to E-government and/or E-governance perspectives and have not fully undergone digital transformation, the empirical data were collected from administrations at various stages of this process ( Mergel et al., 2019 ). According to Chantillon (2021) , as suggested by the concept of “good enough governance,” public administrations are indeed continuously balancing the public values they strive to achieve, the use of coordination tools, and the interrelated objectives set by different public management departments. To facilitate digital transformation, changes in how public administrations function and the public values they strive for will be necessary. However, these changes will only occur gradually and sometimes may not lead to the desired success, thus necessitating monitoring and evaluation.

3.3.3 Evolution of research hotspots

The time zone analysis of CiteSpace represents the chronological evolution of scholarly literature and pinpoints emerging trends and patterns over time. By organizing articles and terms based on their publication dates, CiteSpace's time zone view enables researchers to examine the fluctuation of research topics, notable terms, and significant advancements within a specific field. This functionality is particularly beneficial for monitoring the advancement of scientific knowledge, recognizing influential publications, and comprehending the temporal context of research trends. The time zone view offers researchers a distinctive viewpoint to glean insights into the historical progression of a discipline and choose informed assessments regarding the significance and impact of scientific endeavors throughout time.

From Figure 10 , it can be observed that research in the field of digital governance in the core collection of the foreign Web of Science database can be divided into three phases, with the earliest research traced back to 2001. Specifically, from 2001 to 2008, scholars primarily focused on information technology, which is the prerequisite of digital governance or digital government, then shifted their attention on the adoption, acceptance, and management of digital governance. From 2009 to 2018, there was a notable emphasis on quality, transparency, trust and satisfaction with digital governance. It is found that the less attention has been put on the technical level but more on the effects and feedback of digital governance. Finally, from 2019 to 2023, scholars predominantly investigated corruption, digital divide, artificial intelligence, and sustainable development in digital governance. According to these keywords, it can be summarized that during this phase more specific points and long-term goals in a wider scale have become the interest of researchers. As mentioned in previous sections in this article, digital divide's impact over developing countries, whether digital governance advances sustainable development, artificial intelligence's impact over digital governance, plays a role.

Figure 10 . Diagram of keywords time zone (source: authors' illustration).

3.3.4 Research frontiers in the field of digital governance

Burst detection in CiteSpace is a functionality designed to pinpoint spikes in activity, such as sudden surges in citations to a specific publication or rapid escalations in the output of publications by a particular author. Utilizing Kleinberg's algorithm, this feature can detect bursts that span multiple years or occur within a single year. The visual representation of burst detection can be applied across different types of nodes, including articles, authors, or keywords, aiding in the identification of highly active research areas or emerging trends ( Chen, 2014 ).

From the Figure 11 , it can be observed that the word “technology” has the longest burst period from 2001 to 2008, while communication technologies owns the strongest burst with the strength of 19.65, showing that at the beginning stages of digital governance most of the attention was given on technical level, which complies with the result of time zone analysis in the previous part. As for the latest burst, it can be found that there are four words, “system”, “quality”, “perceptions” and “public value”. According to these words, it can be uncovered that the research frontiers for digital governance include the usability and reliability of digital governance system, quality assurance under the framework of digital governance, the quality of digital service, impact of digital governance on public perception, effects of digital transformation on public value perceptions, etc.

Figure 11 . Diagram of keywords citation burst (source: authors' illustration).

4 Conclusion

(1) The bibliometric analysis of academic literature demonstrates that since 2000, there has been a growing focus in research areas such as digital government, digital governance, digital transformation, and sustainable governance. Examination of the distribution and growth of these topics suggests that research in digital governance is characterized by its interdisciplinary nature, intersecting with disciplines such as computer technology, public administration, political science, and economics. Otherwise, the widespread adoption of digital government has been hastened by global public crises, prompting governments worldwide to swiftly implement digital solutions to tackle crisis-related challenges. This underscores the significant impact of public emergencies alongside the evolution of digital technologies on government transformation, digital governance, and digital government.

(2) At the national level, the United States holds a leading position in the field of digital governance research. The other four countries of China, the United Kingdom, India, and Spain, have also made great contribution in digital governance research. The density of collaboration between countries indicates close relationships between the United States and China, South Korea, and Mexico, while China, as a superpower in digital technology, maintains close cooperation with the United States, Pakistan, and Malaysia. Additionally, the United States, the United Kingdom, Greece, and Canada were among the earliest countries to initiate research related to digital governance. Among the top five contributing countries, although China and India started later, the rapid development of digital technology in these two major countries has swiftly propelled them to the forefront of research in this field.

(3) In terms of institution contributions, the most influential research institutions are Brunel University, the University at Albany, and the University of Johannesburg. Institutional collaboration exhibits regional characteristics, with key institutions primarily located in countries that have made significant contributions in this field, including the United States and the United Kingdom. Among the top five institutions, the University of Johannesburg, South Africa, and the National University of Singapore, Singapore, rank third and fifth respectively, despite South Africa ranking ninth and Singapore not listed in the top 10 in terms of national contributions. This indicates that institutional contributions do not completely overlap with national contributions. From the overlay visualization, it can be seen that the institutions from South Africa and China have made significant contributions to digital governance research in recent years.

(4) In terms of author contributions, the top five contributors in this field are Reddick C.G., Weerakkody V., Dwivedi, Y. K., Mensah, I. K., and Jaeger, P.T. Additionally, Weerakkody V., Dwivedi, Y. K., Reddick C.G., Gil-García, J. R., Mensah, I. K., Joseph, B. K., and Jaeger, P.T., are the most active researchers in this field, maintaining close collaboration with other researchers.

(5) According to the analysis of keywords co-occurrence, clustering, burst and time zone distribution, shows that the current research hotspots and trends in digital governance encompass various aspects. Initially, in the early stages, research primarily focused on the technological level, particularly the application of information technology, as a prerequisite for digital governance or digital government. Subsequently, the focus gradually shifted toward the adoption, acceptance, and management of digital governance, emphasizing the importance of quality, transparency, trustworthiness, and satisfaction. The latest research now increasingly addresses the usability and reliability of digital governance systems, the quality of digital services, the impact of digital governance on public perceptions, and the effects of digital transformation on public values. Additionally, researchers have started to pay attention to some challenges and issues in digital governance, such as corruption, the digital divide, artificial intelligence, and sustainable development. This indicates that digital governance research is gradually expanding from the technological level to broader social and political domains, with a greater focus on the impacts and practices of digital governance, as well as how to address the challenges and opportunities of the digital age. However, this study also has some limitations. The research data solely comes from the Web of Science database, overlooking literature from other databases such as Elsevier Science and Google Scholar, which may introduce some information bias. The overall coverage of the WoS database is less extensive compared to some other databases such as Scopus, especially in the fields of social sciences and humanities. Other than that, in the humanities, Scopus covers a significant portion of the data available in WoS, whereas WoS only covers a smaller portion of the data available in Scopus. Additionally, due to subscription terms, the accessible timeframe for citations in WoS is relatively short ( Pranckute, 2021 ). Therefore, the study may be limited by the availability of data sources. This implies that it may not comprehensively capture all relevant academic discussions and research findings within the field of digital governance, particularly those published in related disciplinary domains. In the process of literature screening, the diversity in keyword selection may lead to the appearance of semantically similar terms, affecting the accuracy of data analysis. Additionally, only English articles were selected, resulting in some data gaps. Furthermore, the study covers relatively a large time span, constrained by sample selection and the knowledge level of the authors, which may lead to insufficient depth and comprehensiveness in certain parts of the analysis.

Finally, according to previous analysis on research hotspots as well as the evolution of the research of digital governance, it can be assumed that future research on digital governance will focus on the usability and reliability of systems, exploring user acceptance, system performance, and service quality. Additionally, studies will examine how digital governance affects public perception and trust in government services, as well as the impact of digital transformation on public expectations and values. Other than that, challenges and issues in digital governance, such as corruption, the digital divide, artificial intelligence, and sustainable development will continue to be the focus of researchers. What's more, key areas of future research will also include how emerging technologies enhance the personalization and participatory nature of government services, and how to construct a global digital governance framework.

Author contributions

ZL: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. MY: Supervision, Writing – review & editing.

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Acknowledgments

Thanks to UKM for the support of this research. We also would like to extend special thanks to the editor and the reviewers for their insightful comments and constructive suggestions.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: digital governance, bibliometric, developmental trends, research hotspots, VOSviewer, CiteSpace

Citation: Lin Z and Yaakop MR (2024) Research on digital governance based on Web of Science—a bibliometric analysis. Front. Polit. Sci. 6:1403404. doi: 10.3389/fpos.2024.1403404

Received: 25 April 2024; Accepted: 24 July 2024; Published: 16 August 2024.

Reviewed by:

Copyright © 2024 Lin and Yaakop. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Zhao Lin, P118333@siswa.ukm.edu.my

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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How to Write a Research Proposal: (with Examples & Templates)

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Before conducting a study, a research proposal should be created that outlines researchers’ plans and methodology and is submitted to the concerned evaluating organization or person. Creating a research proposal is an important step to ensure that researchers are on track and are moving forward as intended. A research proposal can be defined as a detailed plan or blueprint for the proposed research that you intend to undertake. It provides readers with a snapshot of your project by describing what you will investigate, why it is needed, and how you will conduct the research.  

Your research proposal should aim to explain to the readers why your research is relevant and original, that you understand the context and current scenario in the field, have the appropriate resources to conduct the research, and that the research is feasible given the usual constraints.  

This article will describe in detail the purpose and typical structure of a research proposal , along with examples and templates to help you ace this step in your research journey.  

What is a Research Proposal ?  

A research proposal¹ ,²  can be defined as a formal report that describes your proposed research, its objectives, methodology, implications, and other important details. Research proposals are the framework of your research and are used to obtain approvals or grants to conduct the study from various committees or organizations. Consequently, research proposals should convince readers of your study’s credibility, accuracy, achievability, practicality, and reproducibility.   

With research proposals , researchers usually aim to persuade the readers, funding agencies, educational institutions, and supervisors to approve the proposal. To achieve this, the report should be well structured with the objectives written in clear, understandable language devoid of jargon. A well-organized research proposal conveys to the readers or evaluators that the writer has thought out the research plan meticulously and has the resources to ensure timely completion.  

Purpose of Research Proposals  

A research proposal is a sales pitch and therefore should be detailed enough to convince your readers, who could be supervisors, ethics committees, universities, etc., that what you’re proposing has merit and is feasible . Research proposals can help students discuss their dissertation with their faculty or fulfill course requirements and also help researchers obtain funding. A well-structured proposal instills confidence among readers about your ability to conduct and complete the study as proposed.  

Research proposals can be written for several reasons:³  

• To describe the importance of research in the specific topic  
• Address any potential challenges you may encounter  
• Showcase knowledge in the field and your ability to conduct a study  
• Apply for a role at a research institute  
• Convince a research supervisor or university that your research can satisfy the requirements of a degree program  
• Highlight the importance of your research to organizations that may sponsor your project  
• Identify implications of your project and how it can benefit the audience  

What Goes in a Research Proposal?    

Research proposals should aim to answer the three basic questions—what, why, and how.  

The What question should be answered by describing the specific subject being researched. It should typically include the objectives, the cohort details, and the location or setting.  

The Why question should be answered by describing the existing scenario of the subject, listing unanswered questions, identifying gaps in the existing research, and describing how your study can address these gaps, along with the implications and significance.  

The How question should be answered by describing the proposed research methodology, data analysis tools expected to be used, and other details to describe your proposed methodology.   

Research Proposal Example  

Here is a research proposal sample template (with examples) from the University of Rochester Medical Center. 4 The sections in all research proposals are essentially the same although different terminology and other specific sections may be used depending on the subject.  

Structure of a Research Proposal  

If you want to know how to make a research proposal impactful, include the following components:¹  

1. Introduction  

This section provides a background of the study, including the research topic, what is already known about it and the gaps, and the significance of the proposed research.  

2. Literature review  

This section contains descriptions of all the previous relevant studies pertaining to the research topic. Every study cited should be described in a few sentences, starting with the general studies to the more specific ones. This section builds on the understanding gained by readers in the Introduction section and supports it by citing relevant prior literature, indicating to readers that you have thoroughly researched your subject.  

3. Objectives  

Once the background and gaps in the research topic have been established, authors must now state the aims of the research clearly. Hypotheses should be mentioned here. This section further helps readers understand what your study’s specific goals are.  

4. Research design and methodology  

Here, authors should clearly describe the methods they intend to use to achieve their proposed objectives. Important components of this section include the population and sample size, data collection and analysis methods and duration, statistical analysis software, measures to avoid bias (randomization, blinding), etc.  

5. Ethical considerations  

This refers to the protection of participants’ rights, such as the right to privacy, right to confidentiality, etc. Researchers need to obtain informed consent and institutional review approval by the required authorities and mention this clearly for transparency.  

6. Budget/funding  

Researchers should prepare their budget and include all expected expenditures. An additional allowance for contingencies such as delays should also be factored in.  

7. Appendices  

This section typically includes information that supports the research proposal and may include informed consent forms, questionnaires, participant information, measurement tools, etc.  

8. Citations  

Important Tips for Writing a Research Proposal  

Writing a research proposal begins much before the actual task of writing. Planning the research proposal structure and content is an important stage, which if done efficiently, can help you seamlessly transition into the writing stage. 3,5  

The Planning Stage  

• Manage your time efficiently. Plan to have the draft version ready at least two weeks before your deadline and the final version at least two to three days before the deadline.
• What is the primary objective of your research?  
• Will your research address any existing gap?  
• What is the impact of your proposed research?  
• Do people outside your field find your research applicable in other areas?  
• If your research is unsuccessful, would there still be other useful research outcomes?  

  The Writing Stage  

• Create an outline with main section headings that are typically used.  
• Focus only on writing and getting your points across without worrying about the format of the research proposal , grammar, punctuation, etc. These can be fixed during the subsequent passes. Add details to each section heading you created in the beginning.   
• Ensure your sentences are concise and use plain language. A research proposal usually contains about 2,000 to 4,000 words or four to seven pages.  
• Don’t use too many technical terms and abbreviations assuming that the readers would know them. Define the abbreviations and technical terms.  
• Ensure that the entire content is readable. Avoid using long paragraphs because they affect the continuity in reading. Break them into shorter paragraphs and introduce some white space for readability.  
• Focus on only the major research issues and cite sources accordingly. Don’t include generic information or their sources in the literature review.  
• Proofread your final document to ensure there are no grammatical errors so readers can enjoy a seamless, uninterrupted read.  
• Use academic, scholarly language because it brings formality into a document.  
• Ensure that your title is created using the keywords in the document and is neither too long and specific nor too short and general.  
• Cite all sources appropriately to avoid plagiarism.  
• Make sure that you follow guidelines, if provided. This includes rules as simple as using a specific font or a hyphen or en dash between numerical ranges.  
• Ensure that you’ve answered all questions requested by the evaluating authority.  

Key Takeaways   

Here’s a summary of the main points about research proposals discussed in the previous sections:  

• A research proposal is a document that outlines the details of a proposed study and is created by researchers to submit to evaluators who could be research institutions, universities, faculty, etc.  
• Research proposals are usually about 2,000-4,000 words long, but this depends on the evaluating authority’s guidelines.  
• A good research proposal ensures that you’ve done your background research and assessed the feasibility of the research.  
• Research proposals have the following main sections—introduction, literature review, objectives, methodology, ethical considerations, and budget.  

Frequently Asked Questions  

Q1. How is a research proposal evaluated?  

A1. In general, most evaluators, including universities, broadly use the following criteria to evaluate research proposals . 6  

• Significance —Does the research address any important subject or issue, which may or may not be specific to the evaluator or university?  
• Content and design —Is the proposed methodology appropriate to answer the research question? Are the objectives clear and well aligned with the proposed methodology?  
• Sample size and selection —Is the target population or cohort size clearly mentioned? Is the sampling process used to select participants randomized, appropriate, and free of bias?  
• Timing —Are the proposed data collection dates mentioned clearly? Is the project feasible given the specified resources and timeline?  
• Data management and dissemination —Who will have access to the data? What is the plan for data analysis?  

Q2. What is the difference between the Introduction and Literature Review sections in a research proposal ?  

A2. The Introduction or Background section in a research proposal sets the context of the study by describing the current scenario of the subject and identifying the gaps and need for the research. A Literature Review, on the other hand, provides references to all prior relevant literature to help corroborate the gaps identified and the research need.  

Q3. How long should a research proposal be?  

A3. Research proposal lengths vary with the evaluating authority like universities or committees and also the subject. Here’s a table that lists the typical research proposal lengths for a few universities.  

Q4. What are the common mistakes to avoid in a research proposal ?  

A4. Here are a few common mistakes that you must avoid while writing a research proposal . 7  

• No clear objectives: Objectives should be clear, specific, and measurable for the easy understanding among readers.  
• Incomplete or unconvincing background research: Background research usually includes a review of the current scenario of the particular industry and also a review of the previous literature on the subject. This helps readers understand your reasons for undertaking this research because you identified gaps in the existing research.  
• Overlooking project feasibility: The project scope and estimates should be realistic considering the resources and time available.   
• Neglecting the impact and significance of the study: In a research proposal , readers and evaluators look for the implications or significance of your research and how it contributes to the existing research. This information should always be included.  
• Unstructured format of a research proposal : A well-structured document gives confidence to evaluators that you have read the guidelines carefully and are well organized in your approach, consequently affirming that you will be able to undertake the research as mentioned in your proposal.  
• Ineffective writing style: The language used should be formal and grammatically correct. If required, editors could be consulted, including AI-based tools such as Paperpal , to refine the research proposal structure and language.  

Thus, a research proposal is an essential document that can help you promote your research and secure funds and grants for conducting your research. Consequently, it should be well written in clear language and include all essential details to convince the evaluators of your ability to conduct the research as proposed.  

This article has described all the important components of a research proposal and has also provided tips to improve your writing style. We hope all these tips will help you write a well-structured research proposal to ensure receipt of grants or any other purpose.  

References  

• Sudheesh K, Duggappa DR, Nethra SS. How to write a research proposal? Indian J Anaesth. 2016;60(9):631-634. Accessed July 15, 2024. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5037942/  
• Writing research proposals. Harvard College Office of Undergraduate Research and Fellowships. Harvard University. Accessed July 14, 2024. https://uraf.harvard.edu/apply-opportunities/app-components/essays/research-proposals  
• What is a research proposal? Plus how to write one. Indeed website. Accessed July 17, 2024. https://www.indeed.com/career-advice/career-development/research-proposal  
• Research proposal template. University of Rochester Medical Center. Accessed July 16, 2024. https://www.urmc.rochester.edu/MediaLibraries/URMCMedia/pediatrics/research/documents/Research-proposal-Template.pdf  
• Tips for successful proposal writing. Johns Hopkins University. Accessed July 17, 2024. https://research.jhu.edu/wp-content/uploads/2018/09/Tips-for-Successful-Proposal-Writing.pdf  
• Formal review of research proposals. Cornell University. Accessed July 18, 2024. https://irp.dpb.cornell.edu/surveys/survey-assessment-review-group/research-proposals  
• 7 Mistakes you must avoid in your research proposal. Aveksana (via LinkedIn). Accessed July 17, 2024. https://www.linkedin.com/pulse/7-mistakes-you-must-avoid-your-research-proposal-aveksana-cmtwf/  

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Are Underwater UFOs an Imminent Threat? The U.S. Government Sure Thinks So—And Here’s the Proof

Legislators went so far as to formally change the way they refer to UFO sightings over and under bodies of water.

Claims of such Unidentified Submerged Objects , or USOs, have intrigued UFO enthusiasts for decades. Based on eyewitness reports, some of the objects have even seemed to traverse the boundary between air and water, traveling at shocking speeds of hundreds of miles per hour.

A small group of UFO devotees, including government security and military officials, have believed for years that the U.S. should be seriously looking into potentially threatening anomalies in bodies of water, as well on land and in the air. In a bipartisan effort, that group ultimately helped convince the U.S. government to legislate a name change for the term it uses to refer to UFOs today—from “Unidentified Aerial Phenomena” to “Unidentified Anomalous Phenomena,” reflecting lobbyists’ concerns about underwater threats.

The slight name change may appear to be a simple case of semantics, but it proves the Pentagon sees underwater UFOs as a legitimate concern.

The Department of Defense has made it clear that it doesn’t assume UAPs necessarily indicate extraterrestrial activity. In fact, these phenomena have so far proven to have mundane explanations. These include human-made technology like drones and weather balloons, Starlink satellites , or atmospheric events such as lenticular cloud formations.

The Government’s Name Game

A shift in how the government handled UFO reports first came to a head in the 2010s. Pressure from legislators, as well as public interest in the government’s disclosure of classified UFO reports , started changing defense culture. For instance, after decades of shielding information on sightings from the public, the military now encourages service members to report unexplained phenomena. Today, Navy pilots report odd incidents in the interest of national defense, such as the 2019 sighting by a Navy warship that seemed to link UFOs and USOs.

In 2021, the Department of Defense created the Unidentified Aerial Phenomena Task Force, a program within the U.S. Office of Naval Intelligence meant to “standardize collection and reporting” of UFO sightings. Aiming to integrate knowledge and efforts across the Pentagon and other government agencies, the Office of the Secretary of Defense established the All-Domain Anomaly Resolution Office (AARO) soon afterward. By law, every federal agency must “review, identify, and organize each Unidentified Anomalous Phenomena (UAP) record in its custody for disclosure to the public and transmission to the National Archives.”

Prior to the 2022 National Defense Authorization Act—which authorizes funding levels for the U.S. military and other defense priorities—UAP originally stood for only aerial objects. Now, it includes underwater and trans-medium phenomena. It’s why AARO was so named, to investigate “All-domain” anomalies. But, before the legal name change, AARO was already considering objects over and in the water—so it was a little confusing to keep calling them all “aerial.”

In 2022, the terminology to describe unexplained incidents officially switched from “aerial” to “anomalous.” Congress enacted the name change that December. At the time, Ronald Moultrie, the Under Secretary of Defense for Intelligence and Security told a roundtable of AARO:

“You may have caught that I just said unidentified anomalous phenomena, whereas in the past the department has used the term unidentified aerial phenomena. This new terminology expands the scope of UAP to include submerged and trans-medium objects. Unidentified phenomena in all domains, whether in the air, ground, sea or space, pose potential threats to personnel security and operations security, and they require our urgent attention.”

This legal change traces back to pressures from UFO enthusiasts who believed submerged and trans-medium objects, which seem to fly between air and sea, should be included in the government’s potential threat evaluation. These proponents include U.S. Navy Rear Admiral Tim Gallaudet, Ph.D., who published a report on the potential maritime threat of USOs, and Luis Alizondo , who once ran the government’s secret Pentagon unit, the 2007–12 Advanced Aerospace Threat Identification Program. A dearth of data about USOs and UAPs is “unsettling,” because they “jeopardize US maritime security, which is already weakened by our relative ignorance about the global ocean,” Rear Admiral Gallaudet wrote in his report. In addition, this is an opportunity to expand maritime science and meet the security and scientific challenges of the future, he added.

The Hunt For Solid Evidence

Yet, evidence of submerged objects is murky at best, says UAP investigator Mick West. There is “vastly less evidence than for flying objects,” he explains in an email. “You can’t see very far underwater, so there’s no video or photos. There are only stories about anomalous sonar returns and occasional sightings that might as well be of sea monsters.”

The Puerto Rico “Aguadilla” incident of 2013 also influenced USO and trans-medium enthusiasts, West says. However, they base their claim largely on one video of the incident, which when analyzed turns out to have “a perfectly reasonable explanation of two wedding lanterns and parallax illusions,” West says.

Based on the angle of the camera, positioned on a moving airplane, and consequently its changing line of sight on the flying objects, the viewer sees the objects streaking rapidly over the ocean, apparently diving in, and then emerging again. West’s analysis confirms a theory first proposed by Rubén Lianza, the head of the Argentinian Air Force’s UAP investigation committee.

The objects were wedding lanterns that originated at a nearby hotel and floated on the wind. Lianza confirmed the hotel typically released lanterns that were consistent with the video. The thermal camera (which reads heat) made it appear that the objects merged with the ocean because when the lantern’s flames were hidden, they were about the same temperature as the water they floated over. At the same time, the lanterns seemed to emerge from the water when the flame was visible again.

New trans-medium and submerged UAP reports could crop up in the future. The government will only be able to take reports of strange underwater lights or objects flying out of the water seriously, says West, if the sightings come with enough solid evidence to follow up with a solid analysis.

Before joining Popular Mechanics , Manasee Wagh worked as a newspaper reporter, a science journalist, a tech writer, and a computer engineer. She’s always looking for ways to combine the three greatest joys in her life: science, travel, and food.

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For example, searching Year Published = 2022, will return items with Final Publication Year of 2022 and any items with Published Early Access Year of 2022.

This will also impact the years displayed for Refine an Analyze Results. In the case where an item's Published Early Access Year is different from the Final Publication Year, the Published Early Access year will be used for both Refine and Analyze. Thus, a search of Year Published=2021 may show a Refine Results for Publication year with items listed for 2019, 2020 and 2021.

Search the Address fields by entering the full or partial name of an institution and/or location from an author's address. For example, Univ and University finds institutions in which the term "Univ" appears in the Addresses field within a record.

When entering full names, do not use articles (a, an, the) and prepositions (of, in, for) in the name. For example, entering UNIV Pennsyvania is OK but entering University of Pennsylvania results in an error message.

Note that common address terms may be abbreviated in the product database. For example, the word Department may be abbreviated as Dept or Dep.

We recommend that you combine an Address search with an Author search to broaden or narrow your search results.

Note: In Web of Science Core Collection and Current Contents Connect records, a superscript number may appear after an author's name in a Full Record. This means we have found an association between the author's name and the author's address. When you click the number link, the system takes you to the Addresses field where you can see the author's address.

Address Synonyms and Abbreviations

Common address terms and many institution names are abbreviated in the product database.

Terms such Univ, Med, and Phys must be entered as part of an address phrase. For example, Penn State Univ is acceptable, but Univ alone is not.

About Older Records:

Older records may not have addresses associated with a record.

Search for preferred organization names and/or their name variants from the Preferred Organization Index.

Enter complete names or partial names using wildcards (* $ ?). When searching for multiple preferred names or multiple name variants, separate the names using the OR Boolean operator.

Booleans in Organization Names

When searching for organization names that contain a Boolean (AND, NOT, NEAR, and SAME), always enclose the word in quotation marks ( " " ). For example:

(Japan Science "and" Technology Agency (JST))

("Near" East Univ)

("OR" Hlth Sci Univ)

You can also enclose the entire query in quotation marks. For example:

"Japan Science and Technology Agency (JST)"

"Near" East Univ"

"OR Hlth Sci Univ"

rganizations - Enhanced List

Select the search aid to go to the Organization-Enhanced List where you can view and select preferred organization names and/or their variants.

Selecting the preferred name from the search aid generally returns more precise and accurate results.

Selecting a variant from the search aid executes a search that includes the preferred name and the name variant.

Searching - Preferred Name

Selecting a preferred name from the search aid, or entering a preferred name in the Organization-Enhanced field, returns all records with addresses linked to the preferred name.

For example, the preferred name Columbia University returns all records that include Columbia Univ and any of the variants in the address of a record such as:

Yale Univ, New Haven, CT 06520 USA

Columbia Univ, New York, NY 10027 USA

Data in the Organization-Enhanced List

Due to timing differences between when records are loaded and when the search aid is refreshed, you may not see a particular name variant. Likewise, a variant may be listed in the search aid but retrieve no records because the address in the record has been corrected.

The Conference field allows you to search for records of conference proceedings.

You must have a subscription to one or both Conference Proceedings citation indexes to search for and to view conference records.

The Conference field allows you to search the following fields within a record for conference proceedings papers.

Conference Title

Conference Location

Conference Date

Conference Sponsor

Enter one or more terms connected with search operators (AND, OR, NOT, NEAR). Enter complete words and phrases or partial words and phrases using wildcards (* $ ?).

Use the AND search operator to combine search terms in the Conference field.

Often, just one or two words connected by AND will be enough to search for a particular meeting.

For example, lithium AND Scotland AND 1998 find records of papers from the 9th International Meeting on Lithium Batteries, Edinburgh, Scotland, July 12-17, 1998.

Records in this product include a language indicator that categorizes documents by the language in which they are written.

To restrict your search, select one or more languages from the list. The default selection is All languages.

All languages

Byelorussian

Multi-Language

Serbo-Croatian

Unspecified

When you limit a search by document type, you retrieve only those records that contain the search term(s) you entered in the search fields and the document type(s) you selected from the list.

A search by document type should be combined with a search by another field such as Topic or Author.

Document Type Descriptions

Article: Reports of research on original works. Includes research papers, features, brief communications, case reports, technical notes, chronology, and full papers that were published in a journal and/or presented at a symposium or conference.

Abstract of Published Item: Bibliographic-only data on a published paper. Generally finds records dating back to 1974 or before.

Art Exhibit Review: Reviews of gallery or museum showings of artworks.

Bibliography: A list, often with descriptive or critical notes, of writings relating to a particular subject.

Biographical-Item: Obituaries, articles focusing on the life of an individual, and articles that are tributes to or commemorations of an individual.

Book: A monograph or publication written on a specific topic.

Book Chapter: A monograph or publication written on a specific topic within a main division in a book.

Book Review: A critical appraisal of a book (often reflecting a reviewer's personal opinion or recommendation) that evaluates such aspects as organization and writing style, possible market appeal, and cultural, political, or literary significance.

Chronology: A review of events on a specific topic or subject in their order of occurrence in time.

Correction: Correction of errors found in articles that were previously published and which have been made known after that article was published. Includes additions, errata, and retractions.

Correction, Addition: Correction of errors found in articles that were previously published and which have been made known after that article was published. Includes additions, errata, and retractions.

Dance Performance Review: Reviews of solo dance recitals, complete dance productions, dance programs consisting of several works, and other types of performed dances.

Data Paper: A scholarly publication describing a particular dataset or collection of datasets and usually published in the form of a peer-reviewed article in a scholarly journal. The main purpose of a data paper is to provide facts about the data (metadata, such as data collection, access, features etc) rather than analysis and research in support of the data, as found in a conventional research article.

Database Review: A critical appraisal of a database, often reflecting a reviewer's personal opinion or recommendation. Refers to a structured collection of records or data that is stored in a computer system.

Discussion: An article or paper that discusses questions in an open and usually informal debate. Generally finds records dating back to 1996 or before.

Early Access: An article that has been electronically published by a journal before it has been assigned to a specific volume and issue.

Editorial Material: An article that gives the opinions of a person, group, or organization. Includes editorials, interviews, commentary, and discussions between individual, post-paper discussions, round table symposia, and clinical conferences.

Excerpt: A selection from or a fragment of a literary or musical work, which cannot stand as a separate work in its own right.

Expression of Concern: An "Expression of Concern" is a notification about the integrity of a publication that is typically written by and editor. The outcome may result in a retraction or a correction.

Fiction, Creative Prose: Includes short stories and other works of creative prose.

Film Review: A review of a motion picture.

Hardware Review: A critical appraisal of computer hardware, often reflecting a reviewer's personal opinion or recommendation. Refers to objects that you can actually touch, like disk drives, keyboards, printers.

Item About An Individual: A review of the work(s) of a celebrated person in a particular field of study.

Item Withdrawal: A published statement from an editor or author announcing the withdrawal of a manuscript and the reason for the withdrawal. It must state in the title/text of that the publication is being withdrawn.

Letter: Contributions or correspondence from the readers to the journal editor concerning previously published material.

Meeting Abstract: A general summation of completed papers that were or will be presented at a symposium or conference.

Meeting Summary: A paper that covers multiple meeting abstracts in a variety of subjects.

Music Performance Review: Review of a live musical performance (recital, concert, and opera).

Music Score: Transcript of the original and entire draft of a musical composition or an arrangement with the parts for the different instruments or voices written on staffs one above another.

Music Score Review: Review of a bound musical composition or bound collection of musical compositions.

News Item: News, current events, and recent developments.

Note: A paper that mentions or remarks on a published paper on a specific subject. Generally finds records dating back to 1996 or before.

Poetry: Compositions in verse; metrical writing.

Proceedings Paper: Published literature of conferences, symposia, seminars, colloquia, workshops, and conventions in a wide range of disciplines. Generally published in a book of conference proceedings.

Records covered in the two Conference Proceedings indexes (CPCI-S and CPCI-SSH) are identified as Proceedings Paper. However, the same records covered in the three indexes (SCI-E, SSCI, and A&HCI) are identified as Article when published in a journal.

Publication with Expression of Concern: The original publication that is subject of the publisher's Expression of Concern

Record Review: Reviews of recorded music or speech.

Reprint: An article that was previously published.

Retracted Publication: An article that has been withdrawn by an author, institution, editor, or a publisher because of errors or unsubstantiated data.

Retraction: A public notice that an article should be be withdrawn because of errors or unsubstantiated data.

Review: A renewed study of material previously studied. Includes review articles and surveys of previously published literature. Usually will not present any new information on a subject.

Script: includes film scripts, plays, TV, and radio scripts.

Software Review: A critical appraisal of computer software, often reflecting a reviewer's personal opinion or recommendation. Refers to programs, procedures, and rules, along with associated documentation pertaining to the operation of a computer system.

Theater Review: Review of a performed play.

TV Review, Radio Review: Reviews of television and radio broadcasts.

TV Review, Radio Review, Video Review: Reviews of television, radio broadcasts, and videos.

Withdrawn Publication: The original publication that is being withdrawn

Did You Know ...

Some records in Web of Science may have two document types: Article and Proceedings Paper.

An Article is generally published in a journal. A Proceedings Paper is generally published in a book of conference proceedings. Records covered in the two Conference Proceedings indexes (CPCI-S and CPCI-SSH) are identified as Proceedings Paper. The same records covered in the three indexes (SCI-E, SSCI, and A&HCI) are identified as Article when published in a journal.

Search for funding agency names from the Funding Agency search field. The index contains both the original funding agency name, the preferred funding agency name, and parent agency (when available).

You can enter the full name of an agency. For example:

"National Agency for the Promotion of Science and Technology"

Or, you can enter specific terms that form an agency's name. For example:

National Agency AND Science

Use both the full name of the funding agency and the agency's initials to find all instances of the agency. For example:

Japan Society for the Promotion of Science OR JSPS

Booleans in Funding Agency Names

When searching for funding agency names that contain a Boolean (AND, NOT, NEAR, and SAME), always enclose the word in quotation marks (“ “). For example:

"Near" East Univ

Danish Agency for Science, Technology "and" Innovation

"Near East Univ"

"Danish Agency for Science, Technology and Innovation

Preferred Funding Agency List

Use the Preferred Funding Agency list to see the funding agency names that have been unified.

Copying a preferred name from the list into a Funding Agency search returns all records with funding agencies that map to that preferred name.

Data in the Preferred Funding Agency List

Due to timing differences between when records are loaded and when list is refreshed, you may not see a particular preferred name in the list.

Grant information comes from articles in journals covered by Web of Science Core Collection. Grant information indexing began in 2008.

Grant information is publicly available on many Web sites such as PubMed. You can find additional information by entering the grant number when performing a search. For example, a search on "Swiss National Science Foundation" in PubMed finds articles written by researchers from institutions funded by this agency.

In 2016 Web of Science Core Collection began supplementing the grant information with grant agencies and grant numbers from MEDLINE and researchfish®. Records that already contained grant information will not be changed. Records that did not have grant information were updated with grant information from MEDLINE and researchfish®.

Enter a grant number to search the Grant Number field within the Funding Acknowledgment table within a record.

Enter a full or partial grant number. If you enter a partial grant number, end it with the asterisk (*) wildcard. Join multiple grant numbers by the OR Boolean operator.

Note that some grant numbers will find the same record. For example, 9871363 OR 05168 finds the same record.

The accession number is a unique identifying number associated with each record in the product. It consists of an accession number (a product identification code) and a sequence number.

Always join multiple numbers by the OR Boolean operator. Do not use AND, NOT, NEAR, and SAME when searching for accession numbers: the product will return an error message.

Enter a unique accession number to find a specific record. For example, WOS:000301236900016 finds the record that is associated with this unique accession number.

Enter a partial accession number and include an asterisk (*) wildcard at the end. For example, WOS:0003012369* finds all records that begin with this accession number (the example does not include the sequence number), such as:

WOS:000301236900001

WOS:000301236900002

WOS:000301236900003

And so on ...

Enter a partial accession number and include both left-hand and right-hand truncation. For example, *12369* finds all records that contains these numbers in the accession number.

The PubMed ID is a unique identifier assigned to each MEDLINE record. For example, 14847410 finds the record with PubMed ID 14847410.

The search 148474* finds MEDLINE records with a PubMed ID starting with 148474.

Use the OR operator to search for multiple PubMed IDs. For example, 14847410 OR 23455055 finds records that contain the PubMed ID 14847410 or the PubMed ID 23455055. You cannot combine multiple PubMed IDs using the operator AND, NOT, NEAR or SAME.

The advantage of searching Web of Science Core Collection or Current Contents Connect by PubMed ID is that you can get the addresses of all authors of an article. MEDLINE supplies the address of the first listed author of an article.

Cited Reference Fields

Use the following guidelines when performing a Cited Author search.

Enter the name of the first author of a multi-authored article, book, data study or patent. Cited references from older articles or articles that do not have matching source records may only include the name of the first author.

You may enter the name of a secondary author. The name of a secondary author is preceded by ellipses (...) in the index.

Enter a last name with a space and at least one initial. Always use a wildcard (* $ ?) after the intial(s) to find all variants of an author's name. For example, Lee FN*

You may enter multiple names separated by a Boolean operator (AND, OR, NOT).

Cited authors include corporate authors and inventors.

If the citation refers to a record that is also a source item published during the timespan covered by your institution's subscription, you can enter the name of any of its authors.

For example, if you are looking for cited references to a work called "Preventing the use of biological weapons: Improving response should prevention fail," published in Clinical Infectious Diseases 30 (6): 926-929 June 2000, then you can enter the name of any of the three authors of the article: Inglesby TV, O'Toole T, or Henderson DA. Ellipses (...) will appear before the name of a secondary author in the Cited Reference Index.

However, it is advisable to enter the name of the first listed author in the Cited Author field. That way, you will be sure to retrieve all variations of the same cited reference.

Guidelines for Entering Names

Enter up to three initials after the last name. It is advisable to truncate after the first initial. For example:

Enter Evans PJ to retrieve references with Evans PJ as a cited author. This search will find references where the full first name of the cited author may be abbreviated as PJ, including

Evans Patrick J.

Evans Paul J.

Enter Evans P* to retrieve references with a cited author whose surname is Evans and whose first initial is P or whose first name begins with P, including:

Use upper, lower, or mixed case. For example, CRICK, Crick, or crick finds the same results.

Use the asterisk (*) wildcard to represent any number of characters. For example, Aglitsk* matches Aglitskaya, Aglitski, Aglitskii, Aglitskiy.

Use the question mark (?) to represent one character. For example, Bens?n C* matches Bensen C, Benson C, Bensen CA, Benson CS, and so on.

Boolean Search Operators

Separate two or more names by the OR Boolean operator.

If the cited author has a common last name, try combining variations with OR instead of truncating after the first initial. This way, you will retrieve fewer irrelevant references. For example:

Enter Calvin W* OR Brown M* to look up cited references with either of these authors as the cited author.

Enter Brown M* OR Brown ME* to look up cited references with Brown M or Brown ME as the cited author.

Enter Brown M* to look up cited references that match Brown M, Brown MA, Brown MB, Brown ME, and so on.

Quotation Marks

Use quotation marks (") around the words AND, OR, NOT, NEAR, and SAME in any field when you do not intend these words to serve as search operators.

Enter "OR" W* to search for cited works authored by William Or.

Enter Koechli "OR" to search for works authored by O. R. Koechli.

Enter Food "and" Drug Administration or "Food and Drug Adminstration" to search for cited works authored by this agency.

Hyphens and Apostrophes

If the surname contains a hyphen, or apostrophe, enter the name both with and without the punctuation mark. Likewise, enter a surname with embedded spaces with and without the spaces.

Join the two versions of the name with OR.

Obrien R* OR O'Brien R*

Lopez-Gonzalez J* OR Lopezgonzalez J*

Deville A* OR De Ville A*

If the surname is longer than fifteen characters, enter the first fifteen characters followed by an asterisk (*) wildcard to represent the remaining characters. For example, Klapdor-Kleingrothaus* OR KlapdorKleingro* matches

KlapdorKleingrothaus HV

Klapdor-Kleingrothaus HV

Klapdorkleingro.H

Klapdorkleingro.HK

Klapdorkleingro.HV

About Cited Author Names

For cited references, both the primary and secondary author are listed.

Cited Author Search Tips

To search for anonymous authors, enter anonymous in the Cited Author field.

To search on the name AND, OR, NOT, NEAR, and SAME, enclose the name in quotation marks. Example: "Or"

The Cited Reference Index may display a shortened version of the name you entered. Regardless, enter the full last name of the author. The search engine automatically adjusts for data variations.

Search for cited works such as cited journals, cited conferences, cited books, and cited book chapters.

Enter an abbreviated journal title or look up abbreviations for cited works in the Journal Title Abbreviations list.

Be aware that there may be more than one abbreviation for a journal. Use truncation to match variations of several abbreviations for the same title. Join multiple journal titles with the search operator OR.

Note: When searching for cited conferences, include the title, location, date, and sponsor.

Enter Mark* Sci* to find titles of cited works published in Marketing Science.

Enter Geol* to find titles of cited works published in Geology, Geology Journal (abbreviated as Geol J) and other publications beginning with Geol.

Enter J Mech* Mat* Struct* to find titles of cited works published in J Mech Mat Struct, J Mech Mats Structs, J Mech Mater Struct, and so forth.

Important Note: We recommend that you use an asterisk (*) wildcard in your search query; otherwise, the product may return an incomplete list of results or no results.

Searching for Book Titles as Cited Works

Enter the first significant word or words from the title of the book. It is advisable to truncate because of variant spellings. Always truncate the last word in your search query using an asterisk (*) wildcard; otherwise, your search may return an incomplete list of results or no results. Keep in mind that titles of cited works may be in languages other than English.

Enter Medieval Boundaries* to find works and authors who cited Medieval Boundaries: Rethinking Difference in Old French Literature.

Enter Courtly Love Undressed* to find works and authors who cited Courtly Love Undressed: Reading Through Clothes in Medieval French Culture.

Enter a four-digit year or a limited range of years. For optimal performance, limit the range to two or three years.

Search for a cited year only in combination with a search for a cited author and/or cited work.

Also, even if you know the cited year, try searching for references without specifying the cited year. Often, variations of the same cited reference—particularly references to books—will show different years.

Search for cited works by entering search terms in the following fields.

Cited Volume

Cited Issue

Cited page may include numbers (for example, C231 or 2832) or Roman numerals (for example, XVII). Always use the starting page of a publication. Do not use page ranges.

As a rule, you should avoid specifying the the cited volume, issue and pages in step 1 of a cited reference search. You want to be certain to retrieve all variations of the same reference. Generally, the name of the cited author and the abbreviated cited work are sufficient to perform step 1 successfully.

You may enter a full title, a partial title, or one or more individual terms from the title. Combine individual terms with search operators (AND, OR, NOT, NEAR). Use wildcards (* $ ?) to find variant spellings or both singular and plural forms of words.

For example, each of the following searches finds the reference to Troshkova, G.P. et al. 2001. Improvement of the Technique for Producing media for cell culturing on the basis of enzymatic hydrolysates of soy and rice flour. Biotechnology in Russia. 2006. Iss. 4. Pages 74-78.

Cited Title: Improvement of the Technique for Producing media for cell culturing on the basis of enzymatic hydrolysates of soy and rice flour

Cited Author: Troshkova G*

Cited Work: Biotechnology in Russia

Cited Title: enzymatic hydrolysates