Erin Derby, Certified eDiscovery Specialist (CEDS), and a member of the Lexbe technical services team was recently published in Paralegal Today. Her article, Finding the Needle in a Data Haystack, featured Erin’s expertise on advanced search methodology and offers techniques on culling data, constructing quality search queries, uncovering personally identifiable information (PII) and provides instruction on how to keep records of search processes.
Erin has presented 2 webinars for Lexbe Best Practices: eDiscovery Search and Best Practices to Avoid Missing Key Evidence in Large Doc Review (Uber Index).
You can read Erin’s article here.
How your eDiscovery platform parses and organizes your electronically stored evidence can be the difference between finding or missing that smoking gun. Or worse, unwittingly handing a smoking gun to opposing counsel. Pulling back the curtain on how an eDiscovery platform ingests electronically stored documents and makes the text within documents searchable reveals hidden places where evidence may be hiding. This article explains indexing and breaks down the types of search indexes used in eDiscovery software platforms, discusses the pros and cons of each, and offers solutions to ensure that you never miss crucial evidence.
Indexing occurs during the upload of your documents to your eDiscovery review platform. A number of processes run which separates and organizes your data. The text, in particular, is extracted from your documents and filtered into a database or index. When you enter a search query your software does not review each document searching for the word; that could take hours or days. Rather your software refers to the index (just as you would in a textbook) in order to quickly pull the relevant documents for your review. The process by which the text is extracted from your documents to be placed into that index is critical to the quality of search results.
There are 2 basic indexes used in eDiscovery software platforms, an OCR Index or a Text-based (also called Native extraction) Index.
OCR stands for Optical Character Recognition. In this process, your electronically stored documents could be originally scanned or saved from a native document through a virtual print driver. Specialty OCR software recognizes alpha-numeric text patterns. For example, a Word doc uploaded would be “printed” within the software engine and the text that appears on that virtual print would be lifted off the page and indexed.
Text-based Indexing is also called Native Extraction Indexing because instead of processing the document as a printed page it rather looks at all of the underlying code and data within a document. Where OCR sees the document as a print, Text-based indexing lifts the hood and extracts all of the computer-embedded text in a file and additionally will capture the data that you do not see, such as comments.
The pros of one indexing approach are the cons of the other and vice versa. Specifically, an OCR-based index may miss hidden fields, such as hidden columns on an Excel spreadsheet, while a text-based index would not. Conversely, a Native extraction-based index will not read (index) the text on an image, including scanned or PDF’d documents, where an OCR index will.
This is an example of a native PowerPoint document. When you receive this doc as a .ppt file an OCR-based index would create a virtual print of each slide and lift any text that appears on that print for indexing. The embedded images with text, like this chart titled “Load Growth Model”, would have all text that appears on the chart indexed. Speaker notes, however, like this one regarding “November Data”, could be missed as notes do not normally show on a print, by default.
Conversely, a native extraction-based index would only recognize the .jpg title of the image of the chart and index that file name as text. It cannot “read” an image (as OCR can) and so none of the text appearing on the chart would be indexed. It would, however, pick up the speaker notes regarding November Data. When you search for the company name “CAISO” an OCR-based Index would retrieve this document but a Native Extraction-based index would not. When you search for “November Data” the Native Index would retrieve this document, but an OCR index would miss it. If you were to perform a Boolean search for “CAISO AND November Data” neither index alone would return this document as responsive as it would only see one term or the other.
Some modern eDiscovery software providers will offer both indexes, however, they are siloed and so you would have to run your entire search twice, once through each index. This not only doubles your search time but still leaves you vulnerable to miss evidence when you are using Boolean searches to narrow results. Some eDiscovery vendors will instruct you to write additional language into your ESI order in an attempt to mitigate the loss of potential evidence. Unfortunately, the more complex an ESI request the more likely that mistakes will be made and evidence missed.
Lexbe has solved this false ‘index dilemma’ by creating the first concatenated eDiscovery search index, our Uber-Index℠. At ingestion, documents are run through both OCR and Native extraction indexing simultaneously. Then the OCR and Native-Extracted indices are compiled into one single, searchable database. All text is captured by these two complementary processes, and all evidence is searchable.
Additionally, Lexbe offers an integrated translation feature which is also included in our Uber Index for seamless search in either language. Whether you opt for Lexbe to perform your document translation or upload your own translated docs, our software will tie the original doc to the English translated one for integrated search and document review.
Finally, Lexbe also performs an advanced metadata extraction at ingestion for precision searches. Details such as the author of a document are extracted and will be searchable.
|Features||OCR Index||Text-Based Index||Lexbe Uber Index|
With the Lexbe eDiscovery platform, your search is faster and more complete than with any other index on the market. For more information on how indexing works watch our webinar Best Practices to Avoid Missing Evidence in Large Document Reviews, part of the Lexbe eDiscovery Webinar Series.
File sharing services, such as DropBox, have become increasingly used as eDiscovery repositories for incoming data and outgoing productions. With easy sharing, via a simple URL link, it’s understandable why these tools appear to offer an optimal solution for sending and receiving massive amounts of data as one does with eDiscovery litigation. Unfortunately, this “solution” can become a massive liability and we caution clients against using these services because it is simply too easy to accidentally share privileged documents. In fact, there are several cases in which information has been inadvertently shared and the results were disastrous for the offending party.
It is not that it can’t be done correctly, it is more that one is asking for problems with an open platform like this. With default settings in place, the “owner” of a file relinquishes control of the data within the file when shared with other users. Once shared, the data within the file can be copied, changed and shared without the owner’s permission. New users can be added to the file to view the data and, with seemingly unlimited “cooks in the kitchen,” it is too difficult to maintain chain of custody and ensure responsible sharing. A few specific issues with file sharing services include:
In Harleysville Ins. Co v. Holding Funeral Home, Inc., Case No. 1:15cv00057 (W. D. Va. February 9, 2017), an insurance company refused a funeral home’s fire damage claim after determining the fire was caused by arson. An investigator for the insurance company uploaded video taken at the scene to a platform sharing site, box.com. The investigator sent the link to the insurance company attorney who then shared it with the funeral home attorney in order to substantiate their arson claim. Later, however, the insurance investigator uploaded additional files to that same folder, which the funeral home attorneys still had access to. The court found that because the link and files within were not properly password protected the insurance company had, in essence, “left the files on the park bench” in a virtual sense and thus waived privilege.
Whether a company chooses to use a new technology is a decision within that company’s control. If it chooses to use a new technology, however, it should be responsible for ensuring that its employees and agents understand how the technology works, and, more importantly, whether the technology allows unwanted access by others to its confidential information.
We have developed the Lexbe eDiscovery Platform to include a number of checks against inadvertent disclosure of privileged docs. We create a secure encrypted link specific to each production that can then be safely shared. By insulating exports with secure production links, we help prevent user error that could result in sharing documents not meant for opposing counsel or outside parties.
Lexbe was recently featured in the leading legal blog: ‘Above the Law’ in a post entitled: Today’s Tech: A Litigation Attorney Uses Technology To Level The Playing Field.
A practicing litigator was interviewed and noted that technology in general, and cloud computing in particular, helps a small law firm to stay competitive in today’s constantly changing legal landscape. “Technology is the great equalizer between solo and small law firms and large firms. For smaller law firms it puts you on a level field with law firms many times your size. I can now handle 2 or 3 complex construction litigation cases at one time and it doesn’t take over my practice. I can get through 30,000 documents quickly and narrow them down to what I really need to look at.”
Above the Law noted that Lexbe helps small firms handle the big cases. The interviewed attorney noted that “I handle a lot of cases where upwards of 30,000 docs are produced. These documents used to fill the room. Now I buy access to Lexbe on a case-by-case basis and then search the documents using Boolean logic.”
Lexbe speeds up review and allows for attorney, case and time leverage. Above the Law continues: “So a process that used to require six associates days to read through the documents can now be accomplished in minutes. Because of the Lexbe software, the entire playing field has been leveled for my firm.”
Read the entire post at Above the Law.