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Mayo Clinic's Information Architecture: A Meta-data Repository Implementation April 19, 2000 Minnesota DAMA Chapter Mayo Clinic's Information Architecture: A Meta-data Repository Implementation April 19, 2000 Minnesota DAMA Chapter Sonja Ziegler - Data Administrator Mayo Foundation, Rochester, Minnesota USA Copyright, 2000 © Mayo Foundation

Agenda • • • Background Overview The Vision The Scope The Project The Future Agenda • • • Background Overview The Vision The Scope The Project The Future

Background • Began the search for a comprehensive data model repository in 1995 • Background • Began the search for a comprehensive data model repository in 1995 • Purchased Rochade in 1996 • Training and familiarization throughout 1996 • Established steering committee in late 1996 • Throughout 1996 -1998 a variety of projects were undertaken to address varying needs

Lessons Learned • Identification of a specific business need that requires attention is crucial Lessons Learned • Identification of a specific business need that requires attention is crucial • The scope of the implementation efforts must be tightly controlled • An appropriately staffed repository team is needed for implementation and coordination • A committed user/proponent must be engaged in the project

The Vision Information Architecture • Data Architecture Documentation of all pertinent information about an The Vision Information Architecture • Data Architecture Documentation of all pertinent information about an organization’s data and its interactions • System Architecture The documentation of applications areas and their relations to business areas, information systems, vendors and IT personnel • Business Rules The documentation of business related knowledge that defines the rules of behavior to support the business’ operating procedures using business vernacular • Impact Analysis The ability of developers to gauge the impact that a change to some architectural element will have upon its surrounding elements

The Scope • The Mayo Data Architecture - our first step to a complete The Scope • The Mayo Data Architecture - our first step to a complete Information Architecture and we had a committed user base! • A top-down approach was not feasible because of current company culture • With a diverse multi-platform environment, just documenting what’s there is a vast improvement • Recognizing the difference between the efforts that can be automated by the repository and those that can’t

The Data Architecture Project • • • The Team The RIMs (Repository Information Models) The Data Architecture Project • • • The Team The RIMs (Repository Information Models) The User Interface The Infrastructure Components Mayo’s Problem Space 1. 2. 3. 4. Summarization The Data Population Our Goal

The Team • One FTE for Project Coordination/Management • One FTE for Database and The Team • One FTE for Project Coordination/Management • One FTE for Database and System Administration • One FTE (at least) for Application Development Plus a group of individuals to act as users. - FTE (full time employee)

Mayo Data Conceptual Level RIM DA/Abbreviation DA/Subject. Area DA/Synonym DA/Attribute. Category DA/Relationship DA/Entity DA/Attribute Mayo Data Conceptual Level RIM DA/Abbreviation DA/Subject. Area DA/Synonym DA/Attribute. Category DA/Relationship DA/Entity DA/Attribute DA/Prefer. Representation DA/Relationship. MAP-Rule DA/Entity. MAP Rule DA/Attribute. MAP-Rule

Mayo Data Logical Level RIM DA/Subject. Area DA/Relationship DA/Entity DA/Attribute DA/Relationship. MAP-Rule DA/Entity. MAP Mayo Data Logical Level RIM DA/Subject. Area DA/Relationship DA/Entity DA/Attribute DA/Relationship. MAP-Rule DA/Entity. MAP Rule DA/Attribute- XREF/Data. Model XREF/Relationship XREF/Entity XREF/Attribute XREF/Data. Schema XREF/Reference XREF/Data. Structure XREF/Field PWRDES/ CDM-Model PWRDES / Relationship PWRDES /Entity MAP-Rule PWRDES /Attribute

Mayo Data Physical Level RIM PWRDES/ CDM-Model PWRDES / Relationship PWRDES /Entity XREF/Data. Model Mayo Data Physical Level RIM PWRDES/ CDM-Model PWRDES / Relationship PWRDES /Entity XREF/Data. Model XREF/Relationship XREF/Data. Schema XREF/Reference SYB/Database SYB/Table PWRDES /Attribute XREF/Entity XREF/Attribute XREF/Data. Structure SYB/Column NSSQL/Table XREF/Field NSSQL/Column

Mayo Application RIM DA/Subject. Area DA/Relationship. MAP-Rule XREF/Relationship DA/Entity. MAP Rule XREF/Entity XREF/Reference XREF/Data. Mayo Application RIM DA/Subject. Area DA/Relationship. MAP-Rule XREF/Relationship DA/Entity. MAP Rule XREF/Entity XREF/Reference XREF/Data. Structure XREF/Data. Model XREF/Data. Schema DA/Attribute Appl/Attribute. MAP-Rule DA/Interface. Attribute Appl/Message XREF/Attribute Appl/Interface XREF/Field Appl/CRUDMAP-Rule Appl/Application

The User Interface & Infrastructure Components Data Impor tation BUSES AND SCANNERS FROM VIASOFT™ The User Interface & Infrastructure Components Data Impor tation BUSES AND SCANNERS FROM VIASOFT™ • Sybase™ Catalogs • Power. Designer™ Models • DB 2® Catalogs • COOL: Gen™ • MVS JCL • COBOL Programs • COBOL Data Libraries • Assembler Programs DEVELOPED SCANNERS • Enscribe • FOCUS® • Non. Stop™ SQL CSV IMPORT UTILITY • Microsoft® Access Data Rochade™ USER INTERFACE • VIASOFT™ Auto. Pilot • MDX-Manager Maint enanc e MAINTENANCE • Application • Data Architecture • Cross Reference Query & Repor ting METAQUEST™ QUERY/ REPORTING MODULES • Easy (EZ) • Dual Display (DD) • Extended (EX) • Power (PW) • Administration Tool

Meta. Quest™ Cross Reference Update Meta. Quest™ Cross Reference Update

Meta. Quest™ Query/ EZ-Query Meta. Quest™ Query/ EZ-Query

Meta. Quest™ Report Display Meta. Quest™ Report Display

Meta. Quest™ Query/ DD-Query Meta. Quest™ Query/ DD-Query

Problem Summarization • Mayo has chosen to follow a philosophy of selecting many best-of-breed Problem Summarization • Mayo has chosen to follow a philosophy of selecting many best-of-breed applications and then interfacing between them. • Their relative data models were not designed from an overriding Enterprise Architecture (a bottom-up approach). • As a result, we have data concepts represented differently and named in many different ways throughout our information architecture. ISSUES: • the need to understand our diverse data concepts • the need to integrate our applications

The Data • MICS (Mayo Integrated Clinical Systems) Data Architecture Project undertaken by Data The Data • MICS (Mayo Integrated Clinical Systems) Data Architecture Project undertaken by Data Administration in cooperation with the application development teams • The Data Architecture Model (DAM), the Application Logical Models (ALMs), and the database catalog information

Population of the Repository • • Data entry by summer student personnel Real work Population of the Repository • • Data entry by summer student personnel Real work here, no silver bullets Commitment from management for project Identified personnel from Data Administration and development projects • Ongoing processes established to maintain integrity of repository contents

Mayo’s Goal To have information at hand that will facilitate the understanding needed for: Mayo’s Goal To have information at hand that will facilitate the understanding needed for: • creating efficient application interfaces • effectively designing new databases • redesigning existing databases.

Now & Our Future • Continued commitment from Data Administration to populate the Data Now & Our Future • Continued commitment from Data Administration to populate the Data Architecture • Benefits are already being seen, which turns into good advertising for further IS involvement • Prioritize and keep the scope under control of the varying requests for implementations of the repository (Mayo Rochade Steering Committee)

Questions Questions

Contact Information Sonja Ziegler - ziegler. sonja@mayo. edu Mayo Foundation 200 1 st Street Contact Information Sonja Ziegler - ziegler. sonja@mayo. edu Mayo Foundation 200 1 st Street SW – Massey Studio Rochester, MN 55905