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A Metadata Architecture For Enterprise-Wide Data Sharing

A Metadata Architecture For Enterprise-Wide Data Sharing

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A Metadata Architecture For Enterprise-Wide Data Sharing

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  1. A Metadata Architecture For Enterprise-Wide Data Sharing

  2. Department of Defense (DoD) Data Interoperability Challenge Same Data Requirements Different Functional Needs, Same Descriptions, Different Names Logistics Components/ Services Transportation Procurement Personnel Command & Control Finance Medical

  3. DoD TARGET DATA SHARING ENVIRONMENT A Logistics Perspective SAUDI ARABIA AMMRL QATAR IMRL KUWAIT NAOMIS UAE ATAC MEXICO CAMS DSS MIMMS NSIPS JAPAN SCS ATLAS II CC SS NALDA II FRANCE ATAC AWRDS APS MC-TFS U2 UK MANPERS SAILS MAARS II CRIM CANADA SBSS SAMS MPS (BIC) CAIMS ISRAEL (personnel?) CAS A SARSS FIMAR OAS SCS LIF ARAMIS GO81 SAAS-MOD CASEMIS ASIAN SASSY AFEMS ROAMS CMIS SEATO DO35 TAPDB NATO SUPPLY MGMT TAMMIS SNAP/SUADPS/FIMAR ATAV (LIDB) FUELS - NEURS WARS CAIMS CAIMS MUFFIN AMMIS ARMS SPS/SDW PMIS SAMMS ATEMS TAMMIS MEDSUP FLIS SCCR JECPO TAMMIS MEDASM DVD Prime Vendors URD DOD CAV DAAS LOTS MEDSILS UDR VMI Freight Links NAV NAC MEDLOG COP CSE DISA DBSS GCCS - C2 IC3 JL ACTD ALP GDSS WPS IBS CFM TAPE TAPE TAPE DITTS RFT-E TCAIMS II RFT-K Legend: Essential AIS ATAC MRP II Contributing AIS USMC USN USAF COALITION USA MILSEALIFT GSA USCG DoD Joint Applications GCCS & GCSS (IDEs) Commercial DLA JMAR TRANSCOM GTN DARPA MTMC AMS GATES CMOS UNCLAS CENTCOM (SOUTHCOM SOCOM) Server TCACCIS UNCLAS PENTAGON UNCLAS JFCOM Servers UNCLAS PACOM Server UNCLAS USFK JTAV Server UNCLAS EUCOM Server G081 GCCS = Global Command & Control System GCSS = Global Combat Support System BROKER GOPAX ADANS ISSE GUARD ISSE GUARD JALIS CLAS PENTAGON CLAS USFK JTAV CLAS JFCOM CLAS EUCOM CLAS CENTCOM CLAS PACOM

  4. METADATA REPOSITORY Defense Data Dictionary System (DoD Standardized Data Elements {SDE}) 17000+ SDEs The DDDS: The Current DoD Repository of DoD Standardized Data Elements Intended to be the DoD Repository of Data Elements to Support DoD Enterprise-wide Interoperable Data Sharing

  5. PART I: The Problem

  6. Current Problems 1. Incorrect data architecture abstraction level for representing Enterprise Level Data Elements for interoperable data sharing 2. Numerous redundant representations of Standardized Data Elements (SDEs) (DIFFERENT NAMES – SAME DEFINITION) 3. Incomplete, non-existent and/or, non-current SDE metadata 4. Inadequate categories of SDE metadata 5. Inadequate support / enforcement of data administration processes for data management

  7. A Data Element Name and Data Element Definition Refresher: Two Data Element Metadata Attributes • Data Element Name is a label given to establish Data Element identity • Data Element Definition is a description providing complete, • unambiguous meaning represented by a Data Element • Name and Definition together provide the semantic context for the • data item values represented by a Data Element • Some key concepts/principles/facts about Data Element Naming and Definition: • NAMEandDEFINITIONare inseparable • NAMEis a unique identifier forDEFINITION • A NAMEcan be viewed as a kind of very shortDEFINITION • In order of precedence,DEFINITIONcreation should always • precedeNAMEcreation • Impossible tocorrectly NAMEa data elementwith precision without aDEFINITION • NAMEand DEFINITION are at the core of the data integration / sharing process • Many data sharing issues arise from “bad” data element NAMING and • DEFINITION practices

  8. A Proposed Metadata Architecture for Shared Enterprise Data Elements • Focuses on solutions for: • Problem 1 – Incorrect data architecture abstraction level • Problem 2 – Differently named data elements for the same • data element concept • Problem 4 - Inadequate categories of standardized data element • metadata • Not a solution for every kind of impediment to • interoperable data sharing • Problems 3 and 5 require quality improvements in • process execution and in data management governance • and will be addressed in Part II. • Will begin by looking more closely at the • fundamental metadata architecture levels…….

  9. Design Layers of a Business Information System Database Architecture • Specified Context Data Model Layer • Roughly analogous to high level conceptual Entity-Relationship (E-R) data models of functional area/business domain, or Community of Interest (COI) data depicting the structure and relationships of entities and their attributes. • Implemented Technology Data Model Layer • Database schemas represented in a particular technology (SQL, COBOL, etc) based on fully attributed 3rd normal form logical data models • Operational (Vendor) DBMS Data Model Layer • Roughly analogous to a physical data model representing a particular vendor’s version of a technology based schema, i.e., Oracle SQL DBMS vs IBM DB2 SQL DBMS vs Sybase SQL DBMS, etc, etc • Business Application View Data Model Layer • Represents the application system access interface to a DBMS which preserves the separation and integrity of the database data from systems that operate on and manipulate the data

  10. Design Layers for a Business Information System Database Architecture “PERSONNEL” FUNCTIONAL AREA DEPENDENT DATA MODEL TEMPLATES “LOGISTICS” FUNCTIONAL AREA DEPENDENT DATA MODEL TEMPLATES “FINANCIAL” FUNCTIONAL AREA DEPENDENT DATA MODEL TEMPLATES “SPECIFIED” DATA MODEL LAYER (DoD FDAd Domain) ENTITY ENTITY ENTITY ATTRIBUTE ATTRIBUTE ATTRIBUTE SUBJECT SUBJECT SUBJECT • Specified Context (Community of Interest) Data Model Layer Layer 1 • May be represented in one, a combination of, or all of the following views: • Entity w/attributes; no key designations; un-normalized; unresolved many – to – many relationships • Key based entities; un-normalized; un-resolved many – to – many relationships • Fully attributed; un-normalized; resolved or un-resolved many – to – many relationships • Fully attributed; 3rd normal form; developed sub-typing; resolved many – to manys • Current DDDS / DDA functional / subject area domains map to domains represented by • designated DoD Functional Data Administrators (FDAds): • Logistics DUSD(L) • Personnel USD(P&R) • Comptroller USD(C) • Health Affairs ASD(HA) • Etc, etc • Each DoD “Subject Area” DAd should have a “specified” data model that represents the data element • structures and relationships of functional area data element requirements for their respective functional area • or community of interest.

  11. Design Layers for a Business Information System Database Architecture • Implemented Technology Data Model Layer FUNCTIONAL AREA / SUBJECT MATTER DEPENDENT DATA MODEL TEMPLATES “SPECIFIED” DATA MODEL LAYER (DoD COI DAd Domain) ENTITY ATTRIBUTE SUBJECT COLUMN COLUMN COLUMN SCHEMA SCHEMA SCHEMA TABLE TABLE TABLE TECHNOLGY DEPENDENT (e.g.,SQL,) FULLY ATTRIBUTED, LOGICAL DATA MODEL “IMPLEMENTED” DATA MODEL LAYER (Data Architect / Modelers Domain) TECHNOLGY DEPENDENT (e.g.,COBOL,) FULLY ATTRIBUTED, LOGICAL DATA MODEL TECHNOLGY DEPENDENT (e.g.,IDMS,) FULLY ATTRIBUTED, LOGICAL DATA MODEL Layer 1 Layer 2 • 3RD Normal form ERD logical data model • Represented in a technology dependent data architecture schema • Technology driven / constrained data element naming • Subject area entity and attribute templates are deployed into schema tables and • columns that must conform to a particular chosen technology such as COBOL or SQL. • Layer 1 attribute metadata is inherited by Layer 2 columns • The relationship between Layer 1 and Layer 2 is one – to – many. That is to say that • any attribute from Layer 1 may be deployed as a column into many Layer 2 schemas.

  12. Design Layers for a Business Information System Database Architecture • Operational Vendor DBMS Data Model Layer FUNCTIONAL AREA / SUBJECT MATTER DEPENDENT DATA MODEL TEMPLATES “SPECIFIED” DATA MODEL LAYER (DoD COI DAd Domain) ENTITY ATTRIBUTE SUBJECT COLUMN SCHEMA TABLE TECHNOLGY DEPENDENT (SQL, COBOL, ETC), FULLY ATTRIBUTED, LOGICAL DATA MODEL “IMPLEMENTED” DATA MODEL LAYER (Data Architect / Modelers Domain) DBMS TABLE DBMS TABLE DBMS TABLE DBMS COLUMN DBMS COLUMN DBMS COLUMN DBMS SCHEMA DBMS SCHEMA DBMS SCHEMA DBMS DEPENDENT (e.g., Sybase) DBMS DATA MODEL DBMS DEPENDENT (e.g., DB2) DBMS DATA MODEL DBMS DEPENDENT (e.g., Oracle) DBMS DATA MODEL “OPERATIONAL” DATA MODEL LAYER (Domain of Database Administrators (DBAs)) Layer 1 Layer 2 Layer 3 • Roughly analogous to a physical data model • Vendor’s versions of particular technology based schema such as SQL, • i.e., Oracle SQL DBMS vs Informix SQL DBMS, vs Sybase SQL DBMS, etc, etc. • Data element naming is bound by vendor’s implemented DBMS business rules • for a particular technology based schema. • Again, the relationship between Layer 2 and Layer 3 is one – to – many. That is to say that • any column from a Layer 2 schema may be deployed as a DBMS column in many Layer 3 DBMSs.

  13. Design Layers for a Business Information System Database Architecture Business Application View Data Model Layer BUSINESS INFORMATION SYSTEM BUSINESS INFORMATION SYSTEM BUSINESS INFORMATION SYSTEM APPLICATION VIEW TABLE APPLICATION VIEW TABLE APPLICATION VIEW TABLE APPLICATION VIEW COLUMN APPLICATION VIEW COLUMN APPLICATION VIEW COLUMN Layer 1 Layer 2 FUNCTIONAL AREA / SUBJECT MATTER DEPENDENT DATA MODEL TEMPLATES “SPECIFIED” DATA DATA MODEL LAYER (DoD COI DAd Domain) ENTITY ATTRIBUTE SUBJECT Layer 3 COLUMN SCHEMA TABLE TECHNOLGY DEPENDENT (SQL, COBOL, ETC), FULLY ATTRIBUTED, LOGICAL DATA MODEL “IMPLEMENTED” DATA MODEL LAYER (Data Architect / Modelers Domain) BUSINESS APPLICATION SYSTEM VIEW DATA MODEL (Command & Control) DBMS TABLE DBMS COLUMN DBMS SCHEMA BUSINESS APPLICATION SYSTEM “VIEW” DATA MODEL (Personnel App) DBMS DEPENDENT (Oracle, DB2, Sybase, etc) DBMS DATA MODEL “OPERATIONAL” DATA MODEL LAYER (Domain of Database Administrators (DBAs)) BUSINESS APPLICATION SYSTEM “VIEW” DATA MODEL (Logistics App) (Domain of Application System Managers (SMs and/or PMs) Layer 4 • Data element naming in conformance with functional area common business language terms • Finally, with respect to a single DBMS, the relationship between Layers 3 and 4 is also one– to – many • from 3 to 4. That is, a DBMS column may be deployed as view columns in many applications • that may interface with a particular DBMS.

  14. The Problem: Sourcing Enterprise “Context Independent” Data Element Standards from Enterprise “Context Dependent” Data and Information Systems and Databases SDE “A”: Person Given Name SDE “A”: Employee First Name SDE “A”: Legal First Name Standalone Database #1 Enterprise Common Data Element Concept “A” Standalone Database #2 Enterprise Common Data Element Concept “A” Layer 1 Person Given Name Layer 1 Sailor Given Name Layer 2 Salesman First Name Sailor First Name Layer 2 EFN Layer 3 Sail_Frst_Nm Layer 3 Layer 4 Name Layer 4 First Name SDE “A”: Sail_Frst_Nm Standalone Database #4 Enterprise Common Data Element Concept “A” Standalone Database #3 Enterprise Common Data Element Concept “A” Layer 1 Employee Given Name Layer 1 Legal Given Name Employee First Name Layer 2 Layer 2 Authoritative First Name Emp_Gv_Nam Layer 3 Layer 3 Lg_Auth_Frst_Nm Given Name Layer 4 Layer 4 Legal First Name Enterprise Registry of Standardized Shared Data Elements: The DDDS Enterprise Registry of Standardized Data Elements (SDE) To Represent Common Enterprise Data Element Concepts Enterprise Data Element Concept “A” Effective Result: Four differently named versions, or, representations of the Enterprise common Data Element Concept, “A”, that will exist in the Registry as Standardized Data Elements. Redundancy and ambiguity is the consequence.

  15. Design Layers for a Business Information System Database Architecture METADATA REPOSITORY Defense Data Dictionary System BUSINESS INFORMATION SYSTEM APPLICATION VIEW TABLE APPLICATION VIEW COLUMN (DoD Standardized Data Elements) 17000+ SDEs FUNCTIONAL AREA / SUBJECT MATTER DEPENDENT DATA MODEL TEMPLATES “SPECIFIED” DATA MODEL LAYER (DoD COI DAd Domain) ENTITY ATTRIBUTE SUBJECT COLUMN SCHEMA TABLE TECHNOLGY DEPENDENT (SQL, COBOL, ETC), FULLY ATTRIBUTED, LOGICAL DATA MODEL “IMPLEMENTED” DATA MODELLAYER (Data Architect / Modelers Domain) DBMS TABLE DBMS COLUMN DBMS SCHEMA DBMS DEPENDENT (Oracle, DB2, Sybase, etc) DBMS DATA MODEL “OPERATIONAL” DATA MODEL LAYER (Domain of Database Administrators (DBAs)) BUSINESS APPLICATION SYSTEM “VIEW” DATA MODEL (Domain of Application System Managers (SMs and/or PMs) • Database System Architecture Design Steps • Specified Context Data Model Layer • Implemented Technology Data Model Layer • Operational Vendor DBMS Data Model Layer • Business Application View Data Model Layer The DDDS Repository Intended to represent DoD globally shared enterprise standard data elements. Thus, the repository should contain only one named data element standard for each unique enterprise level data element concept. Layer 1 Layer 2 Layer 3 Layer 4

  16. Design Layers for a Business Information System Database Architecture BUSINESS INFORMATION SYSTEM APPLICATION VIEW TABLE APPLICATION VIEW COLUMN FUNCTIONAL AREA / SUBJECT MATTER DEPENDENT DATA MODEL TEMPLATES “SPECIFIED” DATA MODEL LAYER (DoD COI DAd Domain) ENTITY ATTRIBUTE SUBJECT COLUMN SCHEMA TABLE TECHNOLGY DEPENDENT (SQL, COBOL, ETC), FULLY ATTRIBUTED, LOGICAL DATA MODEL “IMPLEMENTED” DATA MODEL LAYER (Data Architect / Modelers Domain) DBMS TABLE DBMS COLUMN DBMS SCHEMA DBMS DEPENDENT (Oracle, DB2, Sybase, etc) DBMS DATA MODEL “OPERATIONAL” DATA MODEL LAYER (Domain of Database Administrators (DBAs)) BUSINESS APPLICATION SYSTEM “VIEW” DATA MODEL (Domain of Application System Managers (SMs and/or PMs) The DDDS Repository Intended to represent DoD globally shared enterprise standard data elements. Thus, the repository should contain only one named data element standard for each unique enterprise level data element concept. In reality, the repository contains many cases of differently named data elements that represent the same data element concept. The result is uncontrolled redundancy and ambiguity incapable of supporting seamless and interoperable data sharing. • Database System Architecture Design Steps • Specified Context Data Model Layer • Implemented Technology Data Model Layer • Operational Vendor DBMS Data Model Layer • Application View Data Model Layer Layer 1 A source for DDDS SDEs Layer 2 METADATA REPOSITORY A source for DDDS SDEs Defense Data Dictionary System Layer 3 One GIGANTIC semantic mess A source for DDDS SDEs 17000+ SDEs Layer 4 A source for DDDS SDEs

  17. ….But, Where’s the Beef ?? The DDDS “Big Bun” .…the Enterprise Data Element “Beef” ??

  18. CONCEPTUAL VALUE DOMAIN STRUCTURE CONCEPTUAL VALUE DOMAIN STRUCTURE TYPE CONCEPT STRUCTURE TYPE CONCEPT STRUCTURE CONCEPTUAL VALUE DOMAIN CONCEPT VALUE DOMAIN STRUCTURE TYPE VALUE DOMAIN STRUCTURE DATA ELEMENT CONCEPT STRUCTURE TYPE VALUE DOMAIN DATA ELEMENT Design Layers for a Business Information System Data Architecture DATA ELEMENT CONCEPT STRUCTURE DATA ELEMENT CONCEPT Layer 0 ISO 11179 BUSINESS CONTEXT INDEPENDENT DATA ELEMENT REPRESENTATION Functionally Independent Business Fact Semantic Templates (Globally Shared Data Elements) (Domain of DoD Data Administration) • The Enterprise Data Element Layer • ISO 11179 Naming and Definition • Context Independent Data Elements • Uniform Naming • Uniform Semantics • Uniform Value Domains

  19. Design Layers for a Business Information System Data Architecture CONCEPTUAL VALUE DOMAIN STRUCTURE CONCEPTUAL VALUE DOMAIN STRUCTURE TYPE CONCEPT STRUCTURE TYPE CONCEPT STRUCTURE CONCEPT BUSINESS INFORMATION SYSTEM APPLICATION VIEW TABLE APPLICATION VIEW COLUMN VALUE DOMAIN STRUCTURE TYPE VALUE DOMAIN STRUCTURE DATA ELEMENT CONCEPT STRUCTURE TYPE VALUE DOMAIN FUNCTIONAL AREA / SUBJECT MATTER DEPENDENT DATA MODEL TEMPLATES “SPECIFIED” DATA MODEL LAYER (DoD FDAd Domain) DATA ELEMENT ENTITY ATTRIBUTE SUBJECT COLUMN SCHEMA TABLE TECHNOLGY DEPENDENT (SQL, COBOL, ETC), FULLY ATTRIBUTED, LOGICAL DATA MODEL “IMPLEMENTED” DATA MODEL LAYER (Data Architects / Modelers Domain) The DDDS: DBMS TABLE DBMS COLUMN DBMS SCHEMA DBMS DEPENDENT (Oracle, DB2, Sybase, etc) DBMS DATA MODEL “OPERATIONAL” DATA MODEL LAYER (Domain of Database Administrators (DBAs)) 17000+ SDEs BUSINESS APPLICATION SYSTEM “VIEW” DATA MODEL LAYER (Domain of Application System Managers (SMs and/or PMs) CONCEPTUAL VALUE DOMAIN Layer 0 DATA ELEMENT CONCEPT STRUCTURE DATA ELEMENT CONCEPT ISO 11179 BUSINESS CONTEXT INDEPENDENT DATA ELEMENT REPRESENTATION Functionally Independent Business Fact Semantic Templates (Globally Shared Data Elements) (Domain of DoD Data Administration) Layer 1 DDDS Source Layer 2 DDDS Source One gigantic semantic mess- redundancies & ambiguities DDDS Source Layer 3 DDDS Source Layer 4

  20. DATA ELEMENT BUSINESS INFORMATION APPLICATION SYSTEM VIEW COLUMN STRUCTURE TYPE VIEW VIEW COLUMN STRUCTURE METADATA REPOSITORY Data sharing occurs at the “operational and application” view layers. Made possible through the relationships between all layers represented by metadata in a repository that enables relating syntax, structure, and semantics from any layer to a common ISO 11179 standard representation. VIEW COLUMN ISO 11179 Specified Model VIEW COLUMN STRUCTURE PROCESS Implemented Model Operational DBMS Application View META MODEL ARCHITECTURE SUPPORTING ENTERPRISE WIDE SHARED DATA CONCEPT STRUCTURE TYPE CONCEPTUAL VALUE DOMAIN STRUCTURE CONCEPTUAL VALUE DOMAIN STRUCTURE TYPE CONCEPTUAL VALUE DOMAIN CONCEPT STRUCTURE CONCEPT VALUE DOMAIN STRUCTURE TYPE VALUE DOMAIN STRUCTURE DATA ELEMENT CONCEPT DATA ELEMENT CONCEPT STRUCTURE TYPE DATA ELEMENT CONCEPT STRUCTURE VALUE DOMAIN ISO 11179 BUSINESS CONTEXT INDEPENDENT DATA ELEMENT REPRESENTATION Functionally Independent Business Fact Semantic Templates (Globally Shared Data Elements) (Domain of DoD Data Administration) APPLICATION VIEWS OF DBMS TABLES & COLUMNS “VIEW” DATA MODEL (Domain of Application System Managers (SMs and/or PMs) FUNCTIONALLY DEPENDENT & TECHNOLOGY INDEPENDENT DATA MODEL TEMPLATES ATTRIBUTE  INHERITS DATA ELEMENT “SPECIFIED” DATA MODEL (DoD FDAd Domain) ENTITY ATTRIBUTE SUBJECT TECHNOLGY DEPENDENT & DBMS INDEPENDENT MODEL / SCHEMA COLUMN  INHERITS ATTRIBUTE “IMPLEMENTED” DATA MODEL) (Data Architects / Modelers Domain) COLUMN SCHEMA TABLE DBMS DEPENDENT & APPLICATION VIEW INDEPENDENT DBMS COLUMN (Oracle, DB2, etc) INHERITS  COLUMN “OPERATIONAL” DATA MODEL (Domain of Database Administrators (DBAs)) DBMS SCHEMA DBMS TABLE DBMS COLUMN

  21. Design Layers for a Business Information System Data Architecture CONCEPTUAL VALUE DOMAIN STRUCTURE CONCEPTUAL VALUE DOMAIN STRUCTURE TYPE CONCEPT STRUCTURE TYPE CONCEPT STRUCTURE CONCEPTUAL VALUE DOMAIN CONCEPT BUSINESS INFORMATION SYSTEM APPLICATION VIEW TABLE APPLICATION VIEW COLUMN VALUE DOMAIN STRUCTURE TYPE VALUE DOMAIN STRUCTURE DATA ELEMENT CONCEPT STRUCTURE TYPE VALUE DOMAIN DoD CORE DATA ELEMENT METADATA REPOSITORY ISO 11179 Model Layer FUNCTIONAL AREA / SUBJECT MATTER DEPENDENT DATA MODEL TEMPLATES “SPECIFIED” DATA MODEL LAYER (DoD FDAd Domain) Specified Model Layer DATA ELEMENT ENTITY ATTRIBUTE SUBJECT Implemented Model Layer Operational DBMS Layer COLUMN SCHEMA TABLE Application View Layer TECHNOLGY DEPENDENT (SQL, COBOL, ETC), FULLY ATTRIBUTED, LOGICAL DATA MODEL “IMPLEMENTED” DATA MODEL LAYER (Data Modelers Domain) DBMS TABLE DBMS COLUMN DBMS DEPENDENT (Oracle, DB2, Sybase, etc) DBMS DATA MODEL “OPERATIONAL” DATA MODEL LAYER (Domain of Database Administrators (DBAs)) DBMS SCHEMA BUSINESS APPLICATION SYSTEM “VIEW” DATA MODEL LAYER (Domain of Application System Managers (SMs and/or PMs) Layer 0 DATA ELEMENT CONCEPT STRUCTURE DATA ELEMENT CONCEPT ISO 11179 BUSINESS CONTEXT INDEPENDENT DATA ELEMENT REPRESENTATION Functionally Independent Business Fact Semantic Templates (Globally Shared Data Elements) (Domain of DoD Data Administration) Layer 1 Layer 2 Layer 3 Layer 4

  22. DATA ELEMENT BUSINESS INFORMATION APPLICATION SYSTEM VIEW COLUMN STRUCTURE TYPE VIEW VIEW COLUMN STRUCTURE METADATA REPOSITORY Data sharing occurs at the “operational and application” view layers. Made possible through the relationships between all layers represented by metadata in a repository that enables relating syntax, structure, and semantics from any layer to a common ISO 11179 standard representation. VIEW COLUMN ISO 11179 Specified Model VIEW COLUMN STRUCTURE PROCESS Implemented Model Operational DBMS Application View META MODEL ARCHITECTURE SUPPORTING ENTERPRISE WIDE SHARED DATA CONCEPT STRUCTURE TYPE CONCEPTUAL VALUE DOMAIN STRUCTURE CONCEPTUAL VALUE DOMAIN STRUCTURE TYPE CONCEPTUAL VALUE DOMAIN CONCEPT STRUCTURE CONCEPT VALUE DOMAIN STRUCTURE TYPE VALUE DOMAIN STRUCTURE DATA ELEMENT CONCEPT DATA ELEMENT CONCEPT STRUCTURE TYPE DATA ELEMENT CONCEPT STRUCTURE VALUE DOMAIN ISO 11179 BUSINESS CONTEXT INDEPENDENT DATA ELEMENT REPRESENTATION Functionally Independent Business Fact Semantic Templates (Globally Shared Data Elements) (Domain of DoD Data Administration) APPLICATION VIEWS OF DBMS TABLES & COLUMNS “VIEW” DATA MODEL (Domain of Application System Managers (SMs and/or PMs) FUNCTIONALLY DEPENDENT & TECHNOLOGY INDEPENDENT DATA MODEL TEMPLATES ATTRIBUTE  INHERITS DATA ELEMENT “SPECIFIED” DATA MODEL (DoD FDAd Domain) ENTITY ATTRIBUTE SUBJECT TECHNOLGY DEPENDENT & DBMS INDEPENDENT MODEL / SCHEMA COLUMN  INHERITS ATTRIBUTE “IMPLEMENTED” DATA MODEL) (Data Architects / Modelers Domain) COLUMN SCHEMA TABLE DBMS DEPENDENT & APPLICATION VIEW INDEPENDENT DBMS COLUMN (Oracle, DB2, etc) INHERITS  COLUMN “OPERATIONAL” DATA MODEL (Domain of Database Administrators (DBAs)) DBMS SCHEMA DBMS TABLE DBMS COLUMN

  23. METADATA REPOSITORY Defense Data Dictionary System (DoD Standardized Data Elements) 17000+ SDEs Supply Item Resource Quantity Supply Item Resource Quantity An Optimal Application of an ISO 11179 Based Data Element Architecture for Resolving Disparate Representations of Shared Enterprise Data Elements Business Application Information System (AIS) “View” Model Metadata Repository Architecture of Related Representations of DoD Enterprise Shared Data Elements in Support of Data and Information Sharing Vendor Dependent SQL DBMS “Operational” Model Army SAMS (AIS) “Oracle” DBMS Supply Item Resource Quantity ISO 11179 Context Inde pendent Data Element Representation Meta Model Technology Dependent “Implemented” Model Functional/Organizational Context Dependent “Specified” Model ANSI SQL Concepts Business Fact Semantic Template Name Supply Item Resource Quantity Data Element Concept Materiel Resource Army Logistics Management Physical Item Balance Supply Item Resource Quantity Conceptual Value Domain Data Element Supply Item Resource Quantity SQL Column Names Physical Measure View Column Names Attribute Names DBMS Column Names Quantity Supply Item Resource Quantity Navy Logistics Management Value Domain ANSI SQL Supply Item Resource Quantity Data Element Definition: Supply Item Resource Quantity The quantity of each type of Federal Supply System materiel item contained in an identifiable inventory of materiel objects. “Sybase” DBMS Navy UADPS (AIS) Additional Data Element Structural Metadata: Data type characteristics, local definition, enumerated values ( if specific ), etc.

  24. The “Optimal” Solution

  25. Example Logistics Application of an ISO 11179 Based Data Element Architecture for Relating Disparate Representations of Shared Enterprise Data Elements Business Application Information System (AIS) “View” Model Metadata Repository Architecture of Related Representations of DoD Enterprise Shared Data Elements in Support of Data and Information Sharing Vendor Dependent SQL DBMS “Operational” Model Supply Unit Quantity Army SAMS (AIS) Materiel Unit Inventory Quantity “Oracle” DBMS ISO 11179 Context Inde pendent Data Element Representation Meta Model Technology Dependent “Implemented” Model Functional/Organizational Context Dependent “Specified” Model ANSI SQL Concepts Business Fact Semantic Template Name Data Element Concept Materiel Resource Army Logistics Management Mat_Inv_Qty Materiel Inventory Quantity Physical Item Balance Conceptual Value Domain Data Element Supply Item Resource Quantity SQL Column Names Physical Measure View Column Names Attribute Names DBMS Column Names Materiel Item Inventory Quantity Quantity Mat_Itm_Inv_Qt Navy Logistics Management Value Domain Stocked Materiel Quantity ANSI SQL Ships Stores Quantity Data Element Definition: The quantity of each type of Federal Supply System materiel item contained in an identifiable inventory of materiel objects. CORE METADATA REPOSITORY “Sybase” DBMS Navy UADPS (AIS) ISO 11179 Model Specified Model Additional Data Element Structural Metadata: Implemented Model Operational DBMS Data type characteristics, local definition, enumerated values ( if specific ), etc. Application View

  26. Example Personnel Application of an ISO 11179 Based Data Element Architecture for Relating Disparate Representations of Shared Enterprise Data Elements Business Application Information System (AIS) “View” Model Metadata Repository Architecture of Related Representations of DoD Enterprise Shared Data Elements in Support of Data and Information Sharing Vendor Dependent SQL DBMS “Operational” Model Squad Member Rank Code Army (AIS) Unit Member Rank Code “Oracle” DBMS ISO 11179 Context Inde pendent Data Element Representation Meta Model Technology Dependent “Implemented” Model Functional/Organizational Context Dependent “Specified” Model ANSI SQL Concepts Business Fact Semantic Template Name Data Element Concept Human Resource Army Personnel Management Sold_Rnk_Cd Soldier Rank Code Personnel Classifi- cation Conceptual Value Domain Data Element Personnel Ranking Measure Person Grade Code SQL Column Names View Column Names Attribute Names DBMS Column Names Sailor Rating Code Grade Code Sail_Rat_Cde Navy Personnel Management Value Domain Crew Member Rating Code ANSI SQL Data Element Definition: Launch Team Member Rating Code The code that represents the level of authority and responsibility occupied by Person in a hierarchy of levels ranging from most superior to most subordinate in which each level is subordinate to levels above and superior to levels below. CORE METADATA REPOSITORY “Sybase” DBMS Navy (AIS) ISO 11179 Model Specified Model Implemented Model Operational DBMS Additional Data Element Structural Metadata: Application View Data type characteristics, etc.

  27. Part II: Implementing the Metadata Architecture For Enterprise-wide Data Sharing in a Legacy System Environment

  28. Table of Contents • A Realistic and Practical Approach to Achieve the Ideal Solution • How Do We Get to the Ideal? • Find Our Metadata • Perform Smart Meta-Data Mining • Find the Right Starting Layer • Reverse Engineer to Build the Upper Layers • Overall Forward Engineering Process • Process Statistics • Lessons Learned

  29. DATA ELEMENT BUSINESS INFORMATION APPLICATION SYSTEM VIEW COLUMN STRUCTURE TYPE VIEW VIEW COLUMN STRUCTURE METADATA REPOSITORY Data sharing occurs at the “operational and application” view layers. Made possible through the relationships between all layers represented by metadata in a repository that enables relating syntax, structure, and semantics from any layer to a common ISO 11179 standard representation. VIEW COLUMN ISO 11179 Specified Model VIEW COLUMN STRUCTURE PROCESS Implemented Model Operational DBMS Application View 1.0 META MODEL ARCHITECTURE SUPPORTING ENTERPRISE WIDE SHARED DATA CONCEPT STRUCTURE TYPE CONCEPTUAL VALUE DOMAIN STRUCTURE CONCEPTUAL VALUE DOMAIN STRUCTURE TYPE CONCEPTUAL VALUE DOMAIN CONCEPT STRUCTURE CONCEPT VALUE DOMAIN STRUCTURE TYPE VALUE DOMAIN STRUCTURE DATA ELEMENT CONCEPT DATA ELEMENT CONCEPT STRUCTURE TYPE DATA ELEMENT CONCEPT STRUCTURE VALUE DOMAIN ISO 11179 BUSINESS CONTEXT INDEPENDENT DATA ELEMENT REPRESENTATION Functionally Independent Business Fact Semantic Templates (Globally Shared Data Elements) (Domain of DoD Data Administration) APPLICATION VIEWS OF DBMS TABLES & COLUMNS “VIEW” DATA MODEL (Domain of Application System Managers (SMs and/or PMs) FUNCTIONALLY DEPENDENT & TECHNOLOGY INDEPENDENT DATA MODEL TEMPLATES ATTRIBUTE  INHERITS DATA ELEMENT “SPECIFIED” DATA MODEL (DoD FDAd Domain) ENTITY ATTRIBUTE SUBJECT TECHNOLGY DEPENDENT & DBMS INDEPENDENT MODEL / SCHEMA COLUMN  INHERITS ATTRIBUTE “IMPLEMENTED” DATA MODEL) (Data Architects / Modelers Domain) COLUMN SCHEMA TABLE DBMS DEPENDENT & APPLICATION VIEW INDEPENDENT DBMS COLUMN (Oracle, DB2, etc) INHERITS  COLUMN “OPERATIONAL” DATA MODEL (Domain of Database Administrators (DBAs)) DBMS SCHEMA DBMS TABLE DBMS COLUMN

  30. 1.1 Example Personnel Application of an ISO 11179 Based Data Element Architecture for Relating Disparate Representations of Shared Enterprise Data Elements Business Application Information System (AIS) “View” Model Metadata Repository Architecture of Related Representations of DoD Enterprise Shared Data Elements in Support of Data and Information Sharing Vendor Dependent SQL DBMS “Operational” Model Squad Member Rank Code Army (AIS) Unit Member Rank Code “Oracle” DBMS ISO 11179 Context Inde pendent Data Element Representation Meta Model Technology Dependent “Implemented” Model Functional/Organizational Context Dependent “Specified” Model ANSI SQL Concepts Business Fact Semantic Template Name Data Element Concept Human Resource Army Personnel Management Sold_Rnk_Cd Soldier Rank Code Personnel Classifi- cation Conceptual Value Domain Data Element Personnel Ranking Measure Person Grade Code SQL Column Names View Column Names Attribute Names DBMS Column Names Sailor Rating Code Grade Code Sail_Rat_Cde Navy Personnel Management Value Domain Crew Member Rating Code ANSI SQL Data Element Definition: Launch Team Member Rating Code The code that represents the level of authority and responsibility occupied by Person in a hierarchy of levels ranging from most superior to most subordinate in which each level is subordinate to levels above and superior to levels below. CORE METADATA REPOSITORY “Sybase” DBMS Navy (AIS) ISO 11179 Model Specified Model Implemented Model Operational DBMS Additional Data Element Structural Metadata: Application View Data type characteristics, etc.

  31. 2. How Do We Get to the Ideal? (or the least un-ideal) • Find our metadata • Perform smart metadata mining • Pick the right starting layer • Reverse engineer to build the upper layers • Forward engineer to build standard-data • based applications

  32. 3. Find Our Metadata • Existing schemas within running applications as • that’s the only place where data-truth resides • Extract Cobol FDs within running applications • for the same truth reason • Finally, research metadata libraries like ERwin models

  33. 3.1 Where We Started • DoD had 493 (Erwin) data models that were • developed in the 1990s. There were 5709 tables • and 16921 columns in these tables. • We did not inventory each DoD Agency, but the key • investigator (Hank Lavender) is very much aware of • what, where, and how much all the schemas overlapped. • This effort was to “prove the process”. We will soon • start real Enterprise-wide data sharing projects.

  34. 4. Perform Smart Meta-Data Mining • Pick backbone and rib-cage (HR, Finance, Inventory • Customer Management, Sales) Applications • Pick the most commonly used schemas across the • enterprise that support the backbone and rib-cage • applications • Pick the subset of schemas that have the most • commonly used tables • (note: commonly used is different from exactly the same as…) • Make Where-Used and Frequency-Used Matrices

  35. 4.1 Where Used & Frequency Matrices Basic Types and Populations IDM Data Model Counts Data Model Description Tables Columns Relationships C-03 Budgets & Currency 56 178 53 C3-12 Command & Control 28 276 65 ES-07 Environmental Hazards 41 464 46 ES-08 Environmental Projects 28 185 40 LG-06 Transportation Operations 19 91 26 LG-23 Materiel Documentation 36 272 51 LG-28 Materiel Characteristics 45 225 48 PR-22 Training & Instruction 20 135 23 PR-31 Person Characteristics 36 118 41 Totals 309 1944* 393 *542 Unique Data Element Concepts

  36. SDM IDM Schemas Subject Areas C-03 C3-12 ES-07 ES-08 LG-06 LG-23 LG-28 PR-22 PR-31 Environmental Management X X X Health Management X X X X Logistics Management X X X X Logistics Operations X X X X X Logistics Planning X X X Materiel Maintenance X X Materiel Management X X X X X X X Transportation Operations X X X Property Management X X X Personnel Management X X X X X X Management Administration X X X 4.1 (cont) Subject Areas Use Across IDM Schemas

  37. 4.1 (cont) Where Used & Frequency Matrices Frequency of Use Matrix IDM Schemas & Tables SDM Subject Area Entity C-03 C3-12 ES-07 ES-08 LG-06 LG-23 LG-28 PR-22 PR-31 Logistics Management Organization X X X X X X X Person X X X X X X Country X X X X X Location X X Task X X Facility X X Plan X X Guidance X X Geolocation X X X Personnel Management Logistics Operations Logistics Operations Management Administration Property Management Logistics Planning Environmental Management Property Management

  38. 5. Find the Right Starting Layer Data Modeling Layer Description Start Here ? Context independent business fact semantic templates NO, these are not database models and have no context Data Elements NO, as these are just templates and not database models Technology independent data model templates Specified Data Model OK- if you have “Erwin” like data models that can be researched, tabulated, and extracted via Excel or SQL DDL DBMS independent database data models and hosts for database object classes Implemented Data Model YES! This is the best as it matches the reality of operating databases and applications Operational Data Model DBMS dependent and Operating System specific Database application specific SQL views No, as this is too application-use specific, and not data model centric. View Data Model

  39. 6. Reverse Engineer to Build The Upper Layers • Import to appropriate layer • Promote to higher data modeling layer • Re-engineer the Specified Data Model layer • Analyze to discover the Data Elements • Build Data Element Model Metadata layer

  40. Importing SQL DDL 6.1 Import to Appropriate Layer IDM

  41. 6.1 Import to Appropriate Layer IDM Tables IDM

  42. 6.2 Promote to Higher Data Modeling Layer Promote IDM to SDM

  43. Key Difference Between Subject-Entity-Attribute vs Schema-Table-Column Model of a subject area. Intellectual boundaries, not data processing boundaries. Not a conceptual version of a logical database. It’s a subject based data model template. Define once, use many times, differently in IDM models. Subject-Entity-Attribute (SDM) Model of a database schema that may involve attributes from multiple entities in one table, or attributes of entities across multiple tables. Intended to be implemented within a DBMS as an operational database. Schema-Table-Column (IDM) Not related. This would then mean Transformational Relationship. Subject-Schema Not related. This would mean Transformational Relationship Entity-Table Yes, Related. This allows define once, use many times modeling. Attribute-Column 6.2 Key Promotion Issues

  44. 6.3 Re-engineer the Specified Data Model • Assign Entities to different Subjects • Reassign Entities to within Entities (sub-typing) • Reassign Attribute’s Semantics • Conform Attribute Names to Subject Area Scope • Reassign Attributes to different Entities • Reassign Attributes to different Data Elements SDM Reassign Entity to Subject

  45. 6.3 Re-engineering the Specified Data Model BASIC PROCESSES SDM Reassign Entity to Subject Assign Attribute Meta Category Values Reassign Attribute to Data Element Reassign Attribute to Entity

  46. 6.4 Reallocate Foreign Keys to Encapsulate Subject’s Entities SDM • For Each Subject Area: • Make a List of Entities • Make a Subject Area Based E-R Model Diagram • Delete Unnecessary Foreign Keys from Existing Entities • Make New Foreign Keys Where Needed • Export to E-R Diagrammer to Verify Result • Recycle if Necessary

  47. 6.4 (cont) Reallocate Foreign Keys to Encapsulate Subject’s Entities Validate/Create SDM Foreign Keys SDM

  48. 6.4 (cont) Reallocate Foreign Keys to Encapsulate Subject’s Entities Modify SDM Foreign Keys SDM

  49. 6.5 Discover the Data Element Promote SDM Attributes to Data Elements

  50. 6.6 Build Data Element Model Level Metadata