This technical note explains the processing and options available for reviewing text messages in the Lexbe eDiscovery Platform (LEP): 1) The contents of text messages will be extracted from devices such as iPhones by a Forensic Examiner. A csv file is provided containing the message and associated metadata. 2) Professional Services also offers further extraction and processing of active text messages to manually break apart, recombine and restructure each text message into separate documents to make them look and act like an email (explained in more detail below). This is provided as an hourly billable service. Please contact Lexbe Sales for a free quote. Common Types of Text Messages Text messages are native files generated by electronic devices such as cell phones, tablets, and instant message systems. They come in two forms: short message service (SMS) and multimedia messaging service (MMS). A standard text message is sent using SMS, which is usually no longer than 160 characters. MMS include not only text, but also images, video, and sound. Text messages can be stored and saved with different file formats as follows:
Text Message Challenges Retrieving and extracting data from text messages is not always an easy process because of the accessibility of various message formats. In general, long messages are split into smaller messages by the sending device and concatenated at the receiving end; however, if the electronic device does not support the automatic splitting and concatenation of long SMS messages, then the processing will require manual extraction and conversion. Each text message converted into an email allows the user to easily review documents, ensuring data is properly identified, preserved, and relevant for use in eDiscovery proceedings. We have also to consider that all arguments around inaccessibility, burden, or even privacy will be disregarded, especially when it to comes to preservation and collection of relevant ESI no matter what the source. Using our eDiscovery Professional Services To Process Text Messages Step 1: Extraction We will extract the metadata (below) from each text message: From: To: Date/Time Sent: Message Step 2: Associate Metadata Associate extracted metadata with the following built-in fields: Date Sent Master Date Author Doc Type = (e.g.SMS, iMessage, etc.) Step 3: Upload Text Messages |