The eDiscovery Process for Collaboration Data and SaaS Platforms

| July 6 2022

The eDiscovery Reference Model (EDRM) has been a long-established visualization of the eDiscovery process once litigation is anticipated.

At that point, potential data custodians are identified, and a legal hold notice is sent, most often by an organization’s in-house legal team, letting custodians know not to destroy ESI.

Then that data must be preserved, which with today’s cloud-based SaaS platforms and communications channels, usually means the organization’s IT department will be involved. However, with new eDiscovery tools, data can now be preserved-in-place (PIP), meaning it is locked down at its source in a way that prevents anyone from deleting or spoliating relevant data.

From here, data is collected, after which a number of Early Case Assessment (ECA) tools – which include advanced search, analytics, and artificial intelligence – can be applied to the dataset, allowing legal teams to gain early insights into case evidence and begin the process of culling data which isn’t relevant to the matter at hand.

It’s at this point in the process when in-house legal teams usually send the collected and culled data to outside counsel or a legal service provider for processing and review. However, not just any export format will do: it needs to be a format that puts the collected data into a usable form for review, such as a PDF. After review, all documents included in discovery will be produced according to Department of Justice guidelines.

Because these final stages are often the most time-consuming and costly of the eDiscovery process, in-house legal teams can reduce time, cost, and risk by only sending relevant ESI to outside counsel for review.

Export Formats and How They Affect the Ediscovery Process

JSON

For the vast majority of SaaS platforms and collaboration applications, the most common native export format is JSON. JSON uses human-readable text to store and transmit data objects consisting of attribute-value pairs and arrays (or other serializable values). And while all of the required data is preserved in this format, it’s not the most usable when it comes to reviewing for potential relevance in an investigation, especially for platforms with complex user interfaces or communications channels. 

When you think about how we take in the information on a webpage or application, it’s not linear but dynamic. Instead of reading lines of text from the top down, a user simultaneously takes in a combination of text, images, figures, graphs, emoji, attachments, and more. A JSON export loses the visually dynamic nature of SaaS platforms. 

API

Many SaaS platforms have developed application programming interfaces (API) that create a connection between their native format and other software. APIs are created to only share information that may be useful to an outside program while keeping internal details of its system hidden. APIs may be custom-built for a specific pair of systems or may be created to allow for interoperability.

While APIs give users the ability to use 3rd party solutions to preserve, collect, and even cull data housed in a SaaS application, it’s still limited to what the API is built to communicate, and it still may lack some of the visual and dynamic features of the original interface.

How Dynamic Capture Technology Fills the Export Gap

Sometimes referred to as crawling and scraping, dynamic capture tools combine to preserve website and application data as it appears live on a website. Crawlers capture all of the pages from a single domain, and then scrapers extract predefined data fields from those pages.

For ediscovery and compliance, this technology stores data in a forensically-sound, unalterable way that provides a complete audit trail – including the hash value for the collection in the metadata  – demonstrating a defensible process.

But the real benefit comes from reviewing and interacting with the dynamic web archive, which gives full context to the data and offers users insights that might not be available through an API or JSON export.

When coupled with advanced search and data visualization tools, this technology provides a strong solution for managing SaaS and collaboration data for ediscovery and regulatory compliance.

Conclusion

More and more, relevant data is found not only in the text on a webpage but in the interface as well. Toggles, dropdowns, and other dynamic elements which aren't a part of traditional exports can provide important information for internal investigations, compliance audits, and ediscovery, and having a solution that can defensibly preserve this data will continue to be an important part of the legal process.

 

To learn more about ediscovery technology for collaboration applications, download Hanzo’s Guide to Litigation and Ediscovery here!

DOWNLOAD THE GUIDE

 

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