Discovery has evolved in the last few decades—no one would contest that. And it’s evolving still. Data sets are a microcosm of this change: they’re not just emails anymore. From short messages to videos, there’s way more than enough to review in today’s average e-discovery data set.
Today’s e-discovery involves web-based data, too—what Relativity Developer Partner Hanzo calls “dynamic content.” This is data that requires different kinds of interaction than others, and it poses unique challenges for review teams.
We sat down with Jim Murphy and Evan Gumz from Hanzo to discuss this content and how legal teams can manage it during litigation.
Sam Bock: What is dynamic content, and how does it differ from more typical data types that might come up during e-discovery?
Jim Murphy: Dynamic content refers to interactive content that creates a unique user experience. Dynamic content is continuously changing: it can include blog posts, website comments, videos, animated graphics, and more. It allows businesses to create unique experiences for users and improves the user experience.
Dynamic interactive content elements such as ROI calculators, unique customer website journeys, chat boxes, and customer service bots are often powered by websites using JavaScript. An impressive 94.9 percent of websites use JavaScript as of September 2018, per a W3Techs Web survey. Beyond public-facing websites, browser-based, internal tools that corporations use—like Jira, Slack, Basecamp, Confluence, and others—also use JavaScript.
For legal discovery, it isn’t always ideal to produce or review a screenshot or static PDF of these types of data; the interactivity and complexity of the content may be lost. Whether it’s the content of conversations between a representative and a customer, comments and links within a Facebook post, or a strategy laid out by an internal team within a corporate collaboration platform, web content must be preserved for possible legal and compliance holds just like any other ESI.
This data differs because it’s browser-based. The data is not in traditional stores, like emails and documents. It needs to be accessed via a live browser collection.
How do emerging data types make e-discovery review challenging, and how can e-discovery teams get ahead of it?
JM: Much like Slack is the new email, browsers are the new operating system. The success of the Chromebook is a testament to that. Emerging data types make e-discovery challenging because they are difficult to collect and review without the right technology, and converting dynamic data into static formats causes teams to miss critical data. For the most defensible chain of custody, data should stay as close to native format as possible throughout the entire process, from preservation through collection to review and ultimately production.
Review is one of the most time-consuming components of e-discovery and as a result, it’s costly. Traditional workflows can be tedious as you work from collection to review. Without the right tools (our Hanzo Dynamic Review application for Relativity is one example), the process of exporting, formatting, and importing dynamic content can be manual.
Once you import the data, static collections may leave out critical data. For example, if you have a Terms and Conditions page on your website with features that enable you to expand and collapse a section, the page must be purposely expanded prior to collection or you won’t get that content—forcing you to go back and recollect. Aside from being time-consuming and frustrating, you could miss out on data in the event the content was changed in the interim—meaning you lose evidence.
What is dynamic review, and how can it help improve legal teams’ processes for handling these types of data? Is it different from “native review?"
JM: Dynamic review—also known as native review—is the best way to view true, native-format web content. With native-format web archiving, an entire website is saved in its original format. That website—although it’s disconnected from the live internet to ensure that it doesn’t download or access new content—is fully active, just as if it were online. It displays a dynamic view, allowing the user to click on links, select options from drop-down menus, and access different versions of personalized web experiences. That means that it doesn’t just save the primary website that it’s collecting, it actually saves every website that can be reached from that page—giving the viewer access to all of that data as well.
The saved website records every possible server request and the answer to that request, along with all of the supporting metadata to establish the authenticity of its information. Because each event is time-stamped and hashed, it’s easy to establish that the preserved website is authentic and admissible, and to prove the chain of custody underlying its creation.
Simply put, native/dynamic review gives viewers the ability to navigate this native copy—an exact replica—of the original content as if the reviewer were interacting with the live site. Dynamic review helps the reviewer experience the context, and interact with the data naturally to more rapidly identify responsive data and uncover key information that might otherwise be hidden.
What benefits can native review offer—especially when it comes to review strategy, defensibility, and productivity?
Evan Gumz: When collecting dynamic content in a specialized way, e-discovery professionals can rest assured that they’ve collected complete data. Additionally, dynamic review is very defensible because it’s consistent with e-discovery best practices.
On most document reviews (especially large cases), electronic documents are reviewed in their native format or with the help of document intelligence to expose hidden content within their viewer—making decisions on responsiveness, confidentiality, and privilege are easier to make when the data can be investigated intuitively. For example, you won’t be able to see editor comments on a Word document without clicking to show comments. There’s an understanding now that you need to interact with electronic documents to get the whole story. Webpages are naturally dynamic, so there’s no good reason not to treat them the same as other electronic documents.
Dynamic review empowers reviewers to interact with data as if they were exploring a live site, making it easier to connect the dots and identify what is relevant.
Still, accommodating innumerable dynamic content types and building the workflows to support them is no easy task. Bringing in the right tools can help. With Hanzo, for instance, it’s easy to import collected data directly to a workspace from within Relativity. Reviewers can see both the PDF and native formats, like any other record. By interacting with data in as familiar and natural a way as possible, their normal review process can be accomplished in half the time.
What does Hanzo’s integration with Relativity offer legal teams faced with collecting and reviewing dynamic content?
EG: Today, people consume dynamic web content via a browser because it’s accessible and interactive. However, for e-discovery purposes, web content is difficult to collect defensibly: because it is not in traditional disk-based stores, these web-based platforms require a live browser collection. Adding to the complexity is the fact that APIs for many of these systems are often not well developed or have limitations. Hanzo’s native format crawling technology can capture anything you can see in a browser—future-proofing your collections while giving you access to the most complete data to review.
Review teams can navigate through the evidence naturally—like navigating contextually through a live site. Along with the native content, you have the associated PDF rendition, extracted text, and metadata at your fingertips to inform your coding decisions. Navigating naturally makes it easier to hone in on the salient information.
So far, our customers are pleased with the impact on their workflows: “The ability to review dynamic web content in Relativity as an interactive native site will improve review speed, and accuracy, while reducing questions and confusion,” said Ben Robbins, the Senior Manager for eDiscovery, Forensics, and Information Governance at LinkedIn.
