On this page you will find definitions for key platform terminology, categorized in the following ways:
The Terminology Translation section includes Everlaw terms translated to terms you may be more familiar with from other platforms.
To learn more about terminology on Everlaw related to a specific workflow, for example searching or running productions, select that specific topic from the table of contents below.
*Terms specific to Everlaw will be denoted with an asterisk.
Terminology by Workflow
*Database: On Everlaw, a database is the central storage location for all documents in a given matter. When you upload documents to Everlaw, they get uploaded into a database.
*Project: Documents in your database are then made available for review in projects. Projects are self-contained, user-facing review environments where users can organize, tag, and annotate documents, among other things.
A complete project contains all the of the data hosted in the Database it's within. A partial project can contain all, or just a specified subset, of the data within that Database.
*User Groups: On Everlaw, project permissions control access to features and tools within project workspaces. Project permissions are denoted at the “user group” level. When folks are added to a project, the user group they are added to determines their project permissions.
*Codes & Categories: Codes are designations set-up in a project that reviewers can use to categorize or tag documents. Everlaw has a two-tier coding system: there are categories, and the codes within categories. For example the category of Confidentiality, and the potential codes within of Confidential and Not Confidential. Categories and codes are customizable in every project.
*Freeform Codes: Freeform codes have a set topic (ex: contract date), but reviewers can enter a custom value for the code rather than choosing from a list of options.
*Auto Code Rules: Auto-code rules ensure that all documents in a specified context (duplicates, attachment families, email threads, or document versions) are automatically coded in alignment with other documents in that context, when any given document is coded under a particular coding category. For example, an auto-code rule for the category of Responsiveness and the duplicates context ensures that when a given document is coded within that category (such as coded Responsive), all of its duplicates are automatically coded the same.
*Conditional Rules: Conditional rules require users to take certain actions when a document meets specific criteria. For example, a conditional rule may state that in order to code a document as responsive, a reviewer must first leave a note.
Persistent highlights/hit highlights: Specified words, phrases, or patterns that will appear highlighted on documents for all users in a project whenever they exist. They are used to draw attention to important words or phrases, and for any given instance in a document can easily be redacted.
*Logical Operators/Containers: Logical operators/containers are the building blocks for searches on Everlaw. These include “AND”, “OR” and “NOT”. For example, you may use the AND operator to build a search looking for documents that are emails AND fall within a certain date range. Alternatively, you may want to find all emails OR spreadsheets in your project. Finally, the NOT operator allows you to negate any term, such as looking for all documents that have NOT been coded.
*Nested Search: Using Everlaw’s visual search interface you can “nest” or layer additional containers into your search, allowing you to build out complex searches with a combination of AND/OR/NOT operators, deduplication, sampling, and grouping.
*Smart Terms: Smart Terms are available search terms created by Everlaw to help streamline your searches. Smart Terms have lightning bolt icons next to their names and tooltips when you hover over them. They allow you to search across multiple different metadata fields at once.
*Primary Date Smart Term: The Primary Date Smart Term searches across multiple date fields in a certain order, dependent on file type, and assumes the topmost date value. Project administrators can edit the order in Project Settings. This term can be useful for ensuring documents are searched based on the metadata date value more relevant, according to the type of document.
*All Date Fields Smart Term: The All Date Fields Smart Term searches across all visible date and datetime type metadata fields. If a document has any date field that matches the parameters of the search, that document will be returned.
*Parties Smart Term: Parties searches across the To, From, Cc, and Bcc fields simultaneously.
*Results Table: The results table provides information about a set of documents – from a given search, binder, upload set, etc. When you run a search or click into a set of documents, you’ll be brought to a results table where the rows represent each document and the columns tell you information about your documents.
*Grouping & Removal: Grouping allows you to organize your search hits or document set by context: duplicates, attachments, email threads, or document versions.
Removal allows you to remove certain classes of documents from your document set or search results. These classes are: parents, children, search hits, grouped non-hits, email duplicates, and non-inclusive emails.
Search Term Report: Search term reports allow you to run multiple searches simultaneously and get a high-level view of the results, including the number of resulting documents. Search term reports are typically used during Early Case Assessment. On Everlaw, a search term report's "searchable set" is the set of documents from which the report will search. This could be all documents in the project, or a subset (ex: all documents associated with a specific custodian or date range).
Boolean & Advanced Content Searching: A boolean search allows you to combine the operators AND, OR, and NOT in order to search for specific content in documents. For example, you might search for documents containing the word treaty OR the phrase “key event”, perhaps documents containing the word treaty AND the phrase “key event”, or maybe documents containing the word treaty but NOT the phrase “key event”. These operators can be combined to build out complex searches.
Additionally, Advanced Content Searching goes even further, allowing for variations of words to be searched for, to look for documents that contain a word or phrase within a certain number of words from another, and so on.
Document Review and Assignments
*Everlaw Assignments & Assignment Groups: Everlaw's assignments tool is structured around assignment groups, which consist of one or more assignments (or sets of documents for review) allocated to individual users.
Assignment groups contain documents that meet administrator-specified inclusion criteria. Administrators can then allocate these documents to users in the project in the form of assignments.
Assignments are analogous to what is called "Batches" in some other e-discovery platforms.
*Inclusion Criteria: The inclusion criteria for an assignment group determines which documents are apart of the assignment group (ex: all documents in a binder).
*Review Criteria: The review criteria for an assignment group specifies what review work needs to be applied to the documents for them to be considered reviewed (ex: coded for a Responsiveness and coded for Confidentiality).
Duplicates and Near Duplicates: Duplicates are two or more documents that represent the same document. For example, two copies of the same PDF. One way that duplicates are most commonly identified is by their HASH value, which is like a unique fingerprint for native files. When two files have the same HASH value on Everlaw, they are considered exact duplicates.
Documents that are considered “near duplicates” may vary based on the platform or person determining the duplicate similarity. On Everlaw, “near duplicates” are documents with 95% or more text similarity.
*Email Duplicates: Email duplicates are documents that Everlaw has determined represent the same email, despite textual differences and different hash values. For email-typed documents, Everlaw uses content similarity, close timestamps and other metadata, and email header fields to identify these documents.
Deduplication: Deduplication is the process of removing documents from a set that are the duplicates of another document, such that only one copy remains.
*Context Panel: The context panel is a display in the review window that allows you to quickly view documents that are related to the one you are currently viewing. For example, you can view any duplicate documents, the email thread the document is apart of, the attachment group it is apart of, file structures, and versions of the document when applicable.
*Produced & Original Versions: Versions on Everlaw are different versions or copies of the same document (produced and pre-produced, translated and untranslated, etc.)
*Unitization: Everlaw’s unitization tool allows you to break a compound file into separate documents. For example, you can take a 1000-page, scanned pdf and unitize it into 30 separate documents. This is useful if you happen to receive large, disorganized productions and need to break apart documents into more manageable and logical units.
*Custom Hits: Custom Hits are located as a tab in the full-screen review window, and allow you to search through the contents of your document. You can search for key words, phrases, or patterns.
Redactions & Redaction Stamps: To redact is to remove key information from the contents or metadata of your document. For example, a social security number that is considered confidential information may be redacted so as to make that information not visible.
On Everlaw, redactions are transparent (you can still see the content beneath) on a document until that document is produced via a Production on Everlaw. When produced, a new version of that document is created (the produced version) which has any included redactions burned into the document such that they are no longer transparent and the content beneath is not visible.
Redaction stamps are word or phrases that you can choose to stamp on top of a redaction, often identifying why that redaction was applied (ex: Confidential Information).
*Dependent Cell Redactions: When redacting a spreadsheet, the redaction tool can take into consideration cell dependencies. A dependency is a cell that is dependent on another. For example, if you have a cell whose value is created based on a formula, then the cell that includes that formula is a dependency of the values in the other cells. When redacted, Everlaw will offer you a few options for how to handle the additional dependent cells.
Email threading: The process of determining how emails uploaded to Everlaw fit with one another, and grouping them to identify these relationships. For example, identifying an email that is a forward of another, and so on.
Inclusive/Non-inclusive emails: Inclusive emails include just the emails and attachements in an email thread that are needed in order for the entire contents of the thread to be reviewed. For example, an email reply may contain the content of the original email, so the original email is not apart of the inclusive email set as it is not needed for the entire thread to be reviewed. Non-inclusive emails then, are those that are not needed for the entirety of the contents of the thread to remain.
Batch Action: There are certain actions on Everlaw that can be performed to multiple documents at once. These are called batch actions and include things like applying codes or notes to multiple documents at once, applying redactions to a set of documents, removing a set of documents from a binder, etc.
Uploads and Data
Native Data: Native data is data/documents in their unprocessed, raw format. These might be documents pulled directly from someone’s computer. They have not yet gone through a system like Everlaw. A native file is the original file for a document.
Processed Data: Processed data is data/documents that have been processed by a system like Everlaw before. Processed documents are often stamped with a Bates number, and may have burned in redactions. If you have received a production from opposing counsel, Everlaw calls this "processed data." Please see our definition of the term "Production" below to differentiate.
Processing flag: Upon uploading documents, or document processing, you will be alerted to any potential errors in the upload process via processing flags. Processing flags let you know which documents had errors during processing, and what those errors are so that you may troubleshoot as needed. For example, an unsupported document type might throw a processing flag as it can’t be uploaded successfully.
DeNIST: Sometimes you may try to upload an entire hard drive or a folder that has personal files mixed in with system/software files. Some of these files have no user-specific content and can be removed upon processing. This process is called deNISTing (removing NIST files). Any files that are on the NIST List will qualify for deNISTing automatically upon upload. The NIST List is a commonly used guide for these files across the industry.
Load File: A load file is like a spreadsheet, with each row representing a document in a set, and the columns listing out information about the documents such as metadata values. A DAT file is a common load file type.
Container /Compressed File: A container/compressed file is the outermost file containing a set of data. It serves as a method of organizing the data in one location, but once uploaded to Everlaw does not itself contain any information for review.
Optical Character Recognition (OCR): Optical Character Recognition (OCR), or OCR’ing, is the process of creating a text file for a document. This text file can then be used to review the document and search across the document’s contents.
Attachment Family: An attachment family represents two or more documents that are linked to one another. For example, an email and a document that was attached to that email are apart of the same attachment family. The email represents the parent, while the attachment is referred to as the child document. Similarly, a powerpoint file attached to a calendar event represents the child to that parent calendar event.
Productions & Produced Documents: When Everlaw refers to a "production" or "produced documents," we are referring to a production that you run on Everlaw and then provide to another party, such as opposing counsel. A production is a set of documents, and optionally other files such as a load file or privilege log, that are packaged and prepared to be shared with an outside party. Documents are often bates stamped or endorsed in some way, and may have redactions applied. Documents that are apart of a production are known as produced documents.
*Production Protocol: To produce documents on Everlaw, you must first create a production protocol. This outlines both the specifications for the production as well as identifies the document set that you want to produce. In Everlaw, you can store any number of protocols for future use, allowing you to reuse previously created protocols.
Production Modifications: After running a production, users may need to make alterations to the production document set. One such alteration is known as a Clawback. A Clawback is the process of removing a document from the production set that is privileged or should not be shared. To unprivilege a document is to do the opposite -- now include a document in the production set that was originally withheld for privilege. Additional production modifications available on Everlaw include adding or modifying a load file, adding or modifying a privilege log, and more.
Withholding/Privilege Rules: Withholding and Privilege Rules allow you the flexibility to define if there are any documents you want to withhold from a production, and to customize what placeholder text appears in place of those documents. This means that the images, text, and natives of these documents will not be included in the production. Instead, Everlaw will create a placeholder image for the withheld documents.
You can create multiple rules with different criteria for which documents are withheld, and what the placeholder text will say. Privilege Rules are one example of Withholding Rules you may create specifically for documents that are considered privileged.
*Clustering: Clustering visualizes documents in your dataset by conceptual similarity. It generates insights about concepts in your documents without requiring any user input, such as grouping documents together based on their key defining terms.
Predictive Coding / Active learning / CAL: Active Learning (or Continuous Active Learning) is a tool that uses previous review work applied by actual reviewers to documents, in order to determine how likely the remaining documents in a populous are to be reviewed in the same way. In particular, you will specify criteria identifying which documents the system should learn from for a given model, along with the criteria for a subset of those documents that you want to find more of (ie. those that are relevant).
The prediction system examines the documents that satisfy your criteria, dissects the different features of the documents, and develops a model that predicts the relevancy of any particular document based on its features.
On Everlaw, we call this Predictive Coding, and our tool will give all documents in a project a score from 0-100 of how likely that document is to be coded as relevant if a reviewer were to review it. This can be helpful for prioritizing review, and quality checking review decisions.
*Data Visualizer/Visualizations: The Data Visualizer provides an overview of the documents in your database by summarizing their characteristics visually. With the Data Visualizer, you can explore documents at a glance without the need to review individual documents or predetermine a search. You can also use the Data Visualizer to filter down sets of documents by particular document properties and attributes.
Visualizations, or graphs for your document set, are available for various fields within Everlaw which can be accessed via the left-side toolbar within the Data Visualizer.
*Storybuilder: Storybuilder is a collaborative suite of tools where you and your team can analyze and share key evidence, construct case timelines and argument outlines to prepare for litigation, prepare for and conduct depositions, and more.
*Project Story: A collection of Storybuilder features and tools, all of which can be found by accessing the Story’s dashboard. By default, all projects include a default Story. These objects include: the dashboard, labels, people profiles, timeline, drafts, depositions, and more.
*Timeline: The timeline allows you to select the most important documents in a case and arrange them based on their date to create a coherent story.
*Labels: Labels allow you to tag and associate your documents, testimony pulled from deposition transcripts, and deposition transcript highlights with key information such as events, issues, people, etc.
*People Profiles: People is a special type of label category because creating a people label also creates a corresponding people profile. With people profiles, you can record details such as a person’s contact information, work history, work relationships with other people, general notes, and more.
*Testimony: Key excerpts from a deposition transcript that can be viewed and utilized in Storybuilder as documents can: in the timeline, linked in depositions and drafts, and associated with labels.
*Draft and Deposition Objects: Deposition objects have functionality to prepare for and conduct depositions, and to use deposition materials after the deposition has take place. Drafts are a tool that allows you to create formatted text outlines with document references in-line for a variety of workflows (ex: review protocol, motion preparation, etc.)
Early Case Assessment (ECA): Early Case Assessment generally includes culling through large sets of data at the beginning of a case to determine what data needs to be reviewed further and potentially produced or used. Early Case Assessment (ECA) on Everlaw in particular, refers to a type of Database designed to allow users to simply cull data and identify just the documents that need further review.
*Everlaw Binders: Binders are arbitrary collections of documents (examples include responsive documents, documents for further review, etc.). You can use them to group documents together and to share particular sets of documents with other users. A given document can belong to multiple binders.
*Everlaw Folders: You can store homepage cards representing sets of documents (saved searches, binders, etc.) in folders for later reference, or to share with other users. Sharing a folder with these objects within it is an easy way to share multiple binders or other objects at one time.
Quality Check (QC) / Quality Assurance (QA): A quality check or quality assurance, often referred to as just QC or QA, is the process of double checking work to ensure that it has been done correctly. For example, you might QC a document set before production to ensure you have the correct documents in your set. Similarly, you may QA a search to ensure its bringing back the intended documents.
Metadata: Metadata is information that describes your data. Examples of common metadata fields are a date value or an author value. These may or may not be present in the body of a document, but can nonetheless be detected and displayed by Everlaw in the metadata panel near the top of the review window when available.
Legal Holds/Hold Notices: Legal Holds or Hold Notices inform employees or custodians of the need to preserve data. They can be issued in response to a court order or pre-emptively in anticipation of litigation.
Work Product: Work product represents actions taken and information created on the platform. For example, applying codes to documents, creating binders, and running productions are all examples of work product on Everlaw.