Close
Enter your
text here
Posts By :

Doug Austin

eDiscovery Trends: Metadata Mining Ethics
 

Years ago, I put together a CLE course about metadata awareness and how hidden data (such as tracked changes and comments) can cause embarrassment or even inadvertent disclosures in eDiscovery.  The production of metadata with ESI continues to be a big issue in eDiscovery and organizations need to consider how to handle that metadata (especially if it’s hidden), to avoid issues.

For those who don’t know, metadata can be simply defined as “data about data”, which is to say it’s the data that describes each file and includes information such as when it was created, when it was last modified and who last modified it.  Metadata can often be used in identifying responsive files based on time frame (of creation or last editing) or other criteria.

Many types of files can contain other hidden metadata, such as a record the changes made to a file, who made those changes, and any comments that those parties may have also added (for example, Microsoft Word has Tracked Changes and Comments that aid in collaboration to obtain feedback from one or multiple parties regarding the content of the document).  Embedded objects can also be hidden, for example, depending on how you embed an Excel table into a Word document; the entire Excel file may be accessible within the document, even though only a small part of it is displayed.

Last fall, the American Bar Association published an article with a look at metadata ethics opinions, which was also recently referenced in this article.  The opinions issued to date have focused on three topics with regard to metadata production:

  • The sender's responsibility when transmitting or producing electronic files;
  • The recipient's right to examine (or "mine") files for metadata; and
  • The recipient's duty to notify the sender if sensitive data is discovered.

Sender’s Responsibility

Jurisdictions agree that an attorney sending or producing ESI has a duty to exercise caution to avoid inadvertently disclosing confidential information, though the level of caution required may vary depending upon the jurisdiction and situation.  In SBA Ethics Opinion 07-03, the State Bar of Arizona's Ethics Committee indicated that level of caution may depend upon "the sensitivity of the information, the potential consequences of its inadvertent disclosure, whether further disclosure is restricted by statute, protective order, or confidentiality agreement, and any special instructions given by the client."

Ignorance of technology is no excuse.  The Colorado Bar Association Ethics Committee states that attorneys cannot limit their duty "by remaining ignorant of technology relating to metadata or failing to obtain competent computer support." (CBA Ethics Opinion 119).

Recipient’s Right to Examine

There is less jurisdictional agreement here.  Colorado, Washington D.C. and West Virginia allow metadata mining unless the recipient is aware that the data was sent unintentionally. On the other hand, New York and Maine prohibit metadata mining – the New York State Bar Association's Committee on Professional Ethics based its decision in part on the "strong public policy in favor of protecting attorney-client confidentiality." (NYSBA Opinion 749).  Minnesota and Pennsylvania have not set a bright-line rule, stating that the decision to allow or prohibit metadata mining should depend on the case.

Recipient’s Duty to Notify

Most jurisdictions rely on their local variation of ABA Model Rule of Professional Conduct 4.4(b), which indicates that an attorney who receives confidential data inadvertently sent is obligated to notify the sender.  Maryland is one exception to that position, stating that "the receiving attorney can, and probably should, communicate with his or her client concerning the pros and cons of whether to notify the sending attorney." (MSBA Ethics Docket 2007-09).

Bottom Line

You may not be able to control what a recipient can do with your inadvertently produced metadata, but you can take steps to avoid the inadvertent production in the first place.  Office 2007 and greater has a built in Document Inspector that eliminates the hidden metadata in Office files, while publishing files to PDF will remove some metadata (the amount of metadata removed depends on the settings).  You can also use a metadata “scrubber” application such as Workshare Protect or Metadata Assistant to remove the metadata – most of these will even integrate with email so that you have the option to “scrub” the file before sending.

So, what do you think?  Have you been “stung” by hidden metadata?  Please share any comments you might have or if you’d like to know more about a particular topic.

eDiscovery Case Law: Privilege Waived for Produced Servers

If you were at the International Legal Technology Association (ILTA) trade show this past August, you may have noticed a huge unfinished building in the middle of the strip – the Fontainebleau Resort.  It sits idle after financing was pulled, forcing Fontainebleau Las Vegas LLC to file for Chapter 11 bankruptcy in June of 2009.  Naturally, lawsuits followed, between the Term Lenders and Fontainebleau Resort, LLC (FRLLC), the third party parent of Fontainebleau Las Vegas – In re Fontainebleau Las Vegas Contract Litig., (S.D. Fla. Jan 7, 2011)

A company that responded to a third party subpoena and court orders compelling production by handing over three servers to lenders without conducting any relevancy review and without reviewing two of the servers for privileged materials waived privilege for documents on the two servers that were not reviewed.

The parent company of a resort in bankruptcy proceedings was served by lenders to the resort with a subpoena for production of documents. The company did not object to the scope of the subpoena, and the court granted a motion of the lenders to compel production. Counsel for the company then halted work by an e-discovery vendor who had completed screening the company’s email server for responsive documents but had not started a privilege review because of concerns that the company could not pay for the services. Counsel for the company also sought to withdraw from the case, but the company was unable to find new counsel.

Rather than seeking a stay or challenging discovery rulings from the court, the company turned over data from a document server, an accounting server, and an email server. According to the court, the three servers were turned over to the lenders without any meaningful review for relevancy or responsiveness. Despite an agreement with the lenders on search terms for the email server, the company produced a 126 gigabyte disk with 700,000 emails from that server and then, without asking for leave of court, was late in producing a privilege log for data on the email server. The lenders sought direction from the court on waiver of privilege and their obligation if they found privileged materials in the data produced by the company. The company for the first time then raised objections to the burdensomeness of the original subpoena served over six months earlier given the company’s lack of resources or employees to conduct a document review.

The court held that the company “waived the attorney-client privilege and work product protection, and any other applicable privileges, for the materials it produced from two of three computer servers in what can fairly be described as a data dump as part of a significantly tardy response to a subpoena and to court-ordered production deadlines.” The court stated that in effect, the company “took the two servers, which it never reviewed for privilege or responsiveness, and said to the Term Lenders ‘here, you go figure it out.’”

However, because the company prepared a privilege log for the email server, the court added that privileges were not waived for materials from the email server. Also, the lenders were directed to alert the company to any “clearly privileged material they may find during their review of the production on the documents and accounting servers.” Although the court was not ruling on admissibility at trial of that privileged material, the lenders would be allowed to use it during pre-trial preparations, including depositions.

So, what do you think?  Was justice served?  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.

eDiscovery Best Practices: EDRM Data Set for Great Test Data
 

In it’s almost six years of existence, the Electronic Discovery Reference Model (EDRM) Project has implemented a number of mechanisms to standardize the practice of eDiscovery.  Having worked on the EDRM Metrics project for the past four years, I have seen some of those mechanisms implemented firsthand.

One of the most significant recent accomplishments by EDRM is the EDRM Data Set.  Anyone who works with eDiscovery applications and processes understands the importance to be able to test those applications in as many ways as possible using realistic data that will illustrate expected results.  The use of test data is extremely useful in crafting a defensible discovery approach, by enabling you to determine the expected results within those applications and processes before using them with your organization’s live data.  It can also help you identify potential anomalies (those never occur, right?) up front so that you can be proactive to develop an approach to address those anomalies before encountering them in your own data.

Using public domain data from Enron Corporation (originating from the Federal Energy Regulatory Commission Enron Investigation), the EDRM Data Set Project provides industry-standard, reference data sets of electronically stored information (ESI) to test those eDiscovery applications and processes.  In 2009, the EDRM Data Set project released its first version of the Enron Data Set, comprised of Enron e-mail messages and attachments within Outlook PST files, organized in 32 zipped files.

This past November, the EDRM Data Set project launched Version 2 of the EDRM Enron Email Data Set.  Straight from the press release announcing the launch, here are some of the improvements in the newest version:

  • Larger Data Set: Contains 1,227,255 emails with 493,384 attachments (included in the emails) covering 151 custodians;
  • Rich Metadata: Includes threading information, tracking IDs, and general Internet headers;
  • Multiple Email Formats: Provision of both full and de-duplicated email in PST, MIME and EDRM XML, which allows organizations to test and compare results across formats.

The Text REtrieval Conference (TREC) Legal Track project provided input for this version of the data set, which, as noted previously on this blog, has used the EDRM data set for its research.  Kudos to John Wang, Project Lead for the EDRM Data Set Project and Product Manager at ZL Technologies, Inc., and the rest of the Data Set team for such an extensive test set collection!

So, what do you think?  Do you use the EDRM Data Set for testing your eDiscovery processes?  Please share any comments you might have or if you’d like to know more about a particular topic.

eDiscovery Searching: Proximity, Not Absence, Makes the Heart Grow Fonder

Recently, I assisted a large corporate client where there were several searches conducted across the company’s enterprise-wide document management systems (DMS) for ESI potentially responsive to the litigation.  Some of the individual searches on these systems retrieved over 200,000 files by themselves!

DMS systems are great for what they are intended to do – provide a storage archive for documents generated within the organization, version tracking of those documents and enable individuals to locate specific documents for reference or modification (among other things).  However, few of them are developed with litigation retrieval in mind.  Sure, they have search capabilities, but it can sometimes be like using a sledgehammer to hammer a thumbtack into the wall – advanced features to increase the precision of those searches may often be lacking.

Let’s say in an oil company you’re looking for documents related to “oil rights” (such as “oil rights”, “oil drilling rights”, “oil production rights”, etc.).  You could perform phrase searches, but any variations that you didn’t think of would be missed (e.g., “rights to drill for oil”, etc.).  You could perform an AND search (i.e., “oil” AND “rights”), and that could very well retrieve all of the files related to “oil rights”, but it would also retrieve a lot of files where “oil” and “rights” appear, but have nothing to do with each other.  A search for “oil” AND “rights” in an oil company’s DMS systems may retrieve every published and copyrighted document in the systems mentioning the word “oil”.  Why?  Because almost every published and copyrighted document will have the phrase “All Rights Reserved” in the document.

That’s an example of the type of issue we were encountering with some of those searches that yielded 200,000 files with hits.  And, that’s where proximity searching comes in.  Proximity searching is simply looking for two or more words that appear close to each other in the document (e.g., “oil within 5 words of rights”) – the search will only retrieve the file if those words are as close as specified to each other, in either order.  Proximity searching helped us reduce that collection to a more manageable number for review, even though the enterprise-wide document management system didn’t have a proximity search feature.

How?  We wound up taking a two-step approach to get the collection to a more likely responsive set.  First, we did the “AND” search in the DMS system, understanding that we would retrieve a large number of files, and exported those results.  After indexing them with a first pass review tool that has more precise search alternatives (at Trial Solutions, we use FirstPass™, powered by Venio FPR™, for first pass review), we performed a second search on the set using proximity searching to limit the result set to only files where the terms were near each other.  Then, tested the results and revised where necessary to retrieve a result set that maximized both recall and precision.

The result?  We were able to reduce an initial result set of 200,000 files to just over 5,000 likely responsive files by applying the proximity search to the first result set.  And, we probably saved $50,000 to $100,000 in review costs – on a single search.

I also often use proximity searches as alternatives to phrase searches to broaden the recall of those searches to identify additional potentially responsive hits.  For example, a search for “Doug Austin” doesn’t retrieve “Austin, Doug” and a search for “Dye 127” doesn’t retrieve “Dye #127”.  One character difference is all it takes for a phrase search to miss a potentially responsive file.  With proximity searching, you can look for these terms close to each other and catch those variations.

So, what do you think?  Do you use proximity searching in your culling for review?  Please share any comments you might have or if you’d like to know more about a particular topic.

eDiscovery Trends: Sanctions Down in 2010 — at least thru December 1

Recently, this blog cited a Duke Law Journal study that indicated that eDiscovery sanctions were at an all-time high through 2009.  Then, a couple of weeks ago, I saw a story recently from Williams Mullen recapping the 2010 year in eDiscovery.  It provides a very thorough recap including 2010 trends in sanctions (identifying several cases where sanctions were at issue), advances made during the year in cooperation and proportionality, challenges associated with privacy concerns in foreign jurisdictions and trends in litigation dealing with social media.  It’s a very comprehensive summary of the year in eDiscovery.

One noteworthy finding is that, according to the report, sanctions were sought and awarded in fewer cases in 2010.  Some notable stats from the report:

  • There were 208 eDiscovery opinions in 2009 versus 209 through December 1, 2010;
  • Out of 209 cases with eDiscovery opinions in 2010, sanctions were sought in 79 of them (38%) and awarded in 49 (62% of those cases, and 23% of all eDiscovery cases).
  • Compare that with 2009 when sanctions were sought in 42% of eDiscovery cases and were awarded in 70% of the cases in which they were requested (30% of all eDiscovery cases).
  • While overall requests for sanctions decreased, motions to compel more than doubled in 2010, being filed in 43% of all e-discovery cases, compared to 20% in 2009.
  • Costs and fees were by far the most common sanction, being awarded in 60% of the cases involving sanctions.
  • However, there was a decline in each type of sanction as costs and fees (from 33 to 29 total sanctions), adverse inference (13 to 7), terminating (10 to 7), additional discovery (10 to 6) and preclusion (5 to 3) sanctions all declined.

The date of this report was December 17, and the report noted a total of 209 eDiscovery cases as of December 1, 2010.  So, final tallies for the year were not yet tabulated.  It will be interesting to see if the trend in decline of sanctions held true once the entire year is considered.

So, what do you think?  Is this a significant indication that more organizations are getting a handle on their eDiscovery obligations – or just a “blip in the radar”?  Please share any comments you might have or if you’d like to know more about a particular topic.

eDiscovery Best Practices: Database Discovery Pop Quiz ANSWERS
 

So, how did you do?  Did you know all the answers from Friday’s post – without “googling” them?  😉

Here are the answers – enjoy!

What is a “Primary Key”? The primary key of a relational table uniquely identifies each record in the table. It can be a normal attribute that you expect to be unique (e.g., Social Security Number); however, it’s usually best to be a sequential ID generated by the Database Management System (DBMS).

What is an “Inner Join” and how does it differ from an “Outer Join”?  An inner join is the most common join operation used in applications, creating a new result table by combining column values of two tables.  An outer join does not require each record in the two joined tables to have a matching record. The joined table retains each record in one of the tables – even if no other matching record exists.  Sometimes, there is a reason to keep all of the records in one table in your result, such as a list of all employees, whether or not they participate in the company’s benefits program.

What is “Normalization”?  Normalization is the process of organizing data to minimize redundancy of that data. Normalization involves organizing a database into multiple tables and defining relationships between the tables.

How does a “View” differ from a “Table”?  A view is a virtual table that consists of columns from one or more tables. Though it is similar to a table, it is a query stored as an object.

What does “BLOB” stand for?  A Binary Large OBject (BLOB) is a collection of binary data stored as a single entity in a database management system. BLOBs are typically images or other multimedia objects, though sometimes binary executable code is stored as a blob.  So, if you’re not including databases in your discovery collection process, you could also be missing documents stored as BLOBs.  BTW, if you didn’t click on the link next to the BLOB question in Friday’s blog, it takes you to the amusing trailer for the 1958 movie, The Blob, starring a young Steve McQueen (so early in his career, he was billed as “Steven McQueen”).

What is the different between a “flat file” and a “relational” database?  A flat file database is a database designed around a single table, like a spreadsheet. The flat file design puts all database information in one table, or list, with fields to represent all parameters. A flat file is prone to considerable duplicate data, as each value is repeated for each item.  A relational database, on the other hand, incorporates multiple tables with methods (such as normalization and inner and outer joins, defined above) to store data efficiently and minimize duplication.

What is a “Trigger”?  A trigger is a procedure which is automatically executed in response to certain events in a database and is typically used for keeping the integrity of the information in the database. For example, when a new record (for a new employee) is added to the employees table, a trigger might create new records in the taxes, vacations, and salaries tables.

What is “Rollback”?  A rollback is the undoing of partly completed database changes when a database transaction is determined to have failed, thus returning the database to its previous state before the transaction began.  Rollbacks help ensure database integrity by enabling the database to be restored to a clean copy after erroneous operations are performed or database server crashes occur.

What is “Referential Integrity”?  Referential integrity ensures that relationships between tables remain consistent. When one table has a foreign key to another table, referential integrity ensures that a record is not added to the table that contains the foreign key unless there is a corresponding record in the linked table. Many databases use cascading updates and cascading deletes to ensure that changes made to the linked table are reflected in the primary table.

Why is a “Cartesian Product” in SQL almost always a bad thing?  A Cartesian Product occurs in SQL when a join condition (via a WHERE clause in a SQL statement) is omitted, causing all combinations of records from two or more tables to be displayed.  For example, when you go to the Department of Motor Vehicles (DMV) to pay your vehicle registration, they use a database with an Owners and a Vehicles table joined together to determine for which vehicle(s) you need to pay taxes.  Without that join condition, you would have a Cartesian Product and every vehicle in the state would show up as registered to you – that’s a lot of taxes to pay!

If you didn’t know the answers to most of these questions, you’re not alone.  But, to effectively provide the information within a database responsive to an eDiscovery request, knowledge of databases at this level is often necessary to collect and produce the appropriate information.    As Craig Ball noted in his Law.com article Ubiquitous Databases, “Get the geeks together, and get out of their way”.  Hey, I resemble that remark!

So, what do you think?  Did you learn anything?  Please share any comments you might have or if you’d like to know more about a particular topic.

eDiscovery Best Practices: Database Discovery Pop Quiz
 

Databases: You can’t live with them, you can’t live without them.

Or so it seems in eDiscovery.  On a regular basis, I’ve seen various articles and discussions related to discovery of databases and other structured data and I remain very surprised how few legal teams understand database discovery and know how to handle it.  A colleague of mine (who I’ve known over the years to be honest and reliable) even claimed to me a few months back while working for a nationally known eDiscovery provider that their collection procedures actually excluded database files.

Last month, Law.com had an article written by Craig Ball, called Ubiquitous Databases, which provided a lot of good information about database discovery. It included various examples how databases touch our lives every day, while noting that eDiscovery is still ultra document-centric, even when those “documents” are generated from databases.  There is some really good information in that article about Database Management Software (DBMS), Structured Query Language (SQL), Entity Relationship Diagrams (ERDs) and how they are used to manage, access and understand the information contained in databases.  It’s a really good article especially for database novices who need to understand more about databases and how they “tick”.

But, maybe you already know all you need to know about databases?  Maybe you would already be ready to address eDiscovery on your databases today?

Having worked with databases for over 20 years (I stopped counting at 20), I know a few things about databases.  So, here is a brief “pop” quiz on database concepts.  Call them “Database 101” questions.  See how many you can answer!

  • What is a “Primary Key”? (hint: it is not what you start the car with)
  • What is an “Inner Join” and how does it differ from an “Outer Join”?
  • What is “Normalization”?
  • How does a “View” differ from a “Table”?
  • What does “BLOB” stand for? (hint: it’s not this)
  • What is the different between a “flat file” and a “relational” database?
  • What is a “Trigger”?
  • What is “Rollback”? (hint: it has nothing to do with Wal-Mart prices)
  • What is “Referential Integrity”?
  • Why is a “Cartesian Product” in SQL almost always a bad thing?

So, what do you think?  Are you a database guru or a database novice?  Please share any comments you might have or if you’d like to know more about a particular topic.

Did you think I was going to provide the answers at the bottom?  No cheating!!  I’ll answer the questions on Monday.  Hope you can stand it!!

eDiscovery Trends: 2011 Predictions — By The Numbers
 

Comedian Nick Bakay”>Nick Bakay always ends his Tale of the Tape skits where he compares everything from Married vs. Single to Divas vs. Hot Dogs with the phrase “It's all so simple when you break things down scientifically.”

The late December/early January time frame is always when various people in eDiscovery make their annual predictions as to what trends to expect in the coming year.  We’ll have some of our own in the next few days (hey, the longer we wait, the more likely we are to be right!).  However, before stating those predictions, I thought we would take a look at other predictions and see if we can spot some common trends among those, “googling” for 2011 eDiscovery predictions, and organized the predictions into common themes.  I found serious predictions here, here, here, here and here.  Oh, also here and here.

A couple of quick comments: 1) I had NO IDEA how many times that predictions are re-posted by other sites, so it took some work to isolate each unique set of predictions.  I even found two sets of predictions from ZL Technologies, one with twelve predictions and another with seven, so I had to pick one set and I chose the one with seven (sorry, eWEEK!). If I have failed to accurately attribute the original source for a set of predictions, please feel free to comment.  2) This is probably not an exhaustive list of predictions (I have other duties in my “day job”, so I couldn’t search forever), so I apologize if I’ve left anybody’s published predictions out.  Again, feel free to comment if you’re aware of other predictions.

Here are some of the common themes:

  • Cloud and SaaS Computing: Six out of seven “prognosticators” indicated that adoption of Software as a Service (SaaS) “cloud” solutions will continue to increase, which will become increasingly relevant in eDiscovery.  No surprise here, given last year’s IDC forecast for SaaS growth and many articles addressing the subject, including a few posts right here on this blog.
  • Collaboration/Integration: Six out of seven “augurs” also had predictions related to various themes associated with collaboration (more collaboration tools, greater legal/IT coordination, etc.) and integration (greater focus by software vendors on data exchange with other systems, etc.).  Two people specifically noted an expectation of greater eDiscovery integration within organization governance, risk management and compliance (GRC) processes.
  • In-House Discovery: Five “pundits” forecasted eDiscovery functions and software will continue to be brought in-house, especially on the “left-side of the EDRM model” (Information Management).
  • Diverse Data Sources: Three “soothsayers” presaged that sources of data will continue to be more diverse, which shouldn’t be a surprise to anyone, given the popularity of gadgets and the rise of social media.
  • Social Media: Speaking of social media, three “prophets” (yes, I’ve been consulting my thesaurus!) expect social media to continue to be a big area to be addressed for eDiscovery.
  • End to End Discovery: Three “psychics” also predicted that there will continue to be more single-source end-to-end eDiscovery offerings in the marketplace.

The “others receiving votes” category (two predicting each of these) included maturing and acceptance of automated review (including predictive coding), early case assessment moving toward the Information Management stage, consolidation within the eDiscovery industry, more focus on proportionality, maturing of global eDiscovery and predictive/disruptive pricing.

Predictive/disruptive pricing (via Kriss Wilson of Superior Document Services and Charles Skamser of eDiscovery Solutions Group respective blogs) is a particularly intriguing prediction to me because data volumes are continuing to grow at an astronomical rate, so greater volumes lead to greater costs.  Creativity will be key in how companies deal with the larger volumes effectively, and pressures will become greater for providers (even, dare I say, review attorneys) to price their services more creatively.

Another interesting prediction (via ZL Technologies) is that “Discovery of Databases and other Structured Data will Increase”, which is something I’ve expected to see for some time.  I hope this is finally the year for that.

Finally, I said that I found serious predictions and analyzed them; however, there are a couple of not-so-serious sets of predictions here and here.  My favorite prediction is from The Posse List, as follows: “LegalTech…renames itself “EDiscoveryTech” after Law.com survey reveals that of the 422 vendors present, 419 do e-discovery, and the other 3 are Hyundai HotWheels, Speedway Racers and Convert-A-Van who thought they were at the Javits Auto Show.”

So, what do you think?  Care to offer your own “hunches” from your crystal ball?  Please share any comments you might have or if you’d like to know more about a particular topic.

State eDiscovery Rules: Wisconsin Adopts Amendments to Rules for eDiscovery
 

On November 1 of last year, we noted on this blog that Oklahoma had become the latest state to adopt amendments to their Rules of Civil Procedure, leaving only 14 states (including DC) to not have enacted any rules changes that address discovery of ESI as of January 1st of this year.

That’s because on January 1, Wisconsin became the latest state to adopt eDiscovery amendments to their Rules of Civil Procedure.  The amendments affect the following Wisconsin Statutes:

  • §§ 802.10(3)(jm) – Scheduling Order: The scheduling order may address the need for discovery of ESI, which focuses early attention on eDiscovery issues.
  • §§ 804.01(4m) – Discovery Conference: The parties must confer regarding discovery of ESI unless excused by the court (required meet and confer).  The required issues to be discussed include the scope of electronic discovery, the preservation of ESI, the format of production, and the costs of proposed discovery (including the extent to which such costs shall be limited).
  • §§ 804.08(3) – Business Records: Parties have the option to produce or allow access to business records in response to an interrogatory.
  • §§ 804.09(1) and (2) – Format of Production: Requesting party may specify “form” of production of ESI and, if no form is requested, information must be produced in the form in which it is ordinarily maintained or in a “reasonably usable form”.
  • §§ 804.12(4m) – Safe Harbor: Contains a safe harbor provision to protect a party who destroys information in good faith according to a routine records retention policy.
  • §§ 805.07(2) – Subpoena: Protect parties from the unreasonable burden of responding to subpoenas asking for ESI by enabling the producing party to produce information in the form in which it is ordinarily maintained or in a “reasonably usable form” and also by permitting testing or sampling of the information instead of inspection of copying.

The required meet and confer provision – §§ 804.01(4m) – was adopted, despite the opinion of the Judicial Council Evidence and Civil Procedure Committee that Wisconsin did not need a mandatory meet and confer rule.  The strong dissent expressed the concern that the requirement “has the potential to diminish both fairness and efficiency along with the potential of increasing the time and expense of litigation” and noted that, unlike the federal courts, Wisconsin state courts “do not have many cases involving a large number of documents and electronic discovery disputes” and that such a rule would “impose ‘significant added burden on litigants while yielding little benefit.'”  It concluded with a call to “judges, lawyers, and litigants from around the state to monitor this new mandate, and if it is not working, [to] petition the court for change.”

So, what do you think?  Wondering where your state stands?  Please share any comments you might have or if you’d like to know more about a particular topic.

eDiscovery Case Law: Crispin v. Christian Audigier Inc.

Yesterday, we took a look at “Major Tours, Inc. v. Colorel”, which addresses whether a party may obtain a Protective Order relieving it of the duty to access backup tapes, even when that party’s failure to issue a litigation hold resulted in the data only being available on those backup tapes.

Discoverability of social media content has been a big topic this year, with several cases addressing the issue, including this one, previously discussed on eDiscovery Daily.  The holiday week look back at cases concludes with Crispin v. Christian Audigier Inc., 2010 U.S. Dist. Lexis 52832 (C.D. Calif. May 26, 2010), which addresses whether ‘private’ data on social networks is discoverable.

This copyright infringement claim brought by artist Buckley Crispin against defendant and designer Christian Audigier, alleges that Audigier used artwork outside the scope of the original oral license between the parties and also sub-licensed the artwork to other companies and individuals (named as co-defendants) without Crispin’s consent.  The defendants served subpoenas on social media providers Facebook, MySpace, and Media Temple, directing them to turn over all communications between Crispin and Audigier, as well as any communications referencing the co-defendants.

Crispin sought to quash the subpoenas, arguing that they sought private electronic communications protected under the Stored Communications Act of 1986 (SCA), prohibiting Electronic Communication Services (ECS) and Remote Computing Services (RCS) providers from turning over those communications, but the motion was denied because Magistrate Judge John E. McDermott determined that Facebook, MySpace, and Media Temple did not qualify for protection from disclosure under the SCA.  Crispin moved for reconsideration with the U.S. District Court for the Central District of California.

District Court Judge Margaret Morrow’s decision partially reversed and partially vacated Judge McDermott’s order, finding that the SCA’s protections (and associated discovery preclusions) include at least some of the content hosted on social networking sites, including the private messaging features of social networking sites protected as private email.  She also concluded that because Facebook, MySpace, and Media Temple all provide private messaging or email services as well as electronic storage, they all qualify as both ECS and RCS providers, with appropriate SCA protections.

However, regarding Facebook wall postings and MySpace comments, Judge Morrow determined that there was insufficient evidence to determine whether these wall postings and comments constitute private communications as the user’s privacy settings for them were less clear and ordered a new evidentiary hearing regarding the portions of the subpoenas that sought those communications.

This opinion sets a precedent that, in future cases, courts may allow protection to social networking and web hosting providers from discovery based on SCA protections as ECS and RCS providers and may consider social media ESI protected, based on the provider’s privacy controls and the individual user’s privacy settings.

So, what do you think?  Is this the most significant eDiscovery case of 2010?  Please share any comments you might have or if you’d like to know more about a particular topic.

Happy New Year from all of us at Trial Solutions and eDiscovery Daily!