The world of eDiscovery can be intimidating. We get it.
That’s why we’ve written posts like eDiscovery 101 – Easily explain the process and costs of eDiscovery to a 5th Grader. Even then, there are a lot of terms to know and understand.
Today we’re going to break down 12 eDiscovery terms you should know.
Let’s start with an easy one: eDiscovery. eDiscovery, or electronic discovery, is a procedure by which parties involved in a legal case preserve, collect, review, and exchange information in electronic formats for the purpose of using it as evidence. eDiscovery is made easier by the use of software like Relativity, CloudNine and ONE Discovery.
What kind of information is included in eDiscovery? That takes us to our next term: Electronically Stored Information (ESI). Electronically stored information, or ESI, is the data that is in question. Types of ESI include:
- Social media activity
- Photo and image files
- Texts and instant messages
- Video and audio files such as voicemails
- Word and Excel documents
- Website activity and history
More can be read about ESI in our blog, post, Why Your Cases Data Volumes Are Exploding (and What You Should Do About It).
Here are 10 other eDiscovery terms you should know.
Assisted review. The process of having computer software electronically classify and organize documents. The software uses algorithms to review and identify documents and communications that are relevant to a case. This collection of information eliminates room for human error.
Boolean search. Boolean search is a technique that utilizes Boolean Logic to connect keywords or phrases within a single query. With Boolean Search, you can combine keywords with operators or modifiers such as ‘Not’, ‘And’, or ‘Or’ to produce more relevant results. This type of search helps you get a highly targeted set of results. Unlike Google, a Boolean search only identifies the information you aim to find.
Chain of Custody. The practice of maintaining and documenting the handling of evidence is known as chain of custody. This process is important when compiling electronic evidence as it chronologically showcases the detailed log showing who collected, handled, or analyzed evidence during an investigation, whether it’s physical or electronic.
Custodian. A person that possesses administrative control of a legal document or electronic file is known as a custodian (or sometimes data custodian). When a legal investigation develops, the system around identifying, collecting, and protecting relevant content is based on the people who are the custodians of the applicable data. An example of a custodian is a person who has an email in their inbox that is relevant to the investigation.
Data mapping. Creating a comprehensive inventory of an organization’s data is called data mapping. The process organizes:
- What types and formats of data exist
- The location where the data is stored
- Which custodian is in charge of the data
- When the information should be deleted or archived
De-duplication. De-duplication, or deduping, is the process of comparing electronic records in a data set, identifying identical characteristics and removing them so the data is clean. Through the help of software algorithms, the connections between documents are scanned and flagged if they seem too similar. Deduplication strategies are an imperative eDiscovery function as they eliminate unnecessary data from document review.
Metadata. A key focus of eDiscovery is the ‘data about data’ also known as Metadata. On every piece of technology, information is generated by tracking your usage that then creates a digital footprint. Examples of metadata include:
- When a file was created
- When it was last modified
- Where it’s located on a device
Normalization. Normalization, or data normalization, is the act of reorganizing data so there is no redundancy and so all related data items are stored together. It allows databases to be streamlined, ensuring they take up less space and make review easier.
OCR. Optical character recognition or OCR is the process of technology scouring through documents to recognize letters, numbers, and any other written characters, converting images into searchable text. This is particularly helpful for scanned files making them easier to review and search for relevant information.
Predictive Coding. Simply put, predictive coding is the automation of document review. Also referred to as technology-assisted review (TAR) or computer-assisted review (CAR), predictive coding technology creates efficiency by categorizing data in a usable way, making the review process more streamlined.
While eDiscovery can be overwhelming, it doesn’t have to be. We walk attorneys and paralegals through the process (and lingo!) every day.