Enterprise Data Management and NIEM “Positive Impacts on Information Sharing” December 2010 DHS Enterprise Data Management and the National Information.

Enterprise Data Management and NIEM “Positive Impacts on Information Sharing”
December 2010 DHS Enterprise Data Management and the National Information Exchange Model (NIEM) to Foster Improved Information Sharing Unclassified

Agenda Introductions and Level Set
Enterprise Data Management and NIEM at DHS How EDM and NIEM support agency EA and Segment Architecture Processes Break How EDM and NIEM align with Information Sharing Environment EDM Best Practices and the Data Management Working Group – How Data SMEs Collaborate Roundtable Unclassified

You are not alone in this world
Who is here – data architects and SMEs, data managers, and interested parties Nuggets from Forrester Report “What is less understood by Mission areas than business and data architecture – technical and application architectures are the focus of most EA programs” Insights from Gartner report “Data Management will fail to yield expected results unless organizations adopt rigorous data governance and improved data integration planning” Forrester Research published January, 2010 Technical and application architectures are much stronger domains for most EA programs. Our September 2009 general EA survey showed that only 15% of our 415 respondents said they had either not addressed or only implemented a small part of what they need for their infrastructure (technical) architecture domain, and 22% said that about their application architectures (see Figure 3). But 43% said the same about their IA domain. Just under one quarter said they had a large part or nearly all of what they need from IA. For most established IA programs, value delivery is still in the future. Only 22% of the architects we surveyed who had formal IA programs said they were receiving demonstrable value from it. The rest have yet to see value or expect their biggest payback for their efforts to come in the years ahead. Most organizations consider data governance as very important, yet few are good at it. Seventy-four percent of our IA survey respondents called data governance very important or on the critical path, with no respondent saying it was not important (see Figure 6). And yet, 39% said their data governance maturity was very low or low, with another 42% saying it was average. Only 17% said their data governance maturity was high or very high. Gartner Report: February 2008 The data management discipline affords numerous opportunities for reducing and controlling IT costs. Consolidate data management and integration tools and technologies to minimize redundancy. • Focus on essentials — limit deployment of new databases, data integration and metadata management technologies to projects where clear business benefits, such as cost savings or revenue growth exist. 1. Perform operational database consolidation. 2. Optimize data integration tools licensing. 3. Leverage existing data structures and data integration process, rather than building new. 4. Perform data mart consolidation. 5. Enforce standards to foster reuse and agility. 6. Defer replacement of custom-coded architectures. 7. Explore open source licensing. 8. Renegotiate services contracts. 9. Defer low-priority/limited-benefit projects. Through 2012, 70% of SOA projects in complex, heterogeneous environments will fail to yield expected business benefits unless Master Data Management is included. Unclassified

So why does Enterprise Data Management matter?
Critical data questions you may be interested in: Who manages this data? Where is it stored? Who can access this data? How accurate is it? How recent is it? How trustworthy is it? How is this data related to other data elements in the enterprise—i.e., what is the associated context? DHS has determined that the FEA Enterprise Architecture framework and the data reference model in particular lack clear guidance on how to implement effective data architectures These critical questions are a driving force in our efforts to improve the management and sharing of data across all Components and position ourselves for the planning and development requirements of both EA and segment architectures Enterprise Data Management is critical to the data architecture component of EA Frameworks and drives improved understanding and trust of data sources Unclassified

So let’s talk about Enterprise Data Management and NIEM at DHS
Unclassified

DHS Enterprise Data Management Office
Enterprise Data Management (EDM) MISSION Promoting collaboration to achieve efficient management of all data collected, created, used, maintained, shared, stored and disposed by DHS. Fostering innovation and elevating best practices to strengthen and enable the Homeland Security community to: Data and Information Find - Understand - Access - Trust - Use - Share - In support of the DHS Mission The EDMO mission has concentrated on promoting improved data and information management as a means of improving information sharing Originally called the Metadata Center of Excellence before Donna Roy became the Director The mission of data management at the DHS Headquarters level was confusing to those of us in the field Data SMEs now feel that the data management office is more focused on delivering improved value to DHS and providing practical guidance and support to the data troops in the field Unclassified

Enterprise Data Management Core Values
Excellence – providing knowledge, trust and expertise Collaboration – working together we can make a difference Customer Service – voice of the Customer is the most important Recognition – give credit for good work and ensuring best practices are elevated Team Building – the community is only as strong as our weakest link Each of these core values directly reinforces the DHS IT Strategic Plan These core values are being practiced on a daily basis by going out and engaging with mission and technology stakeholders and aiding mission efforts – building data models, explaining performance metrics and balanced scorecards, reviewing program architecture artifacts Unclassified

What DHS Enterprise Data Management is
Enables effective enterprise data management, information sharing, and data reuse across agencies. It utilizes the FEA Data Reference Model (DRM) Framework The DHS DRM is a framework for the visualization, discovery and reuse of enterprise data architecture assets Provides guidance to Components Allows for bi-directional alignment of artifacts FEA’s viewpoint of DRM was great in theory but lacked the practical guidance There is no real reference model content unlike Services and business functions We have talked to the authors of the FEA DRM and they agree with us. This is now a best practice DHS Data architecture is based on a consistent representation of data using published metadata terms, definitions and data categories, data artifacts that are understandable and useful, information sharing using well defined content definition that is available and reusable Unclassified

Enterprise Data Management Concept of Operations (ConOps)
Establishes what it means to “operationalize” the DHS Enterprise Data Management (EDM) and DRM - to enable information discovery, sharing, exchange, and reuse across DHS Describes Governance, Architecture, Information Sharing, and Performance Measurement practice areas Identifies the general types of resources required to be obtained through the budget cycle or redirected Sets the scope and provides a high-level roadmap for DHS and its Components to mature data management practices to attain a target state in which data and information sharing and reuse are enabled via the EDM framework EDM Concept of Operations was our approach to improving the guidance of the FEA DRM and explaining the major practice areas of data management – Governance (standards and policies), architecture (data model development and modeling standards, model management and presentation, and key data artifacts), Information sharing (information exchange definition, information lifecycle), and Performance Measurement (balanced scorecards at the headquarters and Component levels, measuring the quality of data health and architectural products) Mike Simcock Background overview – supporting data management and enterprise architecture at DHS for the past 6 years at both headquarters and in the mission areas, Lead on developing a logical data model for Person Screening with a cross-agency team from the major Components. Used the logical data model to do a gap analysis on NIEM in order to add content for Screening, Immigration and augment existing Justice and Intelligence content. Have continued to use the data related outcomes of this team effort for improving information sharing, architecture planning and Screening portfolio management. Have been advocating data architecture principles and practices as a way of improving the data management landscape at DHS. Unclassified

DHS Enterprise Data Management Roadmap
EDMO has found that this roadmap provides the Component data SMEs with a better sense of where we have been and where we are going Each new version has filled in the blanks for key areas of data management and data architecture Unclassified

So how are you doing your information sharing and getting everyone to talk in the same terms?
Q & A Unclassified

“Common Language” for Information Exchange
NIEM Overview In addition to providing guidance and support for all aspects of data management and information sharing within the DHS mission, … Since September 2008, the Enterprise Data Management Office has been serving as the lead Program Management Office of the National Information Exchange Model (NIEM) program for the U.S. Government and its State, Local, tribal and private sector partners. Components of NIEM data model Repeatable, reusable process for business users to document information exchange requirements “Common Language” for Information Exchange DHS and DOJ signed a MOU in 2005 and DHS started adding content to the original GJXDM data model for the screening of travelers In 2008 DOJ passed the PMO leadership role to DHS Unclassified

DHS and NIEM Information Sharing
Component Project Name CBP Federal Motor Carrier Safety Administration Enforcement (EID) to Seized Assets and Catalog System (SEACATS) Sharing US Census – Entry Summary US Census – Business Partner NCIC/NLETS queries Border Patrol Tracking System Blue Force Tracking (SBI P.25) U.S. Passport Query Interface USCIS Person Centric Query Verification FEMA Exercise Scheduling Improvement Plan US-VISIT US IDENT to CJIS IAFIS S&T Hospital Availability Exchange DHS Core Biographic Elements for Screening and Immigration Terrorist Watch Listing (TWPDES 1.2b) ICE Law Enforcement Info Sharing Services (LEISS v1.0 & LEISS v2.0) Removable Alien Query (RAQ) DNDO Radiological / Nuclear Detection DHS Adoption has gone from 0% to 40% of major IT programs, forecasted to be 60% by FY11 NIEM projects are in development with over 90% of Components Measurement of Adoption and Project progress tracked on the CIO Enterprise Data Management Scorecard FY08 thru FY10: 30 NIEM projects completed FY11: NIEM Projects projected Mandated within the HLS Enterprise Architecture for Common or Shared [SOA] Services on the Enterprise Bus Mandated by PM ISE’s implementation of Common Terrorism Information Sharing Standards (CTISS) Mandated by OMB for cross agency sharing and supported by HHS, USDA and Treasury DOJ and DHS grant language for State and Locals includes NIEM conformance Several Fusion Center RFP’s have been released requiring NIEM conformance Here’s what we have accomplished so far with NIEM Unclassified

Improving Information Sharing through the use of data models
The Logical Data Model (LDM) is the source for identifying what data types are available for sharing within an organization or mission area. By incorporating data entities from the logical data model into the information exchange model, exchange modelers can assure stakeholders that exchange elements are in fact available and being derived from common source. If a new information exchange requirement develops then the LDM must be updated to support the new requirement The Information Sharing landscape provides a complete picture of a component’s data environment What we have found is that the Logical data model and the Information exchange model complement each other in order to define what is available to share within a mission area One of our Components has gone so far as to automate the process of defining information exchanges by defining table and column elements using the NIEM data dictionary and ensuring that the information exchange concepts exist with the Enterprise Logical Data Model. This process automatically generates the exchange schema design and WSDL for each message Unclassified

Logical Data Model and NIEM Exchange Model Integration
The combination of the enterprise logical data model and the NIEM domain models ensure that the information sharing data landscape is complete Goal is to identify the elements of the exchange in business understandable language Unclassified

How EDM and NIEM fit in DHS EA and Segment Development Processes?
Unclassified

DHS Enterprise Architecture
DHS Segment Architectures Benefits Administration Domain Awareness Law Enforcement Incident Management Screening Securing Enterprise Mission Services Enterprise Business Services Enterprise Information Technology (IT) Services The DHS Enterprise Architecture organizes the Department’s mission space around “Functional Areas.” Provide a DHS-wide view of what the Department does and what resources it will need to accomplish its missions. The functional areas have a number of overlapping information objects like Person, infrastructure, and Response resources The Functional Areas serve as the underlying structure, and neutral lens, for planning and assessing performance of DHS resources and capital investments. Unclassified

DHS Segments Information Landscape
Function Area logical data models DHS was built with 22 disparate organization, 7 major organizations such Customs, INS, Coast Guard, FEMA Each with their own “Silos of Excellence” – Stovepipe legacy systems with traditional Component specific or no sharing at all……. Logical data models were absolutely critical to getting a sense of what could be shared The hierarchy of data models explanation Unclassified

EDM Support to DHS Segment Architecture Development
Data Architecture Templates and planning documents Data and information sharing artifacts in System Engineering Life Cycle (SDLC) Data and information sharing artifacts in Segment Architecture planning processes Data management wording in ITAR (acquisition) and SOW language Included critical data architecture documents and peer reviews in the System Engineering Life Cycle (SDLC) Support Segment Architecture planning processes by identifying As Is data capabilities and support of business architectures and Target data architecture requirements of the Segment. This support includes identification of data and information exchange reuse opportunities and modeling of information sources and exchanges Included required data management wording in ITAR (acquisition) and SOW language to expose new data assets and information exchanges and require use of data management standards and processes. DHS Data management plays a significant role in identifying the architectural influences that data and information play in developing solutions that meet mission needs. So how did we do that? Unclassified

Support to DHS Enterprise Architecture Development
EDMO drives the information definition and management support required by Enterprise Architecture frameworks to meet mission needs Identifying information sources, information exchanges, and data services for the information sharing environment Driving data source and information exchange reuse for new investments by mandating inclusion in the EA Information Repository Support to Investment Programs by reviewing their data architecture plans and providing feedback where appropriate and needed Identifying information sources, information exchanges, and data services for the information sharing environment Driving data source and information exchange reuse for new investments by mandating inclusion in the EA Information Repository Support to Investment Programs by reviewing their data architecture plans and providing feedback where appropriate and needed Unclassified

Support to DHS SOA Deployment
EDMO drives the use of NIEM for service development This includes required use of NIEM for information exchange definitions Promoting common exchange definition and reuse to reduce development and maintenance costs NIEM has traditionally been about the definition of the payload but EDMO has been a leader in looking at the message header and package requirements from a data perspective. Common header development is moving forward as seen in the timeline Service information exchanges must be defined for any new physical service Information exchanges must use the Information Exchange Package Documentation standard Unclassified

EA Information Repository (EAIR) and Data Reference Model Support
A centralized repository that enables the search, discovery, and reuse of Enterprise Architecture assets used by DHS and its component organizations It supports DHS alignment to the Federal Enterprise Architecture (FEA) Reference Models Metadata for each data asset and information exchange gives both business and technology users the information they require to determine if this is a reuse candidate Key questions that the EA Information Repository provides: What is the authoritative or trusted source of the data that is of importance to me? What are the characteristics and categories of the data accessible by a particular application system? Is my data asset information protected and available only to authorized users? Who can I contact to gain access to data sources that may provide opportunities for reuse? Unclassified

DHS Information Sharing Environment (ISE)
Information sharing across DHS is dependent on understanding where to find the answers to key mission questions such as where is the best source of person related information and related encounters at DHS The repository is being used to answer the Information Discovery questions Data layer services to mission critical data sources is a key component of the DHS ISE and the presentation of understandable and trusted information Well defined information exchanges provide the common definition and understanding of what information is being delivered Unclassified

EDM Best Practices and the Data Management Working Groups –
How DHS Data SMEs Collaborate Unclassified

EDM Waves of Change DHS planning approach for improving data management across the agency. Foundational documents and practices are in place. EA Information Repository is in place and being augmented to better present all the reference model and interrelationships. Scorecard performance metrics are being used to show value to the mission. Data stewardship is in its infancy. Budget requirements for greater data support to the mission are ongoing. Unclassified

Waves of Data Management Change
Data Management Maturity is a fundamental change in how organizations address their vision and management of information – going from reactive to optimized The wave concept has been around for some time and is based on the idea that each new wave builds on the momentum generated by the previous wave As always happens in IT, mission priorities change consequently DMM must be nimble enough to adapt to change and refocus Today’s wave is Information Sharing but that could be overshadowed by the changing needs of the Agency or Administration Key value of the Waves of data management change is to provide improving support to mission EA efforts while maintaining consistency and adaptability of the data architecture Unclassified

Implementing Data Management Maturity
Collaborative Working Groups - DMWG / NIEM Blue Team DHS Best Practices Data Management and Information Sharing Documents and Guidance EDM Balanced Scorecard Data Management Summits Mission Specific Data Workshops Data Management Office guidance for setting up and operating with the Program or Component DM subject matter expert participation This is how DHS has implemented the maturity model so far Unclassified

Collaborative Working Groups
EDMO Leadership NIEM Blue Team is composed of information exchange subject matter experts from each organization Data Management Working Group is composed of data subject matter experts from each organization from with DHS DMWG Focus Teams drive best practice development and subject matter guidance Purpose of these working groups is to establish collaborative forums where best practices, information updates and problems can be discussed Focus teams are stood up to address specific Data management or information sharing priorities or critical issues Unclassified

Data Management Guidance Documents
Information Exchange Package Documentation Data Modeling Methodology Guidance Data Stewardship Framework Data Management Plan Performance Management Framework Information Flow Modeling Guidelines These are the major products we have delivered to date Still to come or in progress are foundational documents for the DHS Components to assist with Data Standardization / Quality and Reference Data Management Unclassified

Support to DHS Enterprise Architecture Deployment
EA Planning LDM and NIEM integration LDM development Information Flows Data Governance & Stewardship Data Standards & Processes Metadata development Master Reference Data Information Sharing Access agreements Information exchange documentation EDMO promotes the data management and NIEM value proposition to Component’s EA groups to demonstrate how they aid their EA efforts to meet mission needs Inclusion of data management SMEs in investment program reviews to ensure data and information exchange requirements are met Unclassified

Improving Information Sharing through the use of Mission Specific Data Workshops
Data workshops with mission area subject matter experts, i.e. Enforcement Officers, Intelligence Analysts Goal is to identify their information needs and sources of data necessary for supporting their mission efforts Utilized use cases to document the processes each used for gathering information and making decisions Generated information flows to assist each group in recognizing what information was available and what was not being used by each area Utilized EA Information Repository to identify what data sources are available to answer their questions which become new information sharing opportunities EDMO determined that data workshops were an effective way to improve the understanding of what mission support experts were using and what information was required to make them more effective in their daily efforts Information flows were developed from their input and pinpointed key data sources that were available and what information was missing. This input provided EDMO and the Information Sharing Coordinating Group with tactical focus on ways to improve information sharing Unclassified

DHS Enterprise Data Management Scorecard
DHS EDM Scorecard DHS Enterprise Data Management Scorecard Data Architecture Information Sharing Governance Performance Measures Data Asset Catalog % of Component Systems mapped to Data Assets # of Data Assets Captured Score # of Component CDMs and LDMs mapped to Program Investments Component Taxonomy /Vocabulary Developed NIEM IEPDs in Pipeline NIEM IEPD Completion Score NIEM Adoption Score NIEM Domain Stewardship Data Quality Plans Authoritative Data Source Identification and validation Data Management Plans mapped to Program Investments Stewardship Groups established (tactical, operational, strategic) Data Standards Established and Used Business Cases Developed Business Case with Metrics Developed % of Performance Metrics captured at Component Level PM Adoption Score Designed to assist data efforts within the Components by demonstrating to their CIOs how data and information sharing efforts are succeeding Originally intended to provide input to the DHS Secretary on the baseline number of data sources that existed within DHS Based on the number of systems in the EA Systems Inventory, Components have identified over 850 data sources Components are now working on developing balanced scorecards at the Component level and EDMO will consolidate the Component numbers to the DHS level Intent is for Components to have stronger communication with their internal development groups Unclassified

Wrap up Discussion What else can we answer to aid your individual efforts at improving information sharing through EDM and NIEM? How can NIEM help your efforts? EDM and NIEM have a proven track record at DHS for improving information sharing collaboration Roundtable discussion of what has been presented. Answer specific questions around data management and NIEM efforts Discuss NIEM growth approach to new content, governance structures, PMO leadership Unclassified

The End Unclassified

Enterprise Data Management and NIEM “Positive Impacts on Information Sharing” December 2010 DHS Enterprise Data Management and the National Information.

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Enterprise Data Management and NIEM “Positive Impacts on Information Sharing” December 2010 DHS Enterprise Data Management and the National Information.

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