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Introduction
The American Society for Cell Biology is an international forum and inclusive international community for cell biology. It is composed of biologists studying and researching the cell, which is the fundamental unit of life. Cell biology is the study of cells, their structure, function, and lifecycle.
It publishes top-tier journals, like Molecular Biology of the Cell (MBoC) and CBE—Life Sciences Education (LSE), which discuss the latest discoveries and research advancements in cell and molecular biology.
To collect data from such websites manually is time-consuming. The abstracts and conference details may be presented in different formats, like HTML, PDFs, and databases, which might make manual collection look disorganized. The research assistants and interns may spend their valuable time completing low-value tasks, like data entry, that could be utilized in high-level analysis.
That’s why we built an automated ASCB abstract scraping tool, an advanced data extraction tool that automates data collection to create rich and well-structured datasets.
Project Scope & Objectives
The primary objective behind the development of this data extraction tool was to collect the conference details and contact information for numerous ASCB Annual Meetings hosted by the forum. The tool was designed to collect the following information:
- Event Name
- Dates & Location
- Session Information
- Abstract Details
- Author Names
- Affiliations
- Email Addresses and Social Links
The automated data collection reduces the need to manually browse the conference pages, abstracts, and PDF files and copy and paste the data into an Excel sheet. This tool can process hundreds of entries quickly if the conference web page links are provided in the given format. After processing, the data can be exported in the desired format, whether CSV, JSON, or directly into databases.
Solution & Implementation
Our data extraction approach was tailored to meet the technical aspects of ASCB’s website and legal considerations. We ensure that our approach and tool are compliant with ASCB’s terms and conditions and GDPR’s data privacy regulations.
Let’s understand the approach adopted by Relu experts to build an automated data extraction tool:
Step 1. Web Scraping Implementation
We used prominent scraping frameworks, like BeautifulSoup and Scrapy, to crawl the ASCB conference website, locate the data, and extract the key details, like:
- Conference name, dates and locations
- Session titles and schedules
- Abstract titles, descriptions, and keywords
- Author names, affiliations, and contact information.
We utilized Selenium to handle the dynamic content rendered using Javascript. It allowed the scraper to mimic human behavior and access content that standard HTTP requests cannot handle.
Step 2. SERP+AI Integration for Contact Refinement
For contact refinement, we integrated SERP (Search Engine Result Page) APIs with AI algorithms to improve the accuracy of contact information. Once the data from the ASCB website was collected, then:
- The SERP APIs helped in identifying publicly available emails, professional and social profiles of the authors, and institutional contact pages.
- AI algorithms verified the collected data to reduce duplicate entries and find the most relevant contact points.
The combined approach ensured the collection of reliable and apt contact information even when email addresses weren’t available on the website.
Step 3. Structuring Extracted Data
Once the data was extracted from the ASCB website, we processed the collected data to get consistent and usable data. We normalized the data using Python-based ETL (Extract, Transform, and Load) pipelines. In this phase:
- HTML tags, special characters, and irrelevant data were removed.
- Names, affiliations, titles, and other data were formatted to ensure uniformity across the entire database.
- Duplicated or identical entries were merged together to reduce the redundancy.
The data processing and formatting were essential to transform the raw collected data into a well-structured format, which can be easily understood and can be used by platforms and applications for further analysis. The information presented can be used to make data-driven decisions.
Step 4. Deliverable Format
Once the raw data has been formatted, it can be exported in different formats to ensure compatibility with other systems. The data can be exported in CSV or Excel format for streamlined data handling or in JSON format for API integration and advanced data processing.
Results Achieved
The automated web scraping tool helps reduce the manual efforts required to collect the conference details and the time invested in gathering contact information and validating them. So, this task, which took hours to complete, can be finished within minutes using this tool. Here’s how the tool helped in improving productivity and workflow efficiency:
- Time-Saving Benefits
Data scientists spend 60% of their time cleaning and organizing data and 19% of their time collecting and building the datasets. The automated data extraction tool can eliminate repetitive tasks, like copying the details and pasting them into an Excel sheet. Researchers and workers can save around six or more hours per week, almost a full workday if the repetitive tasks were automated. They can focus their efforts and time on valuable tasks and boost productivity.
- Accuracy & Reliability
Manual data entry translates to errors and inconsistencies. Incorrect entries can affect the entire post-analysis process, leading to wrong or improper results. However, with this automated tool, which combines web scraping with AI algorithms and API integration, data accuracy is ensured at all times, regardless of the workload. The structured validation process improves data reliability.
- Enhanced Outreach & Engagement
The author’s contact information is not easily accessible on ASCB’s websites. However, this advanced web scraping tool utilizes SERP API with an AI algorithm. So, the tool can run SERP queries in the format like Author name + LinkedIn, Author name + Email, or Author name + University Profile, automatically to gather accurate contact information. With refined and validated contact information, one can connect with the right audience effectively, leading to better response rates.
- Improved Targeting for Outreach
Detailed datasets help in precisely segmenting the collected data into targeted groups. Then, accordingly, targeted campaigns can be created based on segmented groups, their research interests, affiliations, and conference participation history. Targeted outreach generates high returns as it minimizes wasting efforts on uninterested parties.
- Better Follow-Up & Research Collaboration
Access to extensive conference data and contact data facilitates timely follow-ups and boosts research collaborations. When one has structured and verified contact information, collaborative proposals and follow-up emails can be sent on time. It reduces the time to gather the correct contact information and initiate and formalize research partnerships.
Conclusion
The successful automation of ASCB Data Scraping helped the organization to improve its productivity and reduce its efforts in manually collecting the data. The web scraping functionality, paired with SERP API integration and AI algorithm, ensured faster contact discovery, enhanced collaboration opportunities, and optimized research follow-ups. Build using scalable architecture, the tool can be scaled and its scope can be expanded to other academic conferences and forums. Besides, further AI-driven enhancements can be integrated, like predictive analytics or intelligent data categorization, to streamline the operations.
