Saturday, April 14, 2012

eDiscovery - Lower in the Stack pt.IV - Wrap

The question put forth in this project, where I built a small eDiscovery processing environment, gathered test data and ran it through Concordance and FreeEed, was 'How do we balance cost, effectiveness and reliability in handling this data?'

I don't think there is a definitive answer to that question; I think it is at the front of the minds of anyone whose job it is to manage data -- for business management and intelligence, regulatory compliance, litigation, research or hobby -- and I think we saw some of why it can present a moving target. And this was without even using buzzwords like 'cloud', standards like 'de-duplication', or anachronisms like 'paper' -- all valid and important considerations to many who face these challenges professionally.

The industry-standard Electronic Discovery Reference Model shows the breadth and depth of these issues -- and why I provided the caveat that I'd be looking at Small-to-Medium-Data, where manual intervention is possible. Plenty are the defendants who still scan paper redacted documents to PDF and present them on CD-Rs.

EDRM Graphic

It should not be forgotten that it was just six years ago that the FRCP were amended to speak to the growth of electronically stored information, and still, it is said that for eDiscovery, judges normally care more about results than methodology. And by the same token, most any eDiscovery tool -- in the proper hands -- can be employed successfully.

As an eDiscovery sys admin with a background in social scientific research, I quickly recognized the intersection of these two paths. In their own way, both seek to collect, process and organize data about human action, and from it divine patterns and present them. So I started this blog with that in mind; I used eDiscovery tools for collection and processing, and communication science tools for analysis. I asked questions that I thought were of interest in both fields. And as it turned out, I was in good company. It was an excellent union. All that was missing was system administration, so by going 'lower in the stack' I closed the loop completely.

The "CapitalToomey Data Center" has undergone some changes since this project's outset. They will be outlined in future posts, but at least now I've got control of more components of the eDiscovery and Social Science research frameworks. I will keep on the lookout for interesting topics to post in this general area. I welcome your input, and thank you for reading.

Finally, if you are interested in sharing your results with the test data from this experiment, I would very much like to hear about it - in comments here or via Twitter.

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