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Electronic Discovery

Defendant Compelled by Court to Produce Metadata – eDiscovery Case Law

Remember when we talked about the issue of metadata spoliation resulting from “drag and drop” to collect files?  Here’s a case where it appears that method may have been used, resulting in a judgment against the producing party.

In AtHome Care, Inc. v. The Evangelical Lutheran Good Samaritan Society, No. 1:12-cv-053-BLW (D. ID. Apr. 30, 2013), Idaho District Judge B. Lynn Winmill granted the plaintiff’s motion to compel documents, ordering the defendant to identify and produce metadata for the documents in this case.

In this pilot project contract dispute between two health care organizations, the plaintiff filed a motion to compel after failing to resolve some of the discovery disputes with the defendant “through meet and confers and informal mediation with the Court’s staff”.  One of the disputes was related to the omission of metadata in the defendant’s production.

Judge Winmill stated that “Although metadata is not addressed directly in the Federal Rules of Civil Procedure, it is subject to the same general rules of discovery…That means the discovery of metadata is also subject to the balancing test of Rule 26(b)(2)(C), which requires courts to weigh the probative value of proposed discovery against its potential burden.” {emphasis added}

“Courts typically order the production of metadata when it is sought in the initial document request and the producing party has not yet produced the documents in any form”, Judge Winmill continued, but noted that “there is no dispute that Good Samaritan essentially agreed to produce metadata, and would have produced the requested metadata but for an inadvertent change to the creation date on certain documents.”

The plaintiff claimed that the system metadata was relevant because its claims focused on the unauthorized use and misappropriation of its proprietary information and whether the defendant used the plaintiff’s proprietary information to create their own materials and model, contending “that the system metadata can answer the question of who received what information when and when documents were created”.  The defendant argued that the plaintiff “exaggerates the strength of its trade secret claim”.

Weighing the value against the burden of producing the metadata, Judge Winmill ruled that “The requested metadata ‘appears reasonably calculated to lead to the discovery of admissible evidence.’ Fed.R. Civ.P. 26(b)(1). Thus, it is discoverable.” {emphasis added}

“The only question, then, is whether the burden of producing the metadata outweighs the benefit…As an initial matter, the Court must acknowledge that Good Samaritan created the problem by inadvertently changing the creation date on the documents. The Court does not find any degree of bad faith on the part of Good Samaritan — accidents happen — but this fact does weight in favor of requiring Good Samaritan to bear the burden of production…Moreover, the Court does not find the burden all that great.”

Therefore, the plaintiff’s motion to compel production of the metadata was granted.

So, what do you think?  Should a party be required to produce metadata?  Please share any comments you might have or if you’d like to know more about a particular topic.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

Version 1 of the EDRM Enron Data Set NOW AVAILABLE – eDiscovery Trends

Last week, we reported from the Annual Meeting for the Electronic Discovery Reference Model (EDRM) group and discussed some significant efforts and accomplishments by each of the project teams within EDRM.  That included an update from the EDRM Data Set project, where an effort was underway to identify and remove personally-identifiable information (“PII”) data from the EDRM Data Set.  Now, version 1 of the Data Set is completed and available for download.

To recap, the EDRM Enron Data Set, sourced from the FERC Enron Investigation release made available by Lockheed Martin Corporation, has been a valuable resource for eDiscovery software demonstration and testing (we covered it here back in January 2011).  Initially, the data was made available for download on the EDRM site, then subsequently moved to Amazon Web Services (AWS).  However, after much recent discussion about PII data (including social security numbers, credit card numbers, dates of birth, home addresses and phone numbers) available within FERC (and consequently the EDRM Data Set), the EDRM Data Set was taken down from the AWS site.

Yesterday, EDRM, along with Nuix, announced that they have republished version 1 of the EDRM Enron PST Data Set (which contains over 1.3 million items) after cleansing it of private, health and personal financial information. Nuix and EDRM have also published the methodology Nuix’s staff used to identify and remove more than 10,000 high-risk items.

As noted in the announcement, Nuix consultants Matthew Westwood-Hill and Ady Cassidy used a series of investigative workflows to identify the items, which included:

  • 60 items containing credit card numbers, including departmental contact lists that each contained hundreds of individual credit cards;
  • 572 items containing Social Security or other national identity numbers—thousands of individuals’ identity numbers in total;
  • 292 items containing individuals’ dates of birth;
  • 532 items containing information of a highly personal nature such as medical or legal matters.

While the personal data was (and still is) available via FERC long before the EDRM version was created, completion of this process will mean that many in the eDiscovery industry that rely on this highly useful data set for testing and software demonstration can now use a version which should be free from sensitive personal information!

For more information regarding the announcement, click here. The republished version 1 of the Data Set, as well as the white paper discussing the methodology is available at nuix.com/enron.  Nuix is currently applying the same methodology to the EDRM Enron Data Set v2 (which contains nearly 2.3 million items) and will publish to the same site when complete.

So, what do you think?  Have you used the EDRM Enron Data Set?  If so, do you plan to download the new version?  Please share any comments you might have or if you’d like to know more about a particular topic.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

Plaintiff Granted Access to Defendant’s Database – eDiscovery Case Law

Last week in the EDRM Annual Meeting, one of our group discussion sessions was centered on production and presentation of native files – a topic which has led to the creation of a new EDRM project to address standards for working with native files in these areas.  This case provides an example of a unique form of native production.

In Advanced Tactical Ordnance Systems, LLC v. Real Action Paintball, Inc., No. 1:12-CV-296 (N.D. Ind. Feb. 25, 2013), Indiana Magistrate Judge Roger B. Cosbey took the unusual step of allowing the plaintiff direct access to a defendant company’s database under Federal Rule of Civil Procedure 34 because the plaintiff made a specific showing that the information in the database was highly relevant to the plaintiff’s claims, the benefit of producing it substantially outweighed the burden of producing it, and there was no prejudice to the defendant.

In this case involving numerous claims, including trademark infringement and fraud, Advanced Tactical Ordnance Systems LLC (“ATO”) sought expedited discovery after it obtained a temporary restraining order against the defendants. One of its document requests sought the production of defendant Real Action Paintball’s OS Commerce database to search for responsive evidence. Real Action objected, claiming that the request asked for confidential and sensitive information from its “most important asset” that would give the plaintiff a competitive advantage and that the request amounted to “‘an obvious fishing expedition.”

To decide the issue, Judge Cosbey looked to Federal Rule of Civil Procedure 34(a)(1)(A), which allows parties to ask to “inspect, copy, test, or sample . . . any designated documents or electronically stored information . . . stored in any medium from which information can be obtained either directly or, if necessary, after translation by the responding party into a reasonably usable form.” The advisory committee notes to this rule explain that the testing and sampling does not “create a routine right of direct access to a party’s electronic information system, although such access might be justified in some circumstances.” Judge Cosbey also considered whether the discovery request was proportionate under Federal Rule of Civil Procedure 26(b)(2)(C)(iii), comparing the “burden or expense” of the request against its “likely benefit, considering the needs of the case, the amount in controversy, the parties’ resources, the importance of the issues at stake in the action, and the importance of the discovery in resolving the issues.”

Based on its analysis, Judge Cosbey permitted ATO’s request. The benefits of allowing the plaintiff to access the defendant’s OS Commerce database outweighed the burden of producing data from it, especially because the parties had entered a protective order. The information was particularly important to the plaintiff’s argument that the defendant was using hidden metatags referencing ATO’s product to improve its results in search engines, thereby stealing the plaintiff’s customers.

Despite the defendant company’s claims that the information the database contained was proprietary and potentially harmful to the business’s competitive advantage, the court found the company failed to establish how the information in the database constituted a trade secret or how its disclosure could harm the company, especially where much of the information had already been produced or was readily available on the company’s website. Moreover, the company could limit the accessibility of the database to “‘Attorneys’ Eyes Only.’”

So, what do you think?  Was it appropriate to grant the plaintiff direct access to the defendant’s database?  Please share any comments you might have or if you’d like to know more about a particular topic.

Case Summary Source: Applied Discovery (free subscription required).  For eDiscovery news and best practices, check out the Applied Discovery Blog here.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

How to Create an Image Using FTK Imager – eDiscovery Best Practices

A few days ago, we talked about the benefits and capabilities of Forensic Toolkit (FTK), which is a computer forensics software application provided by AccessData, as well as how to download your own free copy.  Now, let’s discuss how to create a disk image.

Before we begin, it’s important to note that best practices when creating a disk image includes the use of a write blocker.  Write blockers are devices that allow data to be acquired from a drive without creating the possibility of accidentally damaging the drive contents. They allow read commands to pass but block write commands, protecting the drive contents from being changed.  Tableau and FireFly are two examples of write blockers.

It’s also important to note that while we’re showing you how to “try this at home”, use of a certified forensic collection specialist is recommended when collecting data forensically that could require expert testimony on the collection process.

Create an Image Using FTK Imager

I’m going to create an image of one of my flash drives to illustrate the process.  To create an image, select Create Disk Image from the File menu.

Source Evidence Type: To image an entire device, select Physical Drive (a physical device can contain more than one Logical Drive).  You can also create an image of an Image File, which seems silly, but it could be desirable if, say, you want to create a more compressed version of the image.  You can also image the specific Contents of a Folder or of a Femico Device (which is ideal for creating images of multiple CDs or DVDs with the same parameters).  In this example, we’ll select Physical Drive to create an image of the flash drive.

Source Drive Selection: Based on our selection of physical drive, we then have a choice of the current physical drives we can see, so we select the drive corresponding to the flash drive.

Create Image: Here is where you can specify where the image will be created.  We also always choose Verify images after they are created as a way to run a hash value check on the image file.  You can also Create directory listings of all files in the image after they are created, but be prepared that this will be a huge listing for a typical hard drive with hundreds of thousands of entries.

Select Image Type: This indicates the type of image file that will be created – Raw is a bit-by-bit uncompressed copy of the original, while the other three alternatives are designed for use with a specific forensics program.  We typically use Raw or E01, which is an EnCase forensic image file format.  In this example, we’re using Raw.

Evidence Item Information: This is where you can enter key information about the evidence item you are about to create to aid in documenting the item.  This information will be saved as part of the image summary information once the image is complete.

Select Image Destination: We’ll browse to a folder that I’ve created called “FTKImage” on the C: drive and give the image a file name.  Image Fragment Size indicates the size of each fragment when you want to break a larger image file into multiple parts.  Compression indicates the level of compression of the image file, from 0 (no compression) to 9 (maximum compression – and a slower image creation process).  For Raw uncompressed images, compression is always 0.  Use AD Encryption indicates whether to encrypt the image – we don’t typically select that, instead choosing to put an image on an encrypted drive (when encryption is desired).  Click Finish to begin the image process and a dialog will be displayed throughout the image creation process.  Because it is a bit-by-bit image of the device, it will take the same amount of time regardless of how many files are currently stored on the device.

Drive/Image Verify Results: When the image is complete, this popup window will appear to show the name of the image file, the sector count, computed (before image creation) and reported (after image creation) MD5 and SHA1 hash values with a confirmation that they match and a list of bad sectors (if any).  The hash verification is a key check to ensure a valid image and the hash values should be the same regardless which image type you create.

Image Summary: When the image is complete, click the Image Summary button to see the view a summary of the image that is created, including the evidence item information you entered, drive information, hash verification information, etc.  This information is also saved as a text file.

Directory Listing: If you selected Create directory listings of all files in the image, the results will be stored in a CSV file, which can be opened with Excel.

And, there you have it – a bit-by-bit image of the device!  You’ve just captured everything on the device, including deleted files and slack space data.  Next time, we’ll discuss Adding an Evidence Item to look at contents or drives or images (including the image we created here).

For more information, go to the Help menu to access the User Guide in PDF format.

So, what do you think?  Have you used FTK Imager as a mechanism for eDiscovery collection?  Please share any comments you might have or if you’d like to know more about a particular topic.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

More Updates from the EDRM Annual Meeting – eDiscovery Trends

Yesterday, we discussed some general observations from the Annual Meeting for the Electronic Discovery Reference Model (EDRM) group and discussed some significant efforts and accomplishments by the (suddenly heavily talked about) EDRM Data Set project.  Here are some updates from other projects within EDRM.

It should be noted these are summary updates and that most of the focus on these updates is on accomplishments for the past year and deliverables that are imminent.  Over the next few weeks, eDiscovery Daily will cover each project in more depth with more details regarding planned activities for the coming year.

Model Code of Conduct (MCoC)

The MCoC was introduced in 2011 and became available for organizations to subscribe last year.  To learn more about the MCoC, you can read the code online here, or download it as a 22 page PDF file here.  Subscribing is easy!  To voluntarily subscribe to the MCoC, you can register on the EDRM website here.  Identify your organization, provide information for an authorized representative and answer four verification questions (truthfully, of course) to affirm your organization’s commitment to the spirit of the MCoC, and your organization is in!  You can also provide a logo for EDRM to include when adding you to the list of subscribing organizations.  Pending a survey of EDRM members to determine if any changes are needed, this project has been completed.  Team leaders include Eric Mandel of Zelle Hofmann, Kevin Esposito of Rivulex and Nancy Wallrich.

Information Governance Reference Model (IGRM)

The IGRM team has continued to make strides and improvements on an already terrific model.  Last October, they unveiled the release of version 3.0 of the IGRM.  As their press release noted, “The updated model now includes privacy and security as primary functions and stakeholders in the effective governance of information.”  IGRM continues to be one of the most active and well participated EDRM projects.  This year, the early focus – as quoted from Judge Andrew Peck’s keynote speech at Legal Tech this past year – is “getting rid of the junk”.  Project leaders are Aliye Ergulen from IBM, Reed Irvin from Viewpointe and Marcus Ledergerber from Morgan Lewis.

Search

One of the best examples of the new, more agile process for creating deliverables within EDRM comes from the Search team, which released its new draft Computer Assisted Review Reference Model (CARRM), which depicts the flow for a successful Computer Assisted Review project. The entire model was created in only a matter of weeks.  Early focus for the Search project for the coming year includes adjustments to CARRM (based on feedback at the annual meeting).  You can also still send your comments regarding the model to mail@edrm.net or post them on the EDRM site here.  A webinar regarding CARRM is also planned for late July.  Kudos to the Search team, including project leaders Dominic Brown of Autonomy and also Jay Lieb of kCura, who got unmerciful ribbing for insisting (jokingly, I think) that TIFF files, unlike Generalissimo Francisco Franco, are still alive.  🙂

Jobs

In late January, the Jobs Project announced the release of the EDRM Talent Task Matrix diagram and spreadsheet, which is available in XLSX or PDF format. As noted in their press release, the Matrix is a tool designed to help hiring managers better understand the responsibilities associated with common eDiscovery roles. The Matrix maps responsibilities to the EDRM framework, so eDiscovery duties associated can be assigned to the appropriate parties.  Project leader Keith Tom noted that next steps include surveying EDRM members regarding the Matrix, requesting and co-authoring case-studies and white papers, and creating a short video on how to use the Matrix.

Metrics

In today’s session, the Metrics project team unveiled the first draft of the new Metrics model to EDRM participants!  Feedback was provided during the session and the team will make the model available for additional comments from EDRM members over the next week or so, with a goal of publishing for public comments in the next two to three weeks.  The team is also working to create a page to collect Metrics measurement tools from eDiscovery professionals that can benefit the eDiscovery community as a whole.  Project leaders Dera Nevin of TD Bank and Kevin Clark noted that June is “budget calculator month”.

Other Initiatives

As noted yesterday, there is a new project to address standards for working with native files in the different EDRM phases led by Eric Mandel from Zelle Hofmann and also a new initiative to establish collection guidelines, spearheaded by Julie Brown from Vorys.  There is also an effort underway to refocus the XML project, as it works to complete the 2.0 version of the EDRM XML model.  In addition, there was quite a spirited discussion as to where EDRM is heading as it approaches ten years of existence and it will be interesting to see how the EDRM group continues to evolve over the next year or so.  As you can see, a lot is happening within the EDRM group – there’s a lot more to it than just the base Electronic Discovery Reference Model.

So, what do you think?  Are you a member of EDRM?  If not, why not?  Please share any comments you might have or if you’d like to know more about a particular topic.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

Reporting from the EDRM Annual Meeting and a Data Set Update – eDiscovery Trends

The Electronic Discovery Reference Model (EDRM) Project was created in May 2005 by George Socha of Socha Consulting LLC and Tom Gelbmann of Gelbmann & Associates to address the lack of standards and guidelines in the electronic discovery market.  Now, beginning its ninth year of operation with its annual meeting in St. Paul, MN, EDRM is accomplishing more than ever to address those needs.  Here are some highlights from the meeting, and an update regarding the (suddenly heavily talked about) EDRM Data Set project.

Annual Meeting

Twice a year, in May and October, eDiscovery professionals who are EDRM members meet to continue the process of working together on various standards projects.  This will be my eighth year participating in EDRM at some level and, oddly enough, I’m assisting with PR and promotion (how am I doing so far?).  eDiscovery Daily has referenced EDRM and its phases many times in the 2 1/2 years plus history of the blog – this is our 144th post that relates to EDRM!

Some notable observations about today’s meeting:

  • New Participants: More than half the attendees at this year’s annual meeting are attending for the first time.  EDRM is not just a core group of “die-hards”, it continues to find appeal with eDiscovery professionals throughout the industry.
  • Agile Approach: EDRM has adopted an Agile approach to shorten the time to complete and publish deliverables, a change in philosophy that facilitated several notable accomplishments from working groups over the past year including the Model Code of Conduct (MCoC), Information Governance Reference Model (IGRM), Search and Jobs (among others).  More on that tomorrow.
  • Educational Alliances: For the first time, EDRM has formed some interesting and unique educational alliances.  In April, EDRM teamed with the University of Florida Levin College of Law to present a day and a half conference entitled E-Discovery for the Small and Medium Case.  And, this June, EDRM will team with Bryan University to provide an in-depth, four-week E-Discovery Software & Applied Skills Summer Immersion Program for Law School Students.
  • New Working Group: A new working group to be lead by Eric Mandel of Zelle Hoffman was formed to address standards for working with native files in the different EDRM phases.

Tomorrow, we’ll discuss the highlights for most of the individual working groups.  Given the recent amount of discussion about the EDRM Data Set group, we’ll start with that one today!

Data Set

The EDRM Enron Data Set has been around for several years and has been a valuable resource for eDiscovery software demonstration and testing (we covered it here back in January 2011).  The data in the EDRM Enron PST Data Set files is sourced from the FERC Enron Investigation release made available by Lockheed Martin Corporation.  It was reconstituted as PST files with attachments for the EDRM Data Set Project.  So, in essence EDRM took already public domain available data and made the data much more usable.  Initially, the data was made available for download on the EDRM site, then subsequently moved to Amazon Web Services (AWS).

In the past several days, there has been much discussion about the personally-identifiable information (“PII”) available within the FERC (and consequently the EDRM Data Set), including social security numbers, credit card numbers, dates of birth, home addresses and phone numbers.  Consequently, the EDRM Data Set has been taken down from the AWS site.

The Data Set team led by Michael Lappin of Nuix and Eric Robi of Elluma Discovery has been working on a process (using predictive coding technology) to identify and remove the PII data from the EDRM Data Set.  Discussions about this process began months ago, prior to the recent discussions about the PII data contained within the set.  The team has completed this iterative process for V1 of the data set (which contains 1,317,158 items), identifying and removing 10,568 items with PII, HIPAA and other sensitive information.  This version of the data set will be made available within the EDRM community shortly for peer review testing.  The data set team will then repeat the process for the larger V2 version of the data set (2,287,984 items).  A timetable for republishing both sets should be available soon and the efforts of the Data Set team on this project should pay dividends in developing and standardizing processes for identifying and eliminating sensitive data that eDiscovery professionals can use in their own data sets.

The team has also implemented a Forensic Files Testing Project site where users can upload their own “modern”, non-copyrighted file samples that are typically encountered during electronic discovery processing to provide a more diverse set of data than is currently available within the Enron data set.

So, what do you think?  How has EDRM impacted how you manage eDiscovery?  Please share any comments you might have or if you’d like to know more about a particular topic.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

Skip the HASH When Deduping Outlook MSG Files – eDiscovery Best Practices

As we discussed recently in this blog, Microsoft® Outlook emails can take many forms.  One of those forms is the MSG file extension, which is used to represent a self-contained unit for an individual message “family” (email and its attachments).  MSG files can exist on your computer in the same folders as Word, Excel and other data files.  But, when it comes to deduping those MSG files, the approach to do so is typically different.

A few years ago, I was assisting a client and collecting emails from their email archiving system for discovery, outputting the selected emails to individual MSG files (per their request).  Because this was an enterprise-wide search of email archives, the searches that I performed found the same emails again and again in different custodian folders.  There was literally hundreds of thousands of duplicate emails in this collection.  Of course, this is typical – anytime you send an email to three co-workers, all four of you have a copy of the email (assuming none of you deleted it).  If the email is responsive and your goal is to dedupe across custodians, you only want to review and produce one copy, not four.

However, had I performed a HASH value identification of duplicates on those output MSG files, I would find no duplicates.  Why is that?

That’s because each MSG file contains a field which stores the Creation Date and Time. Because this value will be set at the date and time the MSG is saved, two emails with otherwise identical content will not be considered duplicates based on the HASH value.  Remember how “drag and drop” sets the Creation Date and Time of the copy to the current date and time?  The same thing happens when an MSG file is created.

Hmmm, what to do?  Typically, the approach for MSG files is to use key metadata fields to identify duplicates.  Many processing vendors use a typical combination of fields that consist of: From, To, CC, BCC, Subject, Attachment Name, Sent Date/Time and Body of the email.  Some use those fields only on MSG files; others use it on all emails (to dedupe individual emails within MSG files against those same emails within an OST or a PST file).

So, if you’re hungry to eliminate duplicates from your collection of MSG files, skip the HASH and use the metadata fields.  It’s much more (ful)filling.

So, what do you think?  Have you encountered any challenges when it comes to deduping emails?  Please share any comments you might have or if you’d like to know more about a particular topic.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

When Lawyers Get Sued, They Have Preservation Obligations Too – eDiscovery Case Law

In Distefano v. Law Offices of Barbara H. Katsos, PC., No. CV 11-2893 (JS) (AKT) (D. ED NY Mar. 29, 2013), New York Magistrate Judge A. Kathleen Tomlinson found that the defendant (an attorney who was being sued by the plaintiff she previously represented for breach of contract, negligence/legal malpractice, and breach of fiduciary duty/duty of care) had a duty to preserve information from a discarded computer and ordered a hearing for the defendant to address a number of questions to determine the potential relevance of the destroyed data and whether the defendant had a sufficiently culpable state of mind.

The plaintiff alleged professional negligence by the defendant related to her representation of his franchise business for Cold Stone Creamery stores.  During a Discovery Status Conference, it was revealed that the defendant had gotten rid of her computer before the litigation began, as she noted in her affidavit that she was advised by a third-party individual who fixed her office computers that they could not be repaired.  As she used AOL for email correspondence, she contacted AOL “to inquire if emails from several years ago could be recovered by AOL”, but was told that they “could not recover emails from several years ago for the stated email address”.  After receiving the defendant’s affidavit, the plaintiff filed a motion for spoliation.

With regard to the defendant’s duty to preserve information related to her representation of the plaintiff, Judge Tomlinson stated:

“The Court concludes that Katsos’ duty to preserve documents arose as early as late February 2009, when Michael DiStefano terminated the attorney-client relationship between Plaintiffs and Defendants.”  On February 24, 2009, the plaintiff send the defendant a letter terminating the representation “immediately” and stated that he would “communicate with you further, in writing, so as to explain the reasons why I am discharging you.”  Noting that the “language of Michael DiStefano’s letter gives the appearance that Distefano was not satisfied with Katsos’ work”, Judge Tomlinson also noted that “[i]n assessing whether litigation was reasonably foreseeable in these circumstances, the Court cannot ignore the fact that Katsos is an attorney and should have been attuned to the prospect of litigation.”

To determine the defendant’s culpable state of mind, Judge Tomlinson ordered a hearing on May 13 for the defendant to “be prepared to testify regarding, among other things, the following areas:

  1. Katsos’ normal document preservation/retention/deletion/destruction practices;
  2. the number of computers utilized in her office prior to 2009, when the computers were purchased, and the specific circumstances surrounding the breakdown of each of those computers;
  3. the service agreements for those computers and the vendor(s) used;
  4. whether Katsos maintained a network server;
  5. AOL’s automatic deletion policies to the extent they were explained to Katsos;
  6. a complete list of every email address used by Defendant Law Offices of Barbara H. Katsos, PC and Defendant Barbara Katsos or her staff to communicate with Plaintiffs;
  7. Katsos’ attempts to gain access to the email accounts used by her paralegals and interns referenced in Paragraph 5 of Katsos Aff. II and page 16 of Plaintiffs’ Memorandum;
  8. the document preservation steps undertaken by Katsos when Plaintiffs instituted an adversary proceeding against her in March of 2010;
  9. the retention and utilization of the services of Jan Sloboda.” (the third-party individual that advised her to replace her computers)

The plaintiffs were also ordered to identify “general categories of documents that have been adversely affected” to help determine the relevance of the data in question and were permitted to question the defendant at the hearing.

So, what do you think?  Was this an appropriate course of action to determine whether sanctions are appropriate?  Please share any comments you might have or if you’d like to know more about a particular topic.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

Image is Everything, But it Doesn’t Have to Cost Anything – eDiscovery Best Practices

Do you remember this commercial?  Can you believe it’s 23 years old?

Let’s recap.  So far, in our discussion of free utilities for collection of data for eDiscovery, we’ve discussed the pitfalls of using drag and drop, the benefits of Robocopy (illustrating with the same example copy) and the benefits (and pitfalls) of Richcopy for targeted collection.  But, are there any free tools that will enable you to perform a bit-by-bit forensic image copy that includes deleted files and slack space data?  Yes, there is.

Forensic Toolkit (FTK) is a computer forensics software application provided by AccessData.  The toolkit includes a standalone disk imaging program called FTK Imager.  FTK Imager is a free tool that saves an image of a hard disk in one file or in segments that may be reconstructed later. It calculates MD5 or SHA-1 hash values of the original and the copy, confirming the integrity of the data before closing the files.

With FTK Imager, you can:

  • Create forensic images of local hard drives, floppy diskettes, Zip disks, CDs, and DVDs, entire folders, or individual files from various places within the media.
  • Preview files and folders on local hard drives, network drives, floppy diskettes, Zip disks, CDs, and DVDs – including files located in container files such as ZIP or RAR files.
  • Preview the contents of forensic images stored on the local machine or on a network drive.
  • Mount an image for a read-only view that leverages Windows Explorer to see the content of the image exactly as the user saw it on the original drive.
  • Export files and folders from forensic images.
  • See and recover files that have been deleted from the Recycle Bin, but have not yet been overwritten on the drive.
  • Create MD5 or SHA-1 hashes of files and generate hash reports for regular files and disk images (including files inside disk images) that you can later use as a benchmark to prove the integrity of your case evidence. When a full drive is imaged, a hash generated by FTK Imager can be used to verify that the image hash and the drive hash match after the image is created, and that the image has remained unchanged since acquisition.

Like all forensically-sound collection tools, it retains the file system metadata (and the file path) and creates a log of the files copied.  You can also provide Case Number, Evidence Number, Unique Description, Examiner, and any Notes for tracking purposes to aid in chain of custody tracking.

To download FTK Imager, you can go to the AccessData Product Downloads page here.  Look for the link for FTK Imager in “Current Releases” (it’s currently the seventh item on the list) and open the folder and select the current version of FTK Imager (currently v3.1.2, released on 12/13/12).

Next week, we will begin to discuss how to use FTK Imager to preview files, create forensic images, recover deleted files and use hash values to validate your image.

So, what do you think?  Have you used FTK Imager as a mechanism for eDiscovery collection?  Please share any comments you might have or if you’d like to know more about a particular topic.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.

Court Rejects Defendants’ Claim of Undue Burden in ERISA Case – eDiscovery Case Law
 

In the case we covered on Monday, the court ruled for the defendant in their effort to avoid what they felt to be undue burden and expense in preserving data.  Here is another case where the defendant made an undue burden claim, but with a different result.

In the case In re Coventry Healthcare, Inc.: ERISA Litigation, No. AW 09-2661 (D. Md. Mar. 21, 2013), Maryland Magistrate Judge Jillyn K. Schulze rejected the defendants’ claim of undue burden where they failed to suggest alternatives to using the plaintiffs’ search terms and where they could enter a clawback order to eliminate the cost of reviewing the data for responsiveness and privilege.

In this Employee Retirement Income Security Act (ERISA) class action, a discovery dispute arose when the defendants filed a motion to curtail the relevant time frame for discovery due in part to the burden it would impose on them. The plaintiffs sought discovery from February 9, 2007 to October 22, 2008; the defendants asked the court to limit it to January 1, 2008 to June 30, 2008.

The defendants relied on Rule 26(b)(2)(C)(iii) to establish that the burden of producing the data outweighed any benefit it offered the plaintiffs. Judge Schulze noted that the “party seeking to lessen the burden of responding to electronic records discovery ‘bears the burden of particularly demonstrating that burden and of providing suggested alternatives that reasonably accommodate the requesting party’s legitimate discovery needs’”.

Here, the defendants claimed they tested the plaintiffs’ proposed search terms on the custodians’ data and hit 200,000 documents. They claimed it would cost roughly $388,000 to process, host, and review the data for responsiveness and privilege. However, the defendants did not suggest “any alternative measures that could reasonably accommodate Plaintiffs’ discovery needs other than negotiating more refined search terms.”

In response, the plaintiffs argued they had tried to collaborate with the defendants to “develop appropriate searches for ESI by limiting the searches to certain designated custodians” and by shortening the discovery period by three months.

Judge Schulze found that the narrowing of the discovery period would reduce the costs, and that “a clawback order can protect Defendants against a claim of waiver, such that Defendants need no longer bear the cost of reviewing the ESI for responsiveness and privilege.” Finally, “[t]o further reduce any undue burden, Plaintiffs may need to refine their proposed search terms to narrow the pool of potentially relevant documents.”  With these options available, Judge Schulze found that the defendants had not met their burden to show that producing the evidence would be unduly burdensome.

So, what do you think?  Should the defendant’s request have been granted?  Please share any comments you might have or if you’d like to know more about a particular topic.

Case Summary Source: Applied Discovery (free subscription required).  For eDiscovery news and best practices, check out the Applied Discovery Blog here.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by CloudNine Discovery. eDiscoveryDaily is made available by CloudNine Discovery solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscoveryDaily should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.