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Facebook Download Your Information Function Omits Significant Amounts of Evidence

By John Patzakis and Brent Botta

Facebook provides a “Download Your Information” (“DYI”) function to allow users to download to their computer data they have posted to their own accounts. The output is in the form of a compressed ZIP file.  But is DYI useful or defensible for eDiscovery?

In making that assessment it is important to understand that the following key information is not included in Facebook’s DYI:

  1. The only content that is collected using DYI is what the user posts or comments. Comments to user’s post, as well as posts and comments the user responds to are excluded. As such, the collected portion of the conversation is one-sided with no context available to understand the conversation.
  2. The one-sided posts and comments that are collected are not structured by conversation – they are arranged by date of each individual post or comment. As such, DYI intermingles posts and comments from different conversations, thereby stripping out the context to each actual conversation.
  3. Facebook DYI omits Most Metadata Fields. Facebook contains over 20 unique metadata fields, all of which can be very important as substantive evidence or as information that helps establish an evidentiary foundation, which is particularly important for social media evidence. 

In contrast, X1 Social Discovery (“X1SD”), the leading software used by several hundred law firms, government regulatory agencies and litigation support consultants world-wide for the preservation, analysis and authentication of social media and other internet-based evidence. X1SD aggregates comprehensive social media content and web-based data into a single user interface, while preserving critical metadata, all inline comments, and other user interactions not possible through image capture “screenshot,” simple computer screen printouts or the Facebook Download Your Information (“DYI”) functionality.

One of the many benefits of X1SD is the comprehensive nature in which it collects and displays Facebook ESI. With X1SD, you can collect, preserve and review what a custodian posted, received and responded to. You can also see all the comments from other users in response to a post made by a custodian. Another of the key advantages of X1SD is its ability to preserve the parent child relationship within comments and posts which maintains the critical context and meaning to the content. This preservation is kept intact through the export process. This is opposed to the DYI method that breaks apart comments and posts and lists the Facebook ESI in a manner that prohibits the ability to associate the comments and posts with one another.

For instance, below is a screenshot of a DYI export of a comment to a post by the user illustrating its very limited context and exclusion of all other comments made by others in the conversation and other key information, such as metadata. The DYI export does not even provide the original post to which the user’s comment is made.

In contrast to Facebook DYI, an X1SD collection will include the entire conversation, associated images, and metadata associated with the post. A hash value of each item is generated at the time of collection to better facilitate evidentiary authentication.  Furthermore, the output can be delivered in a load file that is of the exact same format as the timeline collections to ensure ease of uploading for the downstream review platforms. Below is a screenshot of an X1SD export with the same comment but with a much fuller context, including the actual original post being commented on, the full conversation thread, and other important additional potential evidence:

The Sedona Conference noted these limitations with Facebook DYI, including its omission of key metadata and other evidence in its recent publication  The Sedona Conference, Primer on Social Media, Second Edition, 20 Sedona Conf. J. 1 (2019)(at pp 47-48). In the same section, the Sedona Conference recommends X1 Social Discovery, stating: “One of the popular social media discovery collection tools is X1 Social Discovery, which has API collection tools for Facebook, Twitter, YouTube, Instagram, and Tumblr, along with the capability to collect webpages and email from other providers.” (at pg. 49).

To test this for yourself, you can request a free trial of X1 Social Discovery here.

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Microsoft Breaks Search For Office 365

By John Patzakis

Last weeks’ guest blog post by Office 365 expert and independent consultant Bruce Berls clearly outlined why Windows search effectively does not work for business productivity search. Berls, from his testing, noted “I can’t find any OneDrive files when I do a search in Windows” and that any search results were “wildly inconsistent.”

Berls points out that “Microsoft has a vision of grand unified searches that return results from your own files and email, plus results from a wide variety of other places – the web, company documents, other people’s calendars, the contents of books you intend to read but haven’t gotten to yet, your senior thesis…Basically when you do a search, Microsoft will check the entire output of Western civilization and use smart AI to show you search results that are exactly what you want, whether you want them or not.”

And therein lies the problem.

In addition to being very buggy and slow, Microsoft has misapplied big data analytics to try and address business productivity search. That is a major mistake. Big data AI tools can deliver some useful business intelligence to those who are managing structured processes, and every major company has deployed some kind of AI process. But every company still has the problem of business workers not being able to find their information for productivity purposes. That is because the human brain is the most powerful analytical engine for business productivity search, and most search solutions do not effectively leverage this power. Windows O365 utilizes algorithms that try to predict things like document taxonomy classifications.  That can be useful for specific use cases, but not to enable business productively search, because AI-based search results are largely a cacophony of mostly unwanted information and “insights” that only frustrates the user.

When a knowledge professional performs a business productivity search, they generally have an idea of what they are looking for. They may be searching for a sales proposal from two years ago, a PowerPoint discussing GDPR compliance, or an email sent to the CFO last month with a proposed budget in a spreadsheet attachment.  For these very common, in fact hourly, use cases, a search solution with a user-friendly interface that allows humans to use their institutional business memory recall to iteratively search and filter through their information assets is needed. Business productivity search is not big data analytics and it is not web retrieval. It is its own use case with a workflow and interface that is tailored to the end users.

X1 Search provides the end-user with a powerful yet user-friendly and iterative means to quickly retrieve their business documents and emails using their own memory recall as opposed to generic algorithms that generate false positives and a workflow ill-suited to business productivity search. This analysis is crystalized in the accompanying chart differentiating X1’s approach to business productivity search versus big data analytics and web search.

These points are further mentioned in this testimonial from recent Nobel Prize Winner in Chemistry and Stanford professor Dr. Michael Levitt, who states: “X1 is an intimate part of my workflow — it is essentially an extension of my mind when I engage in information retrieval, which is many times an hour during my workday.” In my opinion, you will not find that level of enthusiasm by end-users for other enterprise search platforms.

Given these requirements, X1 emerges as the best choice for a business productivity search solution. The X1 Search interface is award-winning and beloved by users (try finding users that love traditional enterprise search). Business professionals can search emails, files, OneDrive SharePoint, and the other content, whether local or in Office 365, that they need to do their jobs in a single-pane-of-glass interface that enables post-search actions. Directly in the UI, users can respond to emails, for example, or forward OneDrive documents. With this kind of user interface, business workers can use their business memory recall and intuition to quickly find information. They can instantaneously filter and preview directly in the UI, providing an iterative search process, making it possible to find that critical document in a matter of seconds. And you can try X1 Search via a free trial.

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Windows Can’t Find My OneDrive Files

By Bruce Berls
(originally published August 20, 2020)

Editor’s note: Today we are featuring a guest blog post from Bruce Berls, an independent IT Consultant and Office 365 expert. He is the CEO of Bruceb Consulting. www.bruceb.com

Windows Search has a problem with my OneDrive files. It can’t find them. I’ve gone back to using X1 Search, which indexes and searches everything, including OneDrive files, with grace and dignity.

Microsoft doesn’t think it’s enough to just search your files. Microsoft has a vision of grand unified searches that return results from your own files and email, plus results from a wide variety of other places – the web, company documents, other people’s calendars, the contents of books you intend to read but haven’t gotten to yet, your senior thesis, decoded World War II messages, maybe more. Basically when you do a search, Microsoft will check the entire output of Western civilization and use smart AI to show you search results that are exactly what you want, whether you want them or not.

There have been lots of steps backwards in Windows Search in 2020. The search window that comes up from the taskbar is cluttered and hard to use. The search bar in Outlook has been moved to a less convenient place and produces a freakishly huge box with too many options. Searches are no longer done as you type. There are bugs a-plenty.

Microsoft has never acknowledged it – which is strange – but it appears that Microsoft’s quest for bigger and better searches caused it to completely rewrite Windows Search for Windows 10 version 1909, released in November 2019. An important change: Microsoft announced that Windows Search would integrate search results from OneDrive right in File Explorer.

It’s not going well. I can’t find any OneDrive files when I do a search in Windows.

I’ve done searches starting in different places in File Explorer – starting in Quick Access, starting in the root OneDrive for Business folder, starting in OneDrive subfolders. I’ve done searches for file names and for words known to be in the text of Office documents. The search results are wildly inconsistent.

If I’m missing something, I’d really like to find out what it is. But if this is just broken, it’s inexcusable. Businesses large and small should be howling for a functional OneDrive search capability. Have we become so used to Windows failures that everyone just shrugs and accepts them?

If you’re serious about search, look at X1 Search. X1 Search indexes files on your computer, files on the network, and everything in Outlook, and does lightning-fast searches for words in them. Two years ago I wrote an article explaining why you might want to spend $96.00 on X1 Search because of its many advantages over Windows Search – lightning-fast searches, unified search across all sources, easy ways to filter search results, file viewers to preview search results, flexible ways to work with items once they’re found, and more.

Today there’s another reason, and it’s the best one yet. X1 Search connects to OneDrive and does the same instantaneous full-text searches on files stored online. As near as I can tell, X1 Search obtains a full-text index from OneDrive when it’s first connected and stores it locally on your hard drive. I can use X1 Search to locate files when I’m offline. When you’re online, X1 Search gets file previews on the fly when you highlight a search result.

That’s exactly what Microsoft promised but failed to deliver in Windows Search.

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Filed under Best Practices, Desktop Search, OneDrive, productivity, Uncategorized, X1 Search 8

Intelligent ESI Collection Integrated with Relativity Can Cut eDiscovery Costs by 90 Percent

By John Patzakis

One of the biggest drivers of excessive eDiscovery costs is ESI over-collection. This in turn leads to a larger amount of data entering the processing and initial review funnel. These traditional inefficient efforts are manual with numerous hand offs and a high degree of project management and consulting hours to oversee the disjointed workflow. A recent analysis by Compliance CEO Marc Zamsky, illustrated in the chart below, established that cost for collection, processing and first month hosting under a traditional preservation process can cost upwards of $12,000 per custodian:

Properly targeted preservation initiatives are permitted by the courts and can be enabled by next generation software that is able to quickly and effectively access and search these data sources in place and throughout the enterprise. The value of targeted preservation is recognized in the Committee Notes to the recent FRCP amendments, which urge the parties to reach agreement on the preservation of data and the key words, date ranges and other metadata to identify responsive materials. (Citing the Manual for Complex Litigation (MCL) (4th) §40.25(2)). And In re Genetically Modified Rice Litigation, the court noted that “[p]reservation efforts can become unduly burdensome and unreasonably costly unless those efforts are targeted to those documents reasonably likely to be relevant or lead to the discovery of relevant evidence.”

Recently we hosted a webinar with Compliance highlighting the very compelling integration of our X1 Distributed Discovery platform with Relativity. This X1/Relativity integration enables game-changing efficiencies in the eDiscovery process by accelerating speed to review, and providing an end-to-end process from identification through production. As recently stated by Relativity Chief Product Officer Chris Brown: “Our exciting new partnership with X1 highlights our continued commitment to providing a streamlined user experience from collection to production…RelativityOne users will be able to combine X1’s innovative endpoint technology with the performance of our SaaS platform, eliminating the cumbersome process of manual data hand-offs and allowing them to get to the pertinent data in their case – faster.”

The live demonstration highlighted in real time how the integration improves the enterprise eDiscovery collection and ECA process by enabling a targeted and efficient search and collection process, with immediate pre-collection visibility into custodian data. X1 Distributed Discovery significantly streamlines the eDiscovery workflow with integrated culling and deduplication, thereby eliminating the need for expensive and cumbersome electronically stored information (ESI) processing tools. That way, the ESI can be populated straight into Relativity from an X1 collection without multiple hand offs, extensive project management and inefficient data processing.

Zamsky commented that the “ability to collect directly from custodian laptops and desktops into a RelativityOne workspace without impacting custodians is a game-changer,” which will “reduce collection times from weeks to hours so that attorneys can quickly begin reviewing and analyzing ESI in RelativityOne.” In fact, Zamsky demonstrated just that by presenting a second chart showing how this streamlined approach, based upon a detailed ROI analysis, reduces eDiscovery costs by over 90 percent:

So in terms of the big picture, with this integration providing a complete platform for efficient data search, eDiscovery, and review across the enterprise, organizations will save a lot of time, save a lot of money, and be able to make faster and better decisions. When you accelerate the speed to review and eliminate over-collection and inefficient processing, you are going to have much better early insight into your data and increase efficiencies on many levels.

A recording of the X1/Relativity integration webinar can be accessed here.

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Federal Judge: Custodian Self-Collection of ESI is Unethical and Violates Federal Rules of Civil Procedure

By John Patzakis

In E.E.O.C. v. M1 5100 Corp., (S.D. Fla. July 2, 2020), Federal District Judge Matthewman excoriated defense counsel for allowing the practice of unsupervised custodian ESI self-collection, declaring that the practice “greatly troubles and concerns the court.” In this EEOC age discrimination case, two employees of the defendant corporation were permitted to identify and collect their own ESI in an unsupervised manner. Despite no knowledge of the process the client undertook to gather information (which resulted in only 22 pages of documents produced), counsel signed the responses to the RFP’s in violation of FRCP Rule 26(g), which requires that the attorney have knowledge and supervision of the process utilized to collect data from their client in response to discovery requirements.Gavel and books

This notable quote from the opinion provides a very strong legal statement against the practice of ESI custodian self-collection:

“The relevant rules and case law establish that an attorney has a duty and obligation to have knowledge of, supervise, or counsel the client’s discovery search, collection, and production. It is clear to the Court that an attorney cannot abandon his professional and ethical duties imposed by the applicable rules and case law and permit an interested party or person to ‘self-collect’ discovery without any attorney advice, supervision, or knowledge of the process utilized. There is simply no responsible way that an attorney can effectively make the representations required under Rule 26(g)(1) and yet have no involvement in, or close knowledge of, the party’s search, collection and production of discovery…Abdicating completely the discovery search, collection and production to a layperson or interested client without the client’s attorney having sufficient knowledge of the process, or without the attorney providing necessary advice and assistance, does not meet an attorney’s obligation under our discovery rules and case law. Such conduct is improper and contrary to the Federal Rules of Civil Procedure.”

In his ruling, Judge Matthewman stated that he “will not permit an inadequate discovery search, collection and production of discovery, especially ESI, by any party in this case.” He gave the defendant “one last chance to comply with its discovery search, collection and production obligations.”  He then also ordered “the parties to further confer on or before July 9, 2020, to try to agree on relevant ESI sources, custodians, and search terms, as well as on a proposed ESI protocol.” The Court reserved ruling on monetary and evidentiary sanctions pending the results of Defendants second chance efforts.

A Defensible Yet Streamlined Process Is Optimal

EEOC v. M1 5100, is yet another court decision disallowing custodian self-collection of ESI and underscoring the importance of a well-designed and defensible eDiscovery collection process. At the other end of the spectrum, full disk image collection is another preservation option that, while being defensible, is very costly, burdensome and disruptive to operations. Previously in this blog, I discussed at length the numerous challenges associated with full disk imaging.

The ideal solution is a systemized, uniform and defensible process for ESI collection, which also enables targeted and intelligent data collection in support of proportionality principles. Such a capability is only attainable with the right enterprise technology. With X1 Distributed Discovery (X1DD), parties can perform targeted search and collection of the ESI of hundreds of endpoints over the internal network without disrupting operations. The search results are returned in minutes, not weeks, and thus can be highly granular and iterative, based upon multiple keywords, date ranges, file types, or other parameters. This approach typically reduces the eDiscovery collection and processing costs by at least one order of magnitude (90%), thereby bringing much needed feasibility to enterprise-wide eDiscovery collection that can save organizations millions while improving compliance by maintaining metadata, generating audit logs and establishing chain of custody.

And in line with the Judge’s guidance outlined in EEOC v. M1 5100, X1DD provides a repeatable, verifiable and documented process for the requisite defensibility. For a demonstration or briefing on X1 Distributed Discovery, please contact us.

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