Presentation on theme: "Big Data, Big Records NOVA ARMA NCC-AIIM"— Presentation transcript:
1 Big Data, Big Records NOVA ARMA NCC-AIIM US. Department of the InteriorOffice of the Chief Information OfficerJohn MontelPolicy Planning and ManagementFebruary 27, 2013Carrie MallenIQ Business GroupeDiscovery Practice
2 Department of the Interior Cabinet level agency14 Bureau OfficesEmploy’s ~70,000 / 280,000 volunteersManages $16.8B operating budgetManages 500 million acres of surface landManages 479 dams and 348 reservoirsSupplies 30% of the nation's energy productionProduce 55,000 different maps each yearProtects ~500 million recreational and cultural visitorsIT TransformationGoal: 500 Million by 2020Goal: IT ConsolidationGoal: Information ManagementGoal: Infrastructure Reduction47 Lines of business5 Strategic mission areasMange one 5th the all US land2,400 office locations90 Million visitors$18.2 Billion in revenue collected from energy, mineral, grazing, timber, recreation, land sales,$1.7 Billion acres of the Outer Continental ShelfU.S. Department of the Interior
3 U.S. Department of the Interior IT TransformationUnified Messaging (BisonConnect)Google apps for GovernmentEnterprise Information (eERDMS)Enterprise eArchive SystemEnterprise Content SystemEnterprise Forms SystemEnterprise Dashboard SystemeERDMS designObjectivesXML NIEMDriving factor November 28, 2011 “Managing Government Records”August 24, 2012 “M-12-18”U.S. Department of the Interior
4 eEDRMS Program VisionProvide the Department of the Interior with a single cohesive integrated information management program designed to support and manage departmental records related to , documents, and content in the CloudeERDMS will provide the Department with an single enterprise records management solutionfor the capture, preservation and management of electronic and paper-based records.eERDMS will identify, capture, preserve and accession recordsassociated with all inbound and outbound , forms, reports, documents, and other Departmental record assetsso that the Department will have effective access and management of all records.
5 eERDMS Program Objectives Capture all unified messaging journaled recordsCapture all mobile content recordsCapture all lines of business recordsCapture all business system recordsDevelop a super bucket records scheduleDevelop an online automated litigation hold processSupport Freedom of Information Act requestsSupport litigation early case assessment needsSupport Congressional and Department inquiries
6 Program Capabilities Records Management DoD 5015 v3 Records, Document and Archiving/JournalingRecords and Document Auto ClassificationRecords and Document Content ManagementRecords and Document ImagingRecords and Document ManagementRecords and Document ScanningRecords and Document WorkflowRecords and Document Collaborating WorkspacesRecords and Document AuditingRecords and Document Advanced Early Case Assessment & ReviewRecords and Document Mobility Content ManagementSection 508 Compliance out of the boxOptional: Advanced Legal Review, Social Media Capture, Management, National Shredding Program & National Digitization Program, Migration Services and Support Staff Services.Other areas are still being evaluated such as Fax
7 U.S. Department of the Interior OMB Directive M-12-18Requires to the fullest extent possible - eliminate paper and use electronic recordkeeping.Expected benefits:improved performance and promotion of openness and accountabilityfurther identification and transfer to the National Archives and Records Administration (NARA) of the permanently valuable historical recordsminimizing costs and operating more efficientlyA driving factor of eERDMSBegins with recordsCombines RM SystemsLow RiskHigh valueU.S. Department of the Interior
8 U.S. Department of the Interior eERDMS EnvironmentEnterpriseContentSystemEnterpriseFormsSystemERANIEMXMLHuman ResourcesEnterpriseRecordsSystemEnterpriseDashboardSystemContractsSecurityPersonnelFinanceProgramsOperationsAdministrationLogisticsEnterpriseFaxSystemEnterpriseSocialSystemU.S. Department of the Interior
9 U.S. Department of the Interior Big Data, Big Business600+ million s a year70 Million in Jan 2013100 Million Estimated for February 20131.2B s received15.5M records produced a day22 Billion data points generated5,500+ FOIA cases a year200+ ongoing litigation cases100+ million printed pages a year4,100+ mobile devices15,000 Fax devicesExabyte / Zettabyte of electric contentU.S. Department of the Interior
10 Records Management Objectives Provide the Department with:a single, simplified, integrated Records Retention Schedule for managing Bureau/Office recordsa Retention Schedule based on Lines of Business shared across Bureaus/Officesa Retention Schedule which reduces the complexity of the existing Schedules to allow for the use of auto-classification tools for assigning retention periods to Department recordsWe are, integrating knowledge for tomorrows workforceCM startsThe information John just provided is the background on the creation, management and rollout of various segments or the program .Now we will change the focus to the management of all of this data with the heavy lifting tools of the program, records management, auto-classification and Technology Assisted Review.
11 Starting Point 14 Bureaus/Offices in DOI Simplified ScheduleTraditionalBig Bucket14 Bureaus/Offices in DOI200 existing Retention Schedules2,330 retention instructionsSome Big Bucket SchedulesSome Traditional SchedulesSome schedules in draftSome schedules at NARA awaiting approvalTo organize the vast amount of data we have in the environment; Carol had to reduce the number of retention instructions by simplifying the schedules.We had to reach a level of granularity with the schedules which would allow for Auto Classification but still adequately capture the records.
12 Department Records Schedule (DRS) Strategy Started with the Existing DOI Retention SchedulesIdentified the Department’s Lines of BusinessCreated CrosswalksCreated Summary WorksheetsDrafted Super Bucket Retention Schedules, Ver 1Entered Super Bucket Retention Schedules, Ver 1 in eERDMSand then……..Auto-ClassificationThis section of my presentation focuses on the super bucket retention schedules that my colleague Carol Brock has created and implemented. I am sure all of you have heard about them and certainly recognize Carol as one of the worlds leading authorities in Digital preservation. In fact, Carol is working on her doctorate in that area when we she is not out here driving this segment of the program.
13 Policy Bucket Controls and Oversight Planning and Budgeting Litigation and Judicial ActivitiesRegulatory Development1st Big Bucket
15 Administrative Bucket AccountingAdministration/HousekeepingUltra Transitory?Transitory; out of office, Amazon, eBay, twitter, early dismissal, marketplace, Credit Union, Advisory notices, holiday notices, Dept. wide noticesHuman ResourcesInformation and Technology3rd Big Bucket((Ask the audience)). Has anyone ever heard the expression ULTRA BUCKET? UTLRA: system generated content
16 CrosswalksMapped each schedule item in every schedule to the Department’s Lines of BusinessDeveloped crosswalksVetted crosswalks with Bureaus/Offices Records OfficersSome Bureaus/Offices were very involved with the processSchedulesLines of BusinessVetted CrosswalksCarol Cross-walked schedule items to the DOI Lines of Business by identifying the best fit of a schedule item to the line of businessOften more than one line of business would fitPlaced an item as close to the function of its office-of-origin as possible, when there were choices
17 Super-Bucket Former Results 200 schedules / 2330 retention PeriodsFormer1 schedule / 207 retention periods over 47 LOBsSuper-BucketSuperbucket Roadmap: Similar in that they appeared to support the same LOBFrom the 14 Bureaus/Offices, we took the 200 existing retention schedules with 2,330 retention periods and condensed them down to one retention schedule with 47 items (lines of business) with 207 retention periods.
18 Auto-Classification Definition/How it Works Exemplars/Why Testing and RefinementTrainingImplementationLegal DefensibilityNOW Lets Focus on auto-classification.
19 Auto-Classification Definition of auto-classification: Tool that provides automatic identification, classification, retrieval, and archival and disposal capabilities for electronic recordsTool that uses a hybrid approach that combines machine learning, rules, and content analyticsTool that uses a rules engine and scans content for words, phrases, tone, etc. to identify semantic relationships to assign records classification and retention periods to content (Open Text)TO me as an eDisovery Litigation preparedness Consultant the most important aspect of AC is THAT IT Removes the classification burden from the users and increases the accuracy of classification!!!Much like document review, human participation is always subjective. Let’s leave Classification and review TO technology.The results are far more accurate as noted in “Legal Trec” and other such controlled studies that have been around as far back as 2006.Automates decisions for assigning retention rules to contentTool that is based on statistically relevant sampling and quality control
20 Auto-ClassificationTransparency and Defensible… the words that have captured the attention of the bench for good reason. A recent ruling on Rule 26(g) to Control e-Discovery AbusesA federal judge in Baltimore added teeth to Rule 26(g) with an opinion enforcing the mandatory sanctions provision. Branhaven LLC v. Beeftek, Inc. This is the first ruling of its kind that I know of. The ruing isolates subsection 3 which imposes sanctions when 26 g is violated which is improper certification of validity of the Discovery by counsel. This is a big game changer.As you are probably aware, the volume of content we produce and have to manage continues to grow, and the only sane thing to do is to start getting rid of content that has no business value. In order to do this, we need to classify the content. This is where Auto-Classification is very important, because it allows us to classify low-touch content such as legacy content, and social media. Auto-Classification is integrated with OpenText Records Management, meaning that you can apply you existing RM classifications and even make use of existing classified documents.There are a couple of things that make Auto-Classification special:1 - We have taken the voodoo out of classifying content by providing a TRANSPARENT, step-by steps process that has been created specifically for records managers to help them achieve their desired accuracy and thoroughness.<CLICK>This process is based on workbenches used for identifying exemplar documents and rules, testing and refining effectiveness and quality assurance and sampling against a broader set of documents on an ongoing basis. The Testing and Optimize workbench performs automated testing, provides reports on effectiveness, and provides suggestions on how to improve effectiveness.2 - Records Managers have told us that they are uncomfortable trusting retention and disposition to a “blackbox” technology.That is why we have built DEFENSIBILITY directly into the solution. Auto-Classification. It includes the a wizard to statistically sample content and a Review Workbench where Records Managers can quickly view documents to accept and reject the classification. This work on a small subset of documents can be used to further refine the accuracy of classification. The ability to demonstrate that you have tested and continue to monitor the effectiveness of Auto-Classification will provideDefensibility and transparency is critical to Auto-Classification, however, it is also good to know what is under the hood. Auto-Classification is powered by OpenText Content Analytics (formerly Nstein) which is a world class semantic analysis and classification engine - which means that tuning the engine will be easier, faster, and better results will be achieved.
21 Auto-Classification Process System uses exemplars of each file node to train system to recognize patterns, tone, etc.Find “like” (similar) feature used to gather additional exemplarsUse exemplars to create a modelPrecision and recall numbers need to be 75% or betterRefine model with additional exemplars over timeAuto-classification run on incoming content to assign retention periods.Back to the process of creating a defensible program. So far, AC is un-tested in Federal sector (although it may already be at intelligence… but they are not talking).DOI attorneys are discussing our approaches with DOJ to assure legal defensibility of our processes.AC based on precision and recall. Since assigning record-ness is usually a user function with minimal compliance, normal practice precision and recall are fairly low. Automated AC can raise those numbers about 75% with refinement. We consider this a great success!
22 Hold Options Search-Based Holds User-Based Holds Location-Based Holds Classification-Based HoldsOther ConsiderationsJournaling“Live” ContentContent at RiskOnto ECA . ECA to me is actually determining the scope and material facts of the matter in order to gather the appropriate evidence and relevant data. Here are our choices in Search-Based Holds Options in content Server- The standardUser-Based Holds- THE option of choice is best when the specifics of a case are not yet knowLocation-Based Holds- Good when you know where the content is, or if there is mixed content in a location. Also effective for users personal WSClassification-Based Holds- Rare - but potentially en entire class of content needs to be placed on hold
24 User Based HoldsIn addition to using keywords, folders or RM Classifications to determine what is on Hold, you can choose Users that are on Hold.Each ‘Hold’ can have different users with different time periods to place content on Hold …...
25 User Based Holds Date ranges can be applied Applies a hold to all items Created By, Owned By or have a version added by the users in the specified date range.The last tab in the process shows a status of how many users haven’t been processed yet, either because they have newly been added or removed from the hold, or if the date range criteria has changed.If you enter a date range, then upon processing, only content created, owned by or have a version added by the users in that time frame will be placed on hold. When you upload a document to the system, you are logged as the creator of that content, there may be someone else that is the owner of that content. And if you upload a version to a document that was originally created by someone else, that document will also be put on hold if you are and if it falls within the date range.If you leave the date ranges blank, then all content in the system created, owned by or have a version added by the specified users will be put on hold, and if the To Date is blank, then any content added on a continuing basis by the users will also be put on hold. So this is a good way to set up a hold in perpetuity, or a continual hold.The Comments of the user based hold will be stored in the audit trail for the holds.User Based HoldsLPU-1871 US: FR: Place a users content on HoldLPU-2334 MA: Process\update user based holds (apply hold to managed items)
26 Users Can be RemovedView users assigned to this Hold, or Remove them. TO me, the targeted hold, custodian interviews and targeted fact gathering pays off in the end.Filter results list by search.See status of hold per user ….
27 More Advanced SearchHere are some of the Advanced search options (tick off from list on left)
29 Communication and Outreach Shared vision and goals up, down, and across the organizationBureau/Office Records Officers Work GroupRecords Officer Task Force with leadership roleStaff dedicated to supporting the effort with the clientPete Denholm is here.- John will introduce him and the Outreach & Comms
30 Thank you John Montel eRecords Service Manager Service Planning and ManagementDepartment of the InteriorOffice of the Chief Information Officer1849 C. Street, N.W.Room 7444Washington, DCT. (202)C. (202)F. (202)E.Carrie MalleneDiscovery SMEIQ Business GroupPrime for eEDRMSDepartment of InteriorRoom 2012Washington, DC 20040CE.