Case Study: Automation of Docket Data Extraction

Background

A client, a major player in the field of legal research and analytics, engaged us to streamline their process of docket data collection from county websites for their Meta analysis project. Their aim was to create a comprehensive, searchable database of all available cases from a specific list of county websites, with distinguished outcomes for analysis by their research team. However, they encountered the following challenges:

  • The company needed data on a giant scale, collected from more than 70 websites from different counties.
  • The data, dating from the earliest records to the present day, was not only diverse and voluminous (with thousands of cases per day) but also poorly structured.
  • Each case had a large number of data points, and the data architecture of these dockets changed over time.
  • Most of the websites had a limited number of dockets displayed per search (usually 500), meaning finding all cases per website was impossible without an automated approach.

Due to this and other challenges company started working on the project with us. We have planned the extraction process and discussed the final output structure with their data engineering team.

County Websites

Cases

%

Accuracy

Impact

Our solution proved to be a game-changer for the client’s operations. By supplying a steady, automated flow of structured data, we enabled the client’s data team to streamline their tasks, optimizing their database population processes.

This solution substantially reduced time spent on manual data collection, freeing the team to concentrate on their research goals. With a rich, organized dataset now readily available, they could delve into deeper insights, greatly enhancing the scope of their legal research.

In essence, our solution was more than just a fix for their immediate data challenges. It opened new avenues for innovation and progression within their field of legal study.

Web Scraping Pipeline

Challenges & Solutions

6

Data Accessibility

Accessing docket data posed a significant hurdle due to the presence of security measures such as captchas and IP blocking, implemented by the websites to prevent automated data extraction.

7

Custom Captcha and IP Blocking Bypass

We developed a script to circumvent these barriers while respecting the capabilities of the website to ensure that other users will have no problems visiting. This allowed our system to access the data reliably.

6

Data Inconsistency

The docket entries showcased considerable variability in their standard formats across the different county websites. This inconsistency meant that developing a unified, coherent approach to extract and organize the data was imperative.

7

Dynamic Parsing Mechanism

Given the change in docket structures over the websites, we created a dynamic parsing algorithm that was easier to adjust per website. This ensured that all data points of interest were captured accurately and consistently.

6

Data Complexity and Volume Variability

On average, each website had several million cases available. The sheer quantity and complexity of the data demanded the deployment of robust, scalable extraction systems capable of comprehensively capturing every docket, regardless of volume. 

7

Full Data Acquisition

To combat the limitations imposed by the websites, we tailored each search query meticulously. Where results exceeded the limits, our refined algorithm adjusted the searches to stay within constraints, ensuring no data was missed.

6

Data Format and Enrichment

The client needed the data delivered in a custom format, aligning with their research objectives. Not only was there a need to adhere to a custom format to facilitate analysis and search processes, but additional fields were also necessary.

7

Data Extraction and Cleaning

We built an extraction system capable of handling the variable data volumes, ensuring that every docket was captured. The system included comprehensive data cleaning and random sample inspection to maintain data accuracy and consistency.

6

Historical Data

The client required historical data from as far back as the sites would allow, which presented a further obstacle due to the changing structure over such a long time period and also search limitations available on the website.

7

Data Normalization

We developed a data normalization process to unify the different standard formats into the preferred custom format. This provided the client with data in a single, standard format, irrespective of the original data structure.

Key Takeaways

Custom Solutions for Complex Issues

This case study emphasizes the importance of creating personalized solutions to tackle unique and complicated data problems. Our flexible parsing mechanism, secure bypass methods, and automated data delivery showcased our capability to design customized solutions.

The Importance of Standardizing Data:

It’s crucial to organize data from a variety of sources into a single, standard format to simplify analysis and usage. By converting the data into a research-friendly format with additional useful calculated fields, we provided the client with easily accessible information.

Limited search data extraction

Automated solutions often make it possible to gather vast amounts of data, an undertaking that would be inconceivable through manual work. Even when certain restrictions may prevent manual data extraction, a properly designed solution can still manage to extract the complete dataset.

Court Dockets Scraping

Conclusion

Wrapping up, this case study underscores the profound impact of tailored web scraping and automation solutions in the realm of legal research and analytics. Our custom solutions navigated a range of challenges, including inconsistent data formats, accessibility barriers, and the retrieval of historical data, even under the constraints of limited search capabilities on county websites.

By overcoming these hurdles, we were not limited to a sample of data. Instead, we could extract the full spectrum of available data, ensuring 100% accuracy for the client’s research. The systems we developed not only bypassed access barriers and parsed diverse data but also ensured meticulous cleaning and standardization, leading to a comprehensive, highly accurate dataset.

Our work transformed the client’s research process, creating a well-structured, easy-to-use database and facilitating more in-depth, precise legal studies. It underscores the power and critical importance of web scraping and automation in advancing research quality and efficiency, particularly when dealing with large-scale, complex data extraction and organization tasks.

Netflix
Duke University
DHL
Pfizer
AT&T

We Understand How Data Can Create Real Change

Make Faster Decisions by Extracting, Organizing, and Analyzing Web Data at Scale