Information Governance (InfoGovernance) is the specification of decision rights and an accountability framework to encourage desirable behavior in the valuation, creation, storage, use, archiving and deletion of information. It includes the processes, roles, standards and metrics that ensure the effective and efficient use of information to enable an organization to achieve its goals. Information governance should be an element in planning an enterprise's information architecture.

(Gartner Hype Cycle for Legal and Regulatory Information Governance, 2009, December 2009).

An Engagement Area (EA) is an area where the commander of a military force intends to contain and destroy an enemy force with the massed effects of all available weapons systems.

(FM 1-02, Operational Terms and Graphics, September 2004).

Wednesday, April 1, 2015

Consolidation of Blogs: New Location of Content on ComplexDiscovery.com

Effective April 1, 2015, the Information Governance Engagement Area blog will no longer be updated on a regular basis.  New content ranging from news and events to opinions and assertions will now be available exclusively on the ComplexDiscovery blog at ComplexDiscovery.com.


This change is simply to streamline the publishing process of regular content and reflects no change in the commitment to provide interesting and insightful updates to those with interest in the growing field of information governance.

Thanks for your consideration and please take the time to visit and benefit from the ComplexDiscovery blog and supporting social media conduits.




Tuesday, March 31, 2015

How to Detect, Define, & Use an Enterprise Document Attribute Matrix

By John Martin

Documents in file shares, content management systems, and scanned archives are often described as “unstructured.” However, there is typically a high level of structure in and interconnectedness among those documents. This structure and interconnectedness occurs because specific document types contain recurring attributes or data elements and those attributes or data elements are shared with other document types.
The relationships can be represented in a matrix with document types shown on the top of the matrix and document attributes or data elements down the left side. In the simplest form, check marks can be used to represent which data elements are typically found in any given document type. In a large enterprise there may be hundreds of document types. 

Monday, March 30, 2015

Using Continuous Active Learning to Solve the ‘Transparency’ Issue in TAR

By John Tredennick
Technology assisted review has a transparency problem. Notwithstanding TAR’s proven savings in both time and review costs, many attorneys hesitate to use it because courts require “transparency” in the TAR process.
Specifically, when courts approve requests to use TAR, they often set the condition that counsel disclose the TAR process they used and which documents they used for training. In some cases, the courts have gone so far as to allow opposing counsel to kibitz during the training process itself.
Attorneys fear that this kind of transparency will force them to reveal work product, thoughts about problem documents, or even case strategy. Although most attorneys accept the requirement to share keyword searches as a condition of using them, disclosing their TAR training documents in conjunction with a production seems a step too far.

Friday, March 27, 2015

Study Shows People Act To Protect Privacy When Told How Often Phone Apps Share Personal Information

By Byron Spice
Message That Grabs Attention: “Your Location Has Been Shared 5,398 Times”
Many smartphone users know that free apps sometimes share private information with third parties, but few, if any, are aware of how frequently this occurs. An experiment at Carnegie Mellon University shows that when people learn exactly how many times these apps share that information they rapidly act to limit further sharing.
In one phase of a study that evaluated the benefits of app permission managers – software that gives people control over what sensitive information their apps can access – 23 smartphone users received a daily message, or “privacy nudge,” telling them how many times information such as location, contact lists or phone call logs had been shared.

Thursday, March 26, 2015

Too Many Notes: In re: Lithium Ion Batteries Antitrust Litigation

By Craig Ball
The core challenge of discovery is identifying information that is responsive but not privileged, achieved without undue burden or expense.  There are multiple ways to approach the task, none optimal. The most labor-intensive method is called “linear human review,” where lawyers (for the most part) look at everything and cull responsive and privileged items.  It sufficed in the pre-digital era when much effort and resources were devoted to recordkeeping.  Despite being costly, slow and error prone, linear review was all we had, so became the gold standard for identifying responsive and privileged information.

Wednesday, March 25, 2015

Frivolous Law Suits? 26+ Reasons to Laugh at eDiscovery (Cartoon and Clip)

The Cartoon and Clip of the Week for March 25, 2015

Regularly we read, see and hear incredibly serious presentations and pontifications related to the theory, practice and business of electronic discovery.  This week our cartoon and clip features a quick look at Rule 26(f) conference planning for a frivolous lawsuit (cartoon) and a quick reference link to a very serious retrospective listing of 26 eDiscovery-related cartoons (clip).


FrivoulousLawSuits590




The Humor of eDiscovery: 26 Cartoons and Clips

Click here for a short retrospective of 26 recent eDiscovery-related cartoons and clips published on the ComplexDiscovery Blog.



Monday, March 23, 2015

Do smart machines require ethical programming?

From Help Net Security
Realizing the potential of smart machines — and ensuring successful outcomes for the businesses that rely on them — will hinge on how trusted smart machines are and how well they maintain that trust. Central to establishing this trust will be ethical values that people recognize and are comfortable with. “Clearly, people must trust smart machines if they are to accept and use them,” said Frank Buytendijk, research vice president and distinguished analyst at Gartner. “The ability to earn trust must be part of any plan to implement artificial intelligence (AI) or smart machines, and will be an important selling point when marketing this technology. CIOs must be able to monitor smart machine technology for unintended consequences of public use and respond immediately, embracing unforeseen positive outcomes and countering undesirable ones.”