Database Querying & Cleaning Using VOSviewer

@TheRSTeam

Hi, I see you need to transform your collection of research records into a clean, analysis-ready dataset for visualisation in VOSviewer. With expertise in data extraction, cleaning, and bibliometric tools like VOSviewer, I will: Craft reliable SQL (or equivalent) queries to extract and combine relational tables and CSV exports without duplication or missing values. Scrub the data by normalising author names, standardising journal titles, fixing date formats, and flagging outliers. Deliver a cleaned master CSV file ready for seamless import into VOSviewer. Provide a walkthrough (screenshots or video) demonstrating the import process and map generation in VOSviewer to ensure you can replicate it independently. Let’s collaborate to deliver a fully functional workflow that runs end-to-end and generates precise co-authorship and keyword maps—I’m ready to start!

@arbu1499

Hello, I can help with this. I have experience consolidating research data from relational tables and CSV sources, writing clean SQL queries to avoid duplication, and preparing analysis-ready datasets for bibliometric tools. I will deliver a fully reproducible query script, a cleaned master CSV with normalized author names, journal titles, and dates, and a short walkthrough showing how to import the file into VOS viewer and generate co-authorship and keyword maps. The focus will be on data accuracy and ensuring the file loads into VOS viewer without warnings or manual fixes. Regards, Arbaz S

@waqaswebmaster

I can help you clean and prepare your dataset for visualization in VOSviewer. Here’s my approach: Steps: Database Querying: I’ll craft reliable SQL queries to extract data from your relational tables and CSV files, ensuring no duplication or missing values. Data Cleaning: I’ll standardize author names, journal titles, and date formats, and flag any outliers to ensure consistency. Visualization Prep: After cleaning, I’ll ensure the data is ready for VOSviewer import without warnings, and generate the necessary co-authorship and keyword maps. Deliverables: SQL Query Script: Fully functional query for data extraction. Master CSV: Cleaned data file for import into VOSviewer. Walkthrough: A brief guide (screenshots or video) showing the VOSviewer import process and map generation. Let me know if you'd like to move forward!

@echekwa

Hi, I can help you take this project from raw records to clean, VOSviewer-ready outputs. I have hands-on experience working with mixed data sources—relational tables and CSV files—using SQL and data-cleaning workflows to ensure nothing is duplicated or lost. I’ll write clear, reusable query scripts to extract and merge the data, then standardise author names, journals, dates, and flag any inconsistencies so the final file loads smoothly into VOSviewer without errors. You’ll receive the full query script, a cleaned master CSV, and a simple walkthrough showing exactly how to import the data and generate co-authorship and keyword maps. Everything will be reproducible end-to-end on your side. Regards, Chijioke

@davig63

Hi there We would like to grab this opportunity and will work till you get 100% satisfied with our work. Please come over chat and discuss your requirement in a detailed way. Regards

@david070154

Hi Santosh, This is a straightforward data engineering plus bibliometric prep workflow, and I can take it from raw tables to a VOS viewer ready dataset. I’ll write reliable SQL queries to merge your relational tables and CSV exports into a single, deduplicated master file, then clean and standardize the data—author names, journal titles, dates, and keywords, so it imports into VOS viewer without errors or warnings. Any anomalies or outliers will be flagged, not hidden. You’ll receive the full query script, a clean master CSV, and a clear walkthrough showing the exact VOS viewer import and map-generation steps, so you can reproduce everything on your end. Once you share the schema and sample files, I’ll confirm the best extraction approach and turnaround time.

@bjorkb

I can immediately deploy my expertise to tackle your project requirements with precision and speed. Your need for a reliable, effective process to consolidate and clean diverse datasets aligns perfectly with my approach to delivering high-quality, timely solutions without duplication or errors. My team and I specialise in data extraction, cleansing, and visualization, ensuring consistent results. I have extensive experience and have completed numerous projects on alternative platforms. is there anything you would like to discuss about your project that you haven't added in the job description? Regards, Bjork Bronkhorst

@sureshk561

I specialize in data extraction, cleansing, and bibliometric preparation for seamless VOSviewer visualization. I’ll consolidate mixed research records from relational tables and CSVs using deduplicated, null-safe queries, then normalize author names, standardize journals, fix dates, and flag outliers to produce an analysis-ready file. Deliverables: End-to-end SQL (or equivalent) script for reproducible extraction Cleaned master CSV ready for VOSviewer (no warnings) Brief walkthrough (screenshots/video) showing import and map generation (co-authorship & keyword maps) Why Me: Strong communication and problem-solving, fast turnaround, and a quality-first approach—your workflow will run cleanly on your side and produce expected VOSviewer maps without manual tweaks.

@lakshmisri1982

Hi, I'm a senior data engineer with 7+ years of experience with skills python, pandas, numpy, sql, pyspark, databricks, airflow and AWS. As a data engineer my daily activities revolve around extracting data from different sources like webpages, csv, text, excel, databases and clean,preprocess, transform and load the data to respective file formats or databases. I understand your requirement of extracting data from relational database and csv files. Will clean the data for any duplicates and normalise the data, will also fix any data type mismatches. Will provide a detailed document for you, so you can work on your system. Happy to connect and discuss about the project.

@harithar24

With my extensive background in data analysis and management, I thrive on such projects that demand intricate transformations of complex datasets. Over the years, I've honed my skills in transforming diverse sets of information into consistent, analysis-ready databases. As a database query expert, I am adept at crafting reliable and efficient scripts that extract pertinent information while eliminating any redundant or missing values. Moreover, cleaning datasets to ensure consistency is second nature to me. I have ample experience in handling multiple data sources and rectifying anomalies like inconsistent author names, varying date formats, and more. With meticulous attention to detail, nothing goes unnoticed under my radar, ensuring your dataset is free from any inconsistencies that may hamper its smooth incorporation into VOSviewer. Finally, my ability to present complex information clearly will prove helpful while providing you with the SQL scripts, a master CSV file as well as a detailed guide on importing and mapping the data using VOSviewer. My aim is to empower you with the knowledge to successfully replicate the process on your end. Let me take charge of transforming your research records into a pristine dataset and visually captivating maps - ultimately delivering invaluable insight from your data!

@tausifraza0786

​"Hi there! ​I saw your project and would love to help you turn your research records into a clean, analysis-ready dataset. I understand that the success of your VOSviewer maps depends entirely on the quality of the initial data extraction and scrubbing. ​How I’ll help you achieve a 'Zero-Warning' result: ​Precision Extraction: I’ll craft SQL queries to pull your relational tables and CSVs together, ensuring we eliminate duplicates and handle missing values right from the start. ​Deep Cleaning: I’ll normalize author names, standardize journal titles, and fix date formats so your file drops into VOSviewer without any manual tweaks or warnings. ​Full Transparency: I will provide the end-to-end SQL script, the master CSV, and a clear video or screenshot walkthrough so you can replicate the map generation process easily. ​My Technical Toolkit: ​SQL & Database Programming: Expert in joining complex tables and ensuring data integrity. ​Data Cleansing: Experienced in using Python or Excel to resolve outliers and inconsistencies. ​Visualization: Familiar with the specific formatting needed for co-authorship and keyword maps in VOSviewer. ​I am committed to accuracy and will ensure the script runs perfectly on your side. I'm ready to start immediately—let’s get your research records organized! ​Best regards, ​Md Tausif R."

@annabellep0

I am a perfect fit for your project, understanding your need for a clean, analysis-ready dataset that integrates relational tables and CSV exports seamlessly. Crafting reliable queries to avoid duplication or missing values, then automating data scrubbing to normalize author names, journal titles, dates, and flag outliers ensures your dataset is user-friendly and ready for VOSviewer without warnings. I offer expertise in SQL scripting, data cleaning, and visualization guidance. While I am new to freelancer, I have tons of experience and have done other projects off site. I would love to chat more about your project! Regards, Annabelle Pretorius

@shubhamv513

Hello, I can help transform your mixed research records into a clean, analysis-ready dataset and visualise it in VOSviewer. I will design reliable SQL queries to integrate relational tables and CSV files while removing duplicates and handling missing values. The data will be cleaned by normalising author names, standardising journal titles, fixing date formats, and flagging outliers to ensure error-free VOSviewer import. Deliverables include the full SQL script, a cleaned master CSV, and a step-by-step walkthrough (screenshots or video) showing data import and map generation so you can replicate the process confidently.