Issue Merging WoS and Scopus Data for VOSviewer Analysis
Varimna Singh
Dear Neeraj Sir,
I am trying to merge Web of Science (WoS) and Scopus databases to perform bibliometric analysis using VOSviewer. I was able to merge the files using Biblioshiny; however, the merged output is not compatible with VOSviewer.
Specifically, VOSviewer is not recognizing certain fields in the merged file. For example, the author keywords field appears as “KW_merged” in the Biblioshiny output, which is not identified correctly by VOSviewer during import. As a result, I am unable to proceed with the intended analysis.
Could you please suggest an alternative method to merge WoS and Scopus datasets in a way that ensures compatibility with VOSviewer? If there are recommended preprocessing steps or export settings that I should follow, I would greatly appreciate your guidance.
Thank you for your time and support.
Regards,
Varimna
NEELAM KAUSHAL
--
The members of this group are expected to follow the following Protocols:
1. Please search previous posts in the group before posting the question.
2. Don't write the query in someone's post. Always use the option of New topic for the new question. You can do this by writing to dataanaly...@googlegroups.com
3. It’s better to give a proper subject to your post/query. It'll help others while searching.
4. Never write Open-ended queries. This group intends to help research scholars, NOT TO WORK FOR THEM.
5. Never write words like URGENT in your posts. People will help when they are free.
6. Never upload any information about National Seminars/Conferences. Send such information
in personal emails and feel free to share any RESEARCH-related information.
7. No Happy New Year, Happy Diwali, Happy Holi, Happy Birthday, Happy Anniversary, etc. allowed in this group.
8. Asking or sharing Research Papers is NOT ALLOWED.
9. You can share your questionnaire only once.
---
You received this message because you are subscribed to the Google Groups "DataAnalysis" group.
To unsubscribe from this group and stop receiving emails from it, send an email to dataanalysistrai...@googlegroups.com.
To view this discussion visit https://groups.google.com/d/msgid/dataanalysistraining/CABpDJ_RJnqTiK96u2Qt872%2BnDUbhzXeTY7h0iy6XMEB59RjCvg%40mail.gmail.com.
Varimna Singh
NEELAM KAUSHAL
To view this discussion visit https://groups.google.com/d/msgid/dataanalysistraining/CABpDJ_QKgNFvz1uxsb5wmfXZedpYQPATuhPxUK5ykZgjijBiYw%40mail.gmail.com.
Prasant Barla
Dear Dr. Neelam Kaushal,
Thank you for your query regarding the merging of Web of Science (WoS) and Scopus databases for bibliometric analysis in VOSviewer.
After extensive testing, I would like to inform you that merging datasets using Biblioshiny—or even through coding within the bibliometrix package in R—does not consistently generate a merged output that is fully compatible with VOSviewer. The issue arises because the merged file restructures and renames key bibliographic fields (for example, author keywords appearing as “KW_merged”), which VOSviewer does not recognize during import. As a result, certain essential fields such as Author Keywords, Affiliations, and References are not correctly identified.
Based on well-tested procedures, the most reliable method to achieve a VOSviewer-compatible merged dataset is through Python-based preprocessing. Using Python allows precise control over field harmonization, standardization of column names, and restructuring of bibliographic records to match the format expected by VOSviewer. This approach has been thoroughly tested and produces stable, compatible outputs for mapping and network analysis.
I have attached the Python code used for this process for your reference. You may follow the same workflow to generate a merged dataset that VOSviewer can read without errors.
Please feel free to reach out if you need any clarification while implementing the procedure.
Thank you for your time and support.
Kind regards,
P. Barla
Asst. Professor in Management
VSSUT, Burla
Varimna Singh
Varimna Singh
NEELAM KAUSHAL
Varimna Singh
To view this discussion visit https://groups.google.com/d/msgid/dataanalysistraining/CAGHvruKLXL045p4EfYD5pyr-bkHw-NptPf3Zz2RYaX9zTkoiiA%40mail.gmail.com.
Varimna Singh
Thank you for providing the code for merging the WoS and Scopus databases. The script worked correctly, and the merged file is now compatible with VOSviewer.
However, I have noticed a discrepancy in the total number of records. When we merged the databases using Biblioshiny, the final dataset contained 310 documents. In contrast, the Python-based merge produced only 251 documents. This difference is substantial and suggests that the two approaches may be applying different deduplication or matching criteria.
Could you please advise on the possible reason for this variation?
Sunil Chawla
--
Varimna Singh
Sunil Chawla
| WoS Columns | Scopus Columns | ||
| 1 | Publication Type | 1 | Authors |
| 2 | Authors | 2 | Author full names |
| 3 | Book Authors | 3 | Author(s) ID |
| 4 | Book Editors | 4 | Title |
| 5 | Book Group Authors | 5 | Year |
| 6 | Author Full Names | 6 | Source title |
| 7 | Book Author Full Names | 7 | Volume |
| 8 | Group Authors | 8 | Issue |
| 9 | Article Title | 9 | Art. No. |
| 10 | Source Title | 10 | Page start |
| 11 | Book Series Title | 11 | Page end |
| 12 | Book Series Subtitle | 12 | Page count |
| 13 | Language | 13 | Cited by |
| 14 | Document Type | 14 | DOI |
| 15 | Conference Title | 15 | Link |
| 16 | Conference Date | 16 | Affiliations |
| 17 | Conference Location | 17 | Authors with affiliations |
| 18 | Conference Sponsor | 18 | Abstract |
| 19 | Conference Host | 19 | Author Keywords |
| 20 | Author Keywords | 20 | Index Keywords |
| 21 | Keywords Plus | 21 | Molecular Sequence Numbers |
| 22 | Abstract | 22 | Chemicals/CAS |
| 23 | Addresses | 23 | Tradenames |
| 24 | Affiliations | 24 | Manufacturers |
| 25 | Repring Addresses | 25 | Funding Details |
| 26 | Email Addresses | 26 | Funding Texts |
| 27 | Research Ids | 27 | References |
| 28 | ORCIDs | 28 | Correspondence Address |
| 29 | Funding Orgs | 29 | Editors |
| 30 | Funding Name Preferred | 30 | Publisher |
| 31 | Funding Text | 31 | Sponsors |
| 32 | Cited References | 32 | Conference name |
| 33 | Cited Reference Count | 33 | Conference date |
| 34 | Times Cited, Wos Core | 34 | Conference location |
| 35 | Times Cited, All Databases | 35 | Conference code |
| 36 | 180 Day Usage Count | 36 | ISSN |
| 37 | Since 2013 Usage Count | 37 | ISBN |
| 38 | Publisher | 38 | CODEN |
| 39 | Publisher City | 39 | PubMed ID |
| 40 | Publisher Address | 40 | Language of Original Document |
| 41 | ISSN | 41 | Abbreviated Source Title |
| 42 | eISSN | 42 | Document Type |
| 43 | ISBN | 43 | Publication Stage |
| 44 | Journal Abbrevation | 44 | Open Access |
| 45 | Journal ISO Abbrevation | 45 | Source |
| 46 | Publication Date | 46 | EID |
| 47 | Publiation Year | ||
| 48 | Volume | ||
| 49 | Issue | ||
| 50 | Part Number | ||
| 51 | Supplement | ||
| 52 | Special Issue | ||
| 53 | Meeting Abstract | ||
| 54 | Start Page | ||
| 55 | End Page | ||
| 56 | Article Number | ||
| 57 | DOI | ||
| 58 | DOI Link | ||
| 59 | Book DOI | ||
| 60 | Early Access Date | ||
| 61 | Number of Pages | ||
| 62 | WoS Categories | ||
| 63 | Web of Science Index | ||
| 64 | Research Areas | ||
| 65 | IDS Number | ||
| 66 | Pubmed Id | ||
| 67 | Open Access Designations | ||
| 68 | Highly Cited Status | ||
| 69 | Hot Paper Status | ||
| 70 | Date of Export | ||
| 71 | UT (Unique WOS ID) | ||
| 72 | Web of Science Record | ||
--
Sunil Chawla
