Glossary of Terms

eDisclosure, also known as electronic disclosure, is the digital exchange of legally relevant information during the litigation or investigation process. This practice involves identifying, collecting, processing, reviewing, and producing electronically stored information (ESI) to comply with legal requests, regulatory inquiries, or corporate investigations.

eDiscovery, short for electronic discovery, is the systematic process of identifying, preserving, collecting, processing, reviewing, and producing electronically stored information (ESI) in response to legal proceedings, regulatory inquiries, or internal investigations. This process helps legal professionals uncover relevant digital evidence to build their cases and ensure compliance with legal requirements.

The Electronic Discovery Reference Model (EDRM) is a widely-adopted framework that outlines the stages and processes involved in eDiscovery, from information governance and identification to presentation and production. The EDRM serves as a guide for legal professionals, eDiscovery practitioners, and technology providers to better understand and manage the eDisclosure process.

Computer Forensics is the science of investigating, preserving, and analysing digital evidence from computer systems, networks, and storage devices. This specialised field helps legal professionals and investigators uncover, recover, and authenticate digital information for use in legal proceedings, corporate investigations, or cybersecurity incident response.

ESI refers to any information created, stored, or transmitted in digital form, such as emails, documents, images, videos, and social media content. In the context of eDisclosure and eDiscovery, ESI is the primary source of digital evidence used to support legal claims, regulatory compliance, and corporate investigations.

Cloud Storage is a service that enables users to store, access, and manage electronically stored information (ESI) on remote servers via the internet. In eDiscovery, cloud storage offers scalable, cost-effective solutions for data preservation, processing, review, and production, but may also introduce additional legal, technical, and security considerations for data privacy and cross-border eDisclosure.

Information Governance is a framework for managing an organisation’s electronically stored information (ESI) throughout its lifecycle, from creation to disposal. This approach encompasses policies, procedures, and technologies designed to ensure the accessibility, security, and compliance of digital data, supporting more efficient and effective

Data Privacy, also known as information privacy, refers to the protection of personal and sensitive information from unauthorised access, use, disclosure, or disposal. In eDisclosure and eDiscovery, data privacy considerations include compliance with data protection regulations, such as the GDPR, and the implementation of appropriate security measures to safeguard the confidentiality and integrity of electronically stored information (ESI).

Confidentiality is the ethical and legal obligation to protect sensitive or proprietary information from unauthorised disclosure, access, or use. In the context of eDisclosure and eDiscovery, maintaining confidentiality involves safeguarding client communications, trade secrets, and personally identifiable information (PII) while complying with legal and regulatory disclosure requirements.

Cybersecurity refers to the measures and practices employed to protect digital information, systems, and networks from unauthorised access, use, disclosure, disruption, or destruction. In eDisclosure and eDiscovery, cybersecurity encompasses the implementation of robust security controls, incident response plans, and risk management strategies to safeguard the integrity, confidentiality, and availability of electronically stored information (ESI).

The GDPR is a comprehensive data protection regulation that governs the collection, processing, and storage of personal data for individuals within the European Union (EU) and the European Economic Area (EEA). In eDiscovery, legal professionals must ensure that their handling of electronically stored information (ESI) complies with GDPR requirements, including data minimisation, privacy by design, and cross-border data transfer restrictions.

The interaction between the General Data Protection Regulation (GDPR) and eDiscovery involves the need to balance data protection and privacy requirements with the obligation to disclose relevant electronically stored information (ESI) in legal cases. Legal professionals must navigate complex GDPR compliance issues during the eDisclosure process, including data minimisation, cross-border data transfers, and the handling of personal data.

Metadata refers to the descriptive information embedded within electronic files, providing context and details about the file’s creation, modification, and usage. In eDiscovery, metadata is essential for establishing the authenticity, relevance, and relationships between documents, supporting more accurate search and analysis during the legal review process.

A Native File refers to an electronic document in its original format, retaining all its associated metadata, formatting, and functionality. In eDiscovery, native files provide the most accurate representation of electronically stored information (ESI), ensuring the preservation of vital context and evidentiary value during the legal review process.

Data Mapping is the process of creating a visual representation or inventory of an organisation’s electronically stored information (ESI) sources, including locations, formats, and custodians. In eDiscovery, data mapping assists lawyers and legal teams in identifying, preserving, and collecting relevant data, streamlining the eDisclosure process and reducing the risk of data spoliation or non-compliance.

A PST (Personal Storage Table) file is a proprietary file format used by Microsoft Outlook to store email messages, calendar events, contacts, and other personal information. In eDiscovery, PST files are often processed and analysed to retrieve relevant email data and metadata, which can be important sources of electronically stored information (ESI) in legal cases.

A Legal Hold, or litigation hold, is a directive issued to preserve relevant electronically stored information (ESI) in anticipation of a legal proceeding, regulatory inquiry, or investigation. This process ensures the integrity and availability of digital evidence by preventing the alteration, deletion, or destruction of pertinent data.

Data Preservation is the process of safeguarding electronically stored information (ESI) from alteration, deletion, or destruction during litigation, regulatory inquiries, or investigations. By implementing legal holds and other data protection measures, lawyers and organisations ensure the integrity and availability of digital evidence for eDisclosure and eDiscovery purposes.

A Preservation Notice, also known as a legal hold or litigation hold, is a formal communication issued by a party in a legal case or investigation, requesting the recipients to identify, locate, and preserve relevant electronically stored information (ESI) that may be subject to disclosure. The notice helps to ensure the proper preservation of evidence and minimise the risk of spoliation or inadvertent destruction of relevant data.

In-Place Preservation is a method of preserving electronically stored information (ESI) in its original location and format, without the need to move or copy the data to a separate storage system. This approach can help maintain the integrity of the data, reduce storage costs, and simplify the data management process during the eDisclosure and eDiscovery stages.

Digital Forensic Collection is the methodical gathering of digital evidence from various sources such as computers, mobile devices, servers, and cloud storage. This process preserves the integrity of electronically stored information (ESI) for use in legal proceedings or investigations, ensuring that data is authentic, reliable, and admissible in court.

Chain of Custody is the chronological documentation of the handling, preservation, and transfer of digital evidence throughout the eDiscovery process. This record establishes the integrity and authenticity of electronically stored information (ESI), ensuring that the evidence remains admissible in legal proceedings or investigations.

Forensic Triage is the process of rapidly assessing and prioritising digital evidence collection and analysis during an investigation or eDiscovery process. This approach helps legal professionals and digital forensic experts identify and focus on the most relevant electronically stored information (ESI), reducing time and costs associated with data collection, processing, and review.

Forensic Imaging, also known as disk imaging or cloning, is the process of creating a bit-for-bit copy of a digital storage device, such as a computer hard drive or mobile device, for the purpose of preserving and analysing digital evidence in eDiscovery. This method ensures that the original data remains unaltered while providing a complete and accurate replica for forensic examination.

Data Collection in eDiscovery is the systematic acquisition of relevant electronically stored information (ESI) from various sources, such as computers, mobile devices, servers, and cloud storage. This process must be carried out methodically and defensibly to maintain the authenticity and admissibility of digital evidence in legal proceedings.

Webmail Collection refers to the process of capturing and preserving email data stored on web-based email services, such as Gmail, Yahoo, or Outlook, for the purpose of eDiscovery. Legal professionals must consider data privacy, security, and compliance requirements when collecting webmail data, as well as the technical challenges associated with different email formats and storage systems.

Social Media Collection is the process of identifying, capturing, and preserving relevant electronically stored information (ESI) from social media platforms, such as Facebook, Twitter, or LinkedIn, during the eDiscovery process. Legal professionals must navigate complex privacy, data protection, and cross-border issues while ensuring that social media data is collected in a legally defensible and forensically sound manner.

Self-Collection is a process in which the custodians of electronically stored information (ESI) are responsible for identifying, locating, and preserving relevant data themselves, rather than relying on legal or IT professionals to perform these tasks. While self-collection can save time and resources, it can also pose risks related to data integrity, chain of custody, and potential spoliation, which must be carefully managed in eDisclosure and eDiscovery processes.

Cellebrite is a leading digital forensics and mobile data extraction company that develops software and hardware solutions for the collection, analysis, and preservation of data from mobile devices, such as smartphones and tablets. In the context of eDiscovery, Cellebrite’s tools can be used by legal professionals and digital forensic experts to retrieve and process relevant electronically stored information (ESI) from mobile devices involved in a case.

UFDR is a proprietary file format created by Cellebrite to store and present data extracted from mobile devices using their Universal Forensic Extraction Device (UFED). The UFDR file format contains extracted data, metadata, and file structure information, which can be imported into eDiscovery or digital forensic tools for further analysis and processing.

Data Processing in eDiscovery involves the transformation of raw electronically stored information (ESI) into a structured, searchable format suitable for review and analysis. This process includes data culling, deduplication, indexing, and metadata extraction, ensuring that the resulting dataset is organised, accurate, and optimised for legal review.

Document Coding, also known as document indexing, is the process of categorising and tagging electronically stored information (ESI) based on specific attributes, such as relevance, issues, confidentiality, or privilege. In eDiscovery, document coding facilitates efficient searching, filtering, and organisation of large volumes of data during the legal review process.

De-NISTing is an eDiscovery process that involves filtering out known system and application files, typically listed in the National Institute of Standards and Technology (NIST) National Software Reference Library (NSRL), from a dataset of electronically stored information (ESI). This technique reduces data volume and focuses the eDisclosure process on relevant, user-generated content by eliminating non-responsive files.

A Container File is a digital file format used to store multiple files or data objects, often in a compressed or encrypted form. Common examples include ZIP, RAR, and ISO files. In eDiscovery, container files must be opened and processed to extract the relevant electronically stored information (ESI) for review and analysis.

Data Culling is an eDiscovery practice that narrows down large volumes of electronically stored information (ESI) to a smaller, more manageable dataset. By filtering, de-duplicating, and excluding irrelevant or non-responsive documents, data culling reduces the amount of information requiring manual review, ultimately saving time and resources during the eDiscovery process.

Data Deduplication is an eDiscovery process that identifies and removes duplicate copies of electronically stored information (ESI) within a dataset. This technique streamlines the review process by eliminating redundant documents, reducing storage costs, and improving the efficiency of legal professionals involved in the case.

Timeline Analysis is a digital forensics technique that involves reconstructing a chronological sequence of events based on timestamps, metadata, and other contextual information associated with electronically stored information (ESI). In eDiscovery, timeline analysis can help legal professionals establish a comprehensive understanding of events, relationships, and patterns of behaviour relevant to a legal case
or investigation.

Automatic Translation, also known as machine translation, is the process of using artificial intelligence and natural language processing algorithms to convert text from one language to another without human intervention. In eDiscovery, automatic translation can be used to process and review multilingual electronically stored information (ESI), enabling legal professionals to access and understand relevant data in different languages more efficiently.

Keyword Expansion is a technique used in eDiscovery to enhance search queries by including synonyms, related terms, and variations of the original keywords. This method can help improve the recall and precision of searches, ensuring that relevant electronically stored information (ESI) is identified and retrieved more effectively during the eDisclosure process.

Review Acceleration refers to the use of advanced technologies, techniques, and strategies to speed up the review stage of eDisclosure and eDiscovery. This may include the use of predictive coding, technology-assisted review (TAR), artificial intelligence, machine learning, or other tools and methods that enable legal professionals to process, review, and analyse large volumes of electronically stored information (ESI) more efficiently and accurately.

Processing Data Expansion refers to the increase in data volume that occurs during the eDiscovery processing stage, as a result of extracting, decompressing, or expanding electronically stored information (ESI) into individual files, metadata, and text. This phenomenon can impact storage requirements, review time, and overall costs of an eDisclosure project. Legal professionals and eDiscovery teams must carefully manage data expansion by employing data culling, deduplication, and filtering techniques to reduce the volume of data for review, while maintaining its relevance and integrity.

ECA is a strategic process in eDiscovery that helps legal teams evaluate the potential risks, costs, and merits of a case before committing to the full-scale document review. By analysing a representative sample of electronically stored information (ESI), ECA informs case strategy, enables informed decision-making, and helps optimise resource allocation.

Managed Document Review is a comprehensive service provided by eDiscovery specialists to review, analyse, and categorise large volumes of electronically stored information (ESI) for legal relevance, privilege, and responsiveness. This process leverages technology-assisted review (TAR), predictive coding, and a team of skilled reviewers to expedite the review process, reduce costs, and maintain quality control.

A Review Platform is an eDiscovery software application or system designed to facilitate the processing, analysis, review, and production of electronically stored information (ESI) during the eDisclosure process. Review platforms offer a range of features, such as advanced search capabilities, document coding, redaction, and collaboration tools, to help legal professionals manage large volumes of data and streamline the legal review process.

OpenText Axcelerate is an advanced eDiscovery software platform designed to streamline the eDisclosure process by providing legal professionals with tools for efficient data processing, review, and analysis. With features such as predictive coding, advanced search capabilities, and visual analytics, Axcelerate helps users manage large volumes of electronically stored information (ESI) and identify key evidence quickly and accurately.

A Boolean Search is an advanced search technique that employs logical operators, such as AND, OR, and NOT, to refine and expand the scope of search queries in eDiscovery. By combining keywords and phrases with Boolean operators, legal professionals can conduct more precise and accurate searches within large volumes of electronically stored information (ESI).

A Keyword Search is a fundamental search method in eDiscovery that locates relevant electronically stored information (ESI) based on specific words or phrases. Legal professionals use keyword searches to identify pertinent documents, emails, or other digital content in the context of litigation, regulatory inquiries, or investigations.

Concept Search is an advanced eDiscovery technique that utilises natural language processing and semantic analysis to identify documents containing similar ideas or themes, rather than relying on specific keywords or phrases. This approach enables legal professionals to uncover relevant electronically stored information (ESI) that might otherwise be missed using traditional search methods.

Near-duplicate Detection is an eDiscovery process that identifies and groups documents with high similarity in content or structure, even if they are not exact duplicates. By consolidating near-duplicates, legal professionals can streamline the review process, reduce redundancies, and ensure consistent coding and analysis across related documents.

Email Threading is an eDiscovery technique used to organise and analyse email messages by grouping related conversations together based on common elements, such as subject lines, senders, and recipients. By identifying and visualising relationships between emails, email threading helps legal professionals review and understand communication patterns more efficiently, reducing duplication and streamlining the eDisclosure process.

TAR is an advanced eDiscovery method that utilises machine learning algorithms and artificial intelligence to automate the document review process. By prioritising relevant documents and reducing manual review efforts, TAR accelerates the eDiscovery process, improves accuracy, and lowers costs associated with large-scale document reviews.

Sentiment Analysis, also known as opinion mining or emotion AI, is a natural language processing technique used to identify and extract subjective information, such as emotions, opinions, and attitudes, from text data. In the context of eDiscovery, sentiment analysis can help legal professionals gain insights into the tone and sentiment of communications, which can provide additional context and reveal potential areas of interest within electronically stored information (ESI).

Predictive Coding is an eDiscovery technique that employs machine learning algorithms to categorise documents based on their relevance to a specific legal matter. This process involves training the algorithm with a sample set of documents reviewed by legal experts, allowing the system to predict the relevance of the remaining documents, thus streamlining the review process and reducing costs.

Data Analytics involves the systematic examination and interpretation of electronically stored information (ESI) to identify patterns, trends, and relationships that can inform decision-making, case strategy, or compliance efforts. In the context of eDisclosure and eDiscovery, data analytics tools and techniques help legal professionals uncover relevant insights, streamline the review process, and improve overall case efficiency.

Document Production is the final stage of the eDiscovery process, where relevant, non-privileged electronically stored information (ESI) is exchanged between parties involved in litigation, regulatory inquiries, or investigations. The production process typically involves converting documents into an agreed-upon format, redacting sensitive information, and ensuring compliance with disclosure obligations.

Rolling Production is an approach in eDiscovery where documents are reviewed and produced to the opposing party in a series of smaller, incremental batches rather than one large, final production. This method can help manage large volumes of data, expedite the disclosure process, and allow for ongoing communication and negotiation between parties.

Quality Control, in the context of eDiscovery, refers to the process of ensuring the accuracy, completeness, and consistency of data collection, processing, review, and production. QC measures may include sampling, random audits, and automated checks to identify potential issues, such as missed documents, incorrect coding, or inconsistent redactions.

Redaction is the process of obscuring or removing sensitive or confidential information from documents before production in eDiscovery. This technique ensures that personally identifiable information (PII), trade secrets, or privileged content is protected, while still complying with legal and regulatory disclosure requirements.

A Load File is a specially formatted file that contains metadata, text, and other information associated with electronically stored information (ESI) to facilitate data import and export between eDiscovery software platforms. Load files enable legal professionals to efficiently transfer and organise large volumes of data during the processing, review, and production stages of eDisclosure.

A Privilege Log is a detailed record of documents withheld from production during eDiscovery due to attorney-client privilege, work product protection, or other legal privileges. The log typically includes information such as document date, author, recipient, and a description of the privilege asserted, ensuring transparency and compliance with discovery obligations.

Defensibility, in the context of eDiscovery and eDisclosure, refers to the ability to demonstrate that the processes and procedures used to identify, collect, preserve, process, review, and produce electronically stored information (ESI) were conducted in a legally sound, consistent, and transparent manner. A defensible eDiscovery approach minimises the risk of spoliation, sanctions, or adverse judgments and helps establish credibility and trust with opposing parties, courts, and regulatory authorities. Defensibility relies on proper documentation, chain of custody, adherence to industry best practices, and the use of reliable technology and tools.

Civil Procedure Rules are the legal framework governing civil litigation in England and Wales. They provide guidelines on how civil cases should be conducted, including the management and handling of eDisclosure and eDiscovery processes.

The Jackson Reforms are a series of civil litigation reforms in England and Wales introduced in 2013, following a review conducted by Lord Justice Jackson. These reforms aimed to streamline the litigation process, reduce costs, and increase efficiency in civil cases. The reforms include changes to the Civil Procedure Rules, cost management, and the emphasis on proportionality in eDisclosure.

Practice Direction 31B is a supplement to the Civil Procedure Rules that provides specific guidance on the disclosure of electronically stored information (ESI) in civil litigation cases in England and Wales. It outlines the principles and procedures related to the identification, preservation, collection, review, and production of ESI in the context of eDisclosure.

The Sedona Principles are a set of best practice guidelines developed by The Sedona Conference, a US-based legal research and educational institute, to address various issues related to eDiscovery, including the preservation, management, and production of electronically stored information (ESI). While primarily focused on the US legal system, the Sedona Principles have influenced eDisclosure practices and policies globally.

The Proportionality Principle is a key concept in eDisclosure and eDiscovery that requires the process of identifying, collecting, reviewing, and producing electronically stored information (ESI) to be reasonable and proportionate to the value, complexity, and importance of the case. This principle is reinforced by the Jackson Reforms and is a critical consideration in the management of eDisclosure processes.

The Pyrrho Investments Judgment is a landmark ruling by the High Court of England and Wales in the case of Pyrrho Investments Ltd v MWB Property Ltd (2016). The judgment approved the use of predictive coding in eDisclosure, marking the first time a UK court endorsed this technology-assisted review method. The Pyrrho Investments Judgment has set a precedent for the acceptance and adoption of predictive coding and other advanced eDiscovery tools in UK litigation.

The Da Silva Moore Judgment is a landmark ruling by the United States District Court in the case of
Da Silva Moore v Publicis Groupe (2012). The judgment endorsed the use of predictive coding in eDiscovery, marking the first time a US court approved this technology-assisted review method. The Da Silva Moore Judgment has influenced the global acceptance and adoption of predictive coding and other advanced eDiscovery tools in legal proceedings.

Cost Shifting is a legal principle that allows courts to allocate some or all of the costs associated with eDiscovery to the requesting party, rather than the producing party. This may occur when the burden or expense of producing the requested electronically stored information (ESI) is deemed disproportionate to the benefits or relevance of the data in the case.

A Disclosure Review Document (DRD) is a document used in the eDisclosure process, particularly under the disclosure pilot scheme for the Business and Property Courts in England and Wales (Practice Direction 51U). The DRD is a collaborative tool that assists parties in scoping the disclosure process, identifying the main issues in dispute, and agreeing on the appropriate disclosure models to be used for each issue. The DRD is designed to facilitate communication and cooperation between parties, ensuring a more efficient and proportionate approach to the eDisclosure process in civil litigation.

The Disclosure Pilot Scheme is a two-year initiative introduced in 2019 for the Business and Property Courts in England and Wales, governed by Practice Direction 51U. The scheme aims to streamline the eDisclosure process, reduce costs, and increase efficiency by encouraging parties to collaborate and agree on the scope of disclosure in a more focused and proportionate manner. The Disclosure Pilot Scheme introduces new disclosure models, a greater emphasis on cooperation between parties, and the use of Disclosure Review Documents (DRDs) to facilitate communication and agreement on disclosure-related matters. The success of the pilot scheme is continually assessed, and its principles may be incorporated into future revisions of the Civil Procedure Rules (CPR) relating to eDisclosure.

File Hashing is a process that generates a unique, fixed-length string of characters, called a hash value, based on the content of a digital file. In eDiscovery, file hashing is used to verify the integrity and authenticity of electronically stored information (ESI) by comparing original and copied files’ hash values, ensuring that digital evidence remains unaltered and admissible in legal proceedings.

TIFF is a widely used image file format that supports lossless compression, making it suitable for storing high-resolution images and scanned documents. In eDiscovery, TIFF files are often used as a standard format for document productions, providing a consistent and easily viewable representation of electronically stored information (ESI).

Slack Space, also known as file slack, refers to the unused space between the end of a file and the end of the storage unit (cluster) it occupies on a storage device. In eDiscovery, slack space can contain fragments of deleted or overwritten files, which may be recoverable and relevant to an investigation or legal case.

Data Recovery is the process of retrieving lost, deleted, or inaccessible electronically stored information (ESI) from damaged or corrupted digital storage devices, such as hard drives, servers, or mobile devices. In eDiscovery, data recovery techniques, including file carving and file system analysis, can help legal professionals uncover relevant data that might not be available through traditional data collection methods.

Incident Response is the systematic approach to identifying, containing, investigating, and recovering from cybersecurity incidents, such as data breaches, malware attacks, or unauthorised access. In the context of eDisclosure and eDiscovery, incident response plans and procedures can help organisations preserve electronically stored information (ESI) and mitigate the risk of legal, regulatory, or reputational consequences.

Ephemeral Data is temporary or transient digital information that is designed to be deleted or overwritten after a short period or upon fulfilment of a specific condition. Examples include chat messages in secure messaging apps or temporary files created by applications. In eDiscovery, ephemeral data may present challenges in data preservation, collection, and analysis due to its short lifespan and volatile nature.

File System Analysis is a digital forensics technique that involves examining the structure, metadata, and content of a file system on a storage device to recover and analyse electronically stored information (ESI). In eDiscovery, file system analysis can help legal professionals uncover relevant data, including deleted or hidden files, and reconstruct the timeline of events related to a legal case or investigation.

Structured Data refers to information that is organised and formatted in a consistent, predefined structure, such as databases, spreadsheets, or XML files. In eDisclosure and eDiscovery, structured data may need to be processed, analysed, and integrated with unstructured data (e.g., emails, documents) to provide a complete understanding of the relevant electronically stored information (ESI) in a case.

File Carving is a digital forensics technique used to recover lost, deleted, or fragmented files from a storage device by analysing raw data without relying on file system metadata. In the context of eDiscovery, file carving can help legal professionals retrieve and reconstruct relevant electronically stored information (ESI) that may not be accessible through traditional data recovery methods.

Log Analysis is the process of reviewing and interpreting digital log files generated by software applications, operating systems, and network devices to identify patterns, trends, or anomalies that may indicate security incidents or relevant events. In the context of eDiscovery, log analysis can provide valuable insights into user activities, data access, and system events, supporting the identification and preservation of electronically stored information (ESI).

Network Forensics is a branch of digital forensics focused on monitoring, capturing, and analysing network traffic and communications to uncover evidence, identify security incidents, or reconstruct events related to a legal case or investigation. In eDiscovery, network forensics can help legal professionals identify and preserve relevant electronically stored information (ESI) transmitted across networks.

Secure Data Erasure, also known as data sanitisation, is the process of permanently and irreversibly removing or destroying electronically stored information (ESI) from digital storage devices to prevent unauthorised access, disclosure, or recovery. In eDisclosure and eDiscovery, secure data erasure techniques may be required to comply with data privacy regulations, confidentiality obligations, or data retention policies.

A Data Breach Investigation is a systematic examination of a security incident involving the unauthorised access, disclosure, or theft of sensitive or protected information. In the context of eDiscovery, a data breach investigation may involve the collection, preservation, and analysis of electronically stored information (ESI) to identify the source, scope, and impact of the breach, as well as potential legal or regulatory implications.

eDiscovery Project Management involves the planning, coordination, and execution of tasks and resources associated with the eDisclosure process, from identification and preservation of electronically stored information (ESI) to review, analysis, and production.

OCR is a technology that converts printed or handwritten text within images, scanned documents, or PDF files into machine-readable, searchable text. In eDiscovery, OCR enables legal professionals to search, analyse, and review non-text-based documents, improving the efficiency and accuracy of the document review process.

A Custodian, in the context of eDiscovery, refers to an individual or entity responsible for the creation, storage, or management of electronically stored information (ESI) relevant to a legal case, regulatory inquiry, or investigation. Custodians can include employees, contractors, or third-party service providers, and their data sources must be identified and preserved during the eDisclosure process.

Bates Numbering is a unique, sequential identifier assigned to each page or document during the eDiscovery process. This labelling system helps legal professionals organise, reference, and track electronically stored information (ESI) throughout the document review, analysis, and production stages, ensuring consistency and accuracy in legal proceedings.

Litigation Support refers to a range of services and tools designed to assist lawyers and legal teams in managing electronically stored information (ESI) throughout the eDisclosure and eDiscovery processes. These services can include data collection, processing, review, analysis, production, and project management, as well as providing technical expertise and training on eDiscovery software and platforms.

Data Migration is the process of transferring electronically stored information (ESI) from one storage system, format, or platform to another while maintaining its integrity, accessibility, and usability. In eDiscovery, data migration may be necessary to consolidate data sources, implement new technologies or platforms, or comply with data retention policies and legal requirements.

Spoliation is the intentional or negligent destruction, alteration, or concealment of electronically stored information (ESI) that is relevant to ongoing or anticipated litigation, regulatory inquiries, or investigations. Spoliation can result in severe legal penalties, including sanctions, adverse inferences, or dismissal of claims, and underscores the importance of proper data preservation practices in eDiscovery.

Cross-border eDiscovery refers to the collection, processing, review, and production of electronically stored information (ESI) across multiple jurisdictions, often involving different legal systems, data protection regulations, and cultural practices. Legal professionals must navigate complex international laws, privacy concerns, and logistical challenges to ensure compliance and effective management of cross-border eDisclosure.

Steganography is the practice of concealing information within other data, such as images, audio files, or text documents, to avoid detection. In the context of eDiscovery, steganography can present challenges for legal professionals and digital forensic experts in identifying and analysing hidden or obfuscated electronically stored information (ESI) relevant to a legal case or investigation.

Unicode is a universal character encoding standard used to represent text and symbols from all writing systems and languages in a consistent, unique manner. In eDiscovery, Unicode support is essential for accurately processing, searching, and analysing multilingual electronically stored information (ESI), ensuring that relevant data is accessible and comprehensible to legal professionals and reviewers.

Personal Identifiable Information (PII) is any information that can be used to identify, contact, or locate a specific individual, either directly or in combination with other data. Examples of PII include names, addresses, phone numbers, and email addresses. In eDisclosure and eDiscovery, legal professionals must handle PII in accordance with data privacy regulations, such as the GDPR, and implement appropriate security measures to protect individuals’ privacy.

Data Retention refers to the policies and practices governing the storage, management, and disposal of an organisation’s electronically stored information (ESI) in accordance with legal, regulatory, and operational requirements. Effective data retention strategies help organisations mitigate the risk of data spoliation, non-compliance, and excessive eDiscovery costs by ensuring that relevant data is preserved, accessible, and defensible.

Containerisation, in the context of eDiscovery and eDisclosure, refers to the practice of storing and managing multiple files or data objects within a single container file, such as a ZIP or RAR archive. Containerisation can help reduce storage requirements, simplify data transfers, and improve security by consolidating and compressing files. However, during the eDisclosure process, container files often need to be expanded, indexed, and processed individually to ensure the proper identification, review, and analysis of the relevant electronically stored information (ESI) contained within them.

Endpoint Detection and Response (EDR) is a cybersecurity solution designed to monitor, detect, and respond to potential threats and suspicious activities on endpoints, such as computers, servers, and mobile devices. In eDiscovery, EDR tools can help identify and preserve relevant electronically stored information (ESI) by providing visibility into data access, transmission, and potential data breaches.

In conclusion, our extensive eDisclosure Glossary of Terms serves as an invaluable resource for legal professionals and those involved in the eDisclosure process, offering insights into a wide range of terms, concepts, and technologies.

By staying informed and up-to-date with the latest developments, you can ensure a more efficient, accurate, and defensible approach to eDisclosure in the ever-changing UK legal landscape. Armed with this comprehensive glossary, you’ll be better equipped to navigate the complexities of eDisclosure and make informed decisions that contribute to the successful resolution of litigation and regulatory matters.