By Nancy Patton
What Is Data Collection? How Does It Differ from Preservation?
In e-discovery, data collection is the process of extracting information from its original repository and copying it into a second repository for the subsequent phases of the e-discovery process. It differs from preservation in that preservation is really just about making sure that the data doesn't leave the original repository, doesn't get deleted. But collection actually copies the electronically stored information (ESI) into a second repository which will be used for processing, review, and analysis of the data.
What Types of Data Do Legal Teams Need to Collect?
Legal teams need to collect a variety of types of data: email, Word documents, files on backup tapes, or even in archives. The most popular data type to be collected, generally, is email that's being created in the last three or so years—typically during the lifetime of the litigation.
What Is Metadata? How Does It Relate to Collection?
Metadata is data about data. What that really means is that data has background information, such as the author, the date it was created, the sender, the recipient, and the domains that the email went to and from. All of this information supports and provides context to the piece of data that is being looked at. In collection, it is critical to preserve this metadata as it contributes to the story the facts of the matter tell. Without metadata, or with metadata that is corrupted or altered in the course of collection, the truth of the matter at hand may be obscured or more difficult to discern.
How Do You Collect Data for E-Discovery?
There are several ways to collect data. They include using internal or external resources to go to the data source and physically collect it. You can also have the employee, also known as a data custodian, self-collect the data. And increasing you have the opportunity to use technology to collect the data remotely. Each of these methods have their own advantages and disadvantages.
What Are Data Collection Best Practices?
Some data collection best practices include not over-collecting data and approaching data collection in a tiered way. So you look at the data that you have initially and if you can't find what you're looking for, you can go into additional collections in an effort to find that information.