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The evolution, whether in the tech or healthcare industry, is the driving force that is revolutionizing the existing operations. However, research plays a crucial role when any innovative idea or product emerges which oughts to transform the industry and make a breakthrough. Research is an intrinsic aspect of converting a mere idea in your head into a successful real-life innovation.
The research process revolves around data collection from popular websites, like ScienceDirect, because it helps the researchers gather the information required to answer research questions, test hypotheses, and achieve the study objectives. The quality of data directly affects the validity and reliability of the research findings, the collected data needs to be stored properly in a structured manner.
While the manual data collection process is a time-consuming task from the perspective of a researcher, an automated web scraping tool simplifies this process. It saved the researcher’s time and helped the team focus on their core competencies.
Challenges in Creating a Structured Database
A structured database of all the collected sources makes it easy for the researchers to organize the information and quickly access the data by just scanning the table. However, the data entry becomes time-consuming because researchers have to read the article, copy all the essential information, and paste it into the Excel sheet.
For instance, ScienceDirect is a leading platform where research papers from all around the world are available for technical, scientific, and medical research. Manually extracting data from data-rich websites, like ScienceDirect, is a tedious and time-consuming task. That’s why, our experts worked on developing an automated web scraping solution to extract all the data points in a structured manner easily.
Behind every innovation or development, there is a need that drives its creation. Let’s understand the challenges that encouraged the researchers to look for an automated data extraction tool:
- Sheer Volume of Resources
Imagine going through 100 sources to collect information points, like the author’s name and publication date. The manual data entry of hundreds and thousands of published research papers becomes overwhelming and time-consuming. Each article needs to be handled one by one, so it becomes a monotonous process.
- Monotonous Process Leads to Errors
When the process becomes repetitive, there is an increased chance of inaccuracies. Simple errors, like typographical mistakes, inconsistent metadata, or overlooked information, can turn out to be expensive because researchers have to spend additional time identifying and correcting the errors.
- Formatting Inconsistencies
Each research paper on ScienceDirect follows different citation styles, like APA, MLA, and Chicago, and researchers have to put in additional efforts to standardize all the data for proper organization. Structured data can be easily analyzed by the AI/ML algorithms to derive the necessary insights. However, if the data isn’t organized properly from the start, performing analysis, like bibliometric studies, topic modeling, or network analysis, becomes difficult.
- Large Dataset Management
Manually organizing, categorizing, and updating the information from a large number of sources and research papers becomes nearly impossible to manage effectively. Besides, keeping track of the changes, like whenever there is an update in the publication or new editions are published, is also difficult.
- Difficult in Searching
A manually created database with improper indexing impacts the researcher’s ability to retrieve the information quickly. Then, the researcher has to waste their valuable time to locate the specific paper or data points, leading to unnecessary delay and waste of effort.
- Poor Scalability
As the database grows, the complexity of adding sources and updating the data points increases exponentially. Besides, the manual systems aren’t designed to handle different data types, like multimedia content or experimental data, making it difficult to expand. Also, when we think from the researcher’s perspective, researching, reading, and manually updating a database can lead to cognitive overload. Besides, the repetitive tasks make it easy to lose focus due to mental exhaustion.
Our Strategy
At Relu, we streamline the heavy lifting that comes with data extraction with our automated web scraping solutions. Here’s how we built a tailored data extraction solution:
- The objective of the tool was to extract and collect the following data points: Title, Author(s), Abstract, Journal Name, Publication Date, and DOI (Digital Object Identifier).
- Our team used Python because it supports a wide variety of libraries for web scraping and data processing functionalities. Web scraping libraries, HTTP libraries, and data storage tools (MySQL and Pandas) were implemented to automate the entire process, from extracting the data to storing it.
- We used ScienceDirect API for structured data retrieval and used tools like 2Captcha and OCR Libraries to bypass the CAPTCHA challenges if required.
Key Features of Our Solution
All our solutions are optimized for interacting with complex websites and large-scale data. Here are the key features of our data scraping solution that helped the researchers to boost their productivity:
- Customized Scraping: The solution provides flexibility in scraping, like users can scrap the metadata based on specific keywords, authors, or journals.
- Batch Processing: We included batch processing functionality, so the data from multiple articles or the entire search result page can be extracted in one go seamlessly.
- Multiple Export Options: The solution supports different export options. The data files can exported in CSV, JSON, or Excel formats, so they can be easily integrated with other research tools.
- Intuitive and Easy to Use: The platform’s user interface (UI) was designed to keep in mind the needs of the users. The user interface was based on point-and-click functionality, so even non-tech users can easily navigate through the platform.
- Easy Integration: The solution can be easily integrated with other research tools, like citation managers ( Zotero and Mendeley) or advanced analytics (Tableau or Power BI), to enhance the collected metadata. For instance, the CSV or Excel files can be imported into the citation manager, and the published papers are automatically organized as per metadata fields.
How The Automated Web Scraping Solution Helped?
Here’s how our solution helped the researchers:
- Eliminated the need to search and organize the information manually
- Saved hours of repetitive work, which included searching the papers, downloading the metadata, and standardizing it.
- Scalability made the solution suitable for large-scale projects
Besides, this tool helped streamline the researcher’s work for further analysis. The export files were in ready-to-use condition for further analysis or building bibliographic databases. For instance, it can be used to perform trend analysis on publication dates, topics, and authorship or generate visualizations on keyword trends and citation graphs. Researchers can also use it for research synthesis, where the enriched datasets can be used to identify the gaps and validate hypotheses.
Conclusion
The ScienceDirect Web Scraping tool helped in automating the repetitive tasks associated with research paper metadata collection. The tool is designed with scalability and customization in mind and ensures consistency in formatting to build a consistent metadata collection.
The tool is integration-friendly, and it can easily integrated with other workflows, like citation managers, for smooth and uninterrupted data flow. The exported data files in standard formats are in ready-to-use conditions that only need to be imported for further analysis.
Our experts can help you create robust and reliable data scraping solutions that are assured to maximize your ROI by creating high-quality datasets for enhanced insights. So, if you are struggling with manual data extraction, then our experts have the apt solution to automate the entire process and relieve your staff from monotonous tasks.
