Author: Gary HuntMobile DiscoverySolutions

From Spreadsheets to Review Platforms: The New Way to Review and Produce Mobile Data

QMobile - new way to review mobile data

As mobile devices have become near-essential in daily life, their ubiquity has made them an important source of electronic evidence in litigation. The use of texting and other messaging applications for business purposes means that cell phones should be routinely evaluated as a potential source of relevant communications. In certain types of matters, such as departed employee investigations and data theft cases, it’s critical to collect and analyze all available mobile device data. This can include call logs, contacts, pictures and deleted files in addition to text messages and chat logs.

The forensic software industry has developed powerful tools for acquiring and analyzing mobile device data. For example, a skilled examiner can generate a forensic image of a mobile device and use the software to extract relevant data types or search for deleted text messages and other deleted data. However, the software tools are designed for acquisition and investigation, rather than for review and production by law firm case teams.

Traditionally, mobile device data has been “produced” by the forensic software by generating a report in PDF or spreadsheet format. Due to the large volume of mobile data, particularly on newer smartphones, these reports are often many thousands of pages. The reports are difficult to review, search and redact. In addition, they are ill-suited to handling the wide variety of mobile data types, including essential categories like messages, pictures and voicemail messages. In short, the existing method of reviewing mobile data is cumbersome and time consuming, requiring a significant amount of manual work.

Our project management team at QDiscovery regularly seeks feedback from existing clients, and there is one constant request: an easier way to review mobile data in the course of litigation. The project management team engaged the forensic team to help address this concern. Together the two teams developed QMobile, an innovative approach that allows mobile data to be easily imported into review platforms such as Relativity.

QMobile allows your case team to review mobile device data in a traditional review platform, similar to how you review emails and documents. You can now review all your Electronically Stored Information in one location and take advantage of the full range of eDiscovery and analytics features of Relativity and other platforms.

QMobile completely changes and improves the analysis, review and production of mobile device data. Below is a comparison of the old, ineffective way of reviewing mobile data versus QMobile.

QMobile Standard Reports
Document review Allows the case team to seamlessly review mobile data within review platforms All content is placed in one bulky report usually across multiple tabs
Filtering Apply filters to narrow the review set by date ranges, names and data type No filtering available
Searching Search the mobile dataset and immediately tag and review only the responsive items Search the entire report and iteratively review each hit in-line
Tagging Tag individual text message records as relevant or privileged Tag the entire report
Redactions Apply redactions to individual text message records Apply redactions to the entire report
Production Only produce mobile data that is responsive and non-privileged Produce the entire report with all necessary redactions made

While QMobile is designed to work with any review platform, QDiscovery has taken advantage of the power of Relativity and developed a truly unique workspace designed from the ground up with mobile in mind. We have built a series of dashboards with different views and widgets to enable your team to narrow down the scope of the mobile dataset and review only the data that is important.

The custom dashboards and views make mobile data user-friendly, allowing you to follow conversations across platforms and participants in order to get to the relevant data more quickly, even potentially discovering new custodians. Visualizations by conversations, dates and participants as well as filters help you recognize patterns that could be key to identifying critical evidence. Conversation threading allows reviewers to discover who was involved in conversations and tag individual messages or entire conversations as relevant. Previously you had to search spreadsheets or PDFs line by line and try to manually piece conversations back together. With QMobile, you can see an entire conversation at a glance; this includes pictures and other in-line attachments because parent/child relationships are maintained.

Relativity Ecosystem developer partner logoOne of the most powerful aspects of Relativity is Relativity Analytics. We’ve built QMobile to be responsive to Relativity Analytics so you can apply the same concept searching, clustering and keyword expansions to mobile data that you used with the rest of your case data. All the robust features available within Relativity are now available for mobile data, which is why QMobile is part of the kCura Relativity Ecosystem.

With QMobile, legal teams can review, analyze and produce mobile data using tools and workflows comparable to what you already use to manage emails. Learn more about the benefits of QMobile or schedule a demo to see it for yourself.

Want to see QMobile in action? Request a personalized demo


Gary Hunt is a Senior Digital Forensic Examiner for QDiscovery. Gary holds the Certified Computer Examiner (CCE) certification, is an active member of the International Society of Forensic Computer Examiners (ISFCE) and High Technology Crime Investigation Association (HTCIA) organizations and is one of QDiscovery’s testifying experts. Prior to joining QDiscovery, Gary managed the Midwest presence for TransPerfect Legal Solutions’ Forensic Technology and Consulting division. His diverse background in technology, forensics and eDiscovery provides a unique perspective to many challenges faced in the eDiscovery industry.

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