1. Employing an RDBMS to Integrate and Enhance the Usability of Land Record Data Dan Steen Steve Yoder AIMS, Johnson County, Kansas

5. Our Situation... 4 th Qtr 2000 Countys GIS operations solely NT based Increasing demand for integrated DB/Map Apps –Recently deployed a number of VB/MO apps Johnson County Land Records data resides on/in various servers/formats –IT had no plans to build an enterprise Land Records DB GIS industry moving toward integrated storage of spatial and attribute data in commercial DBMS software

6. Our Plan Move land record attribute data to DBMS –Before moving spatial data Bring together disparate land record data stores into a single database Use the new database as we develop additional integrated DB/Map apps Lay foundation for expanded DBMS use in AIMS operations and administration

7. Infrastructure Production Server –Compaq Proliant ML370, 2x866 Mhz, 896 MB RAM –OS: Windows 2000 Server, SP2 –Mirrored 18.2 GB Drives for OS, Log Files & Pagefile, 3 36.4 GB Drives in RAID5 for Data (72Gbs Usable space) Microsoft SQL Server 2000 –Service Pack 2

8. JOCOLand

9. Data pertaining to Land Records in Johnson County. JOCOLand is NOT a primary data store; rather, it is a warehouse of replicated data, derived data, and pointers to other data. JOCOLand data comes from a variety of primary data sources including OASIS, CAMA, miscellaneous Appraiser databases, Property Spatial Dataset (i.e., property coverages), as well as data from a number of municipalities and Public Works. Its value is that it brings together data from a variety of sources into a single, centralized, enterprise database.

10. Real Estate Properties/Parcels ownership, situs address, legal description, appraisal characteristics, appraised value Replicated from Mainframe OASIS and CAMA

11. Real Estate Properties/Parcels location (centroid & administrative districts), size Replicated from Property Coverages & Derived from numerous point-in-polys

12. Real Estate Properties/Parcels location (centroid & administrative districts), size Replicated from Property Coverages & Derived from numerous point-in-polys

13. Transfer Orders type (e.g., split, plat), properties/parcels involved, spatial before and after Replicated from INFO files used in Property Coverage Maintenance process

14. Transfer Orders type (e.g., split, plat), properties/parcels involved, spatial before and after Replicated from INFO files used in Property Coverage Maintenance process pointers to archived property coverages

15. Plats and Subdivisions name, year platted, book/page Replicated from Mainframe OASIS & Derived through code

16. Plats and Subdivisions name, year platted, book/page pointer to scanned plat image Replicated from Mainframe OASIS & Derived through code

17. Appraisal Data Value History, BOTA, Front Elevation, Certificate of Value, Sales, Permits Replicated/Massaged from Mainframe OASIS & Appraiser Access Database

18. Appraisal Data Value History, BOTA, Front Elevation, Certificate of Value, Sales, Permits Replicated/Massaged from Mainframe OASIS & Appraiser Access Database pointers to images

19. Situs Addresses including the atomized pieces of an address and its location Replicated/Massaged from Mainframe OASIS, Public Works (INFO), Municipalities (DBF), etc.

20. Code Definitions look-up tables that translate various codes into a text description

21. Under Construction Condominiums (vertical parcels & common areas), Leased Land, Mineral Rights & Underground Warehouses

22. How is data in JOCOLand Refreshed? Most tables are updated each night Typically some pre-processing, for example –INFO.dbf –merge tiled data –point-in-polygon Scheduled Data Transformation Services (DTS Packages)

28. Development of Land Records Application Promote data sharing – Eliminate redundancy Maximize existing data resources – Reduces cost & eliminate redundancy Utilize existing infrastructure and hardware – Reduces cost Minimize specialized development – Administration & support more manageable Make application accessible – 24x7 from anywhere

29. The JCLR Application JCLR – Johnson County Land Records SQL Server 2000 driven application One example of a web interface into DBMS Internet-based land records information access Incorporates tabular and spatial data JCLR and IMS tightly integrated but independent of each other Ties data from AIMS, OASIS, CAMA, Appraiser, Register of Deeds, Planning/Codes, …

30. Goal of JCLR

31. JCLR & IMS Property Id Situs Address Owner Address Owner Names Mail Names Parcel Spatial History Zip Code Legal Description Planimetric Features Spatial Intersections Spatial Buffering Appr. Characteristics Year Built Tax Value Sales Value Zoning Landuse PLSS / Map Number Taxing Unit Neighborhood Unit Comparables Plotting Hardcopy Map Production Pictures Sales Questionnaires Tax Appeal Documents Plat Subdivision Names Subdivision Scans Tax Information Parcel History (splits, etc) Floorplans Scanned Documents

32. Technical Architecture JCLR – Intranet Application –Active Server Page Application –VBScript (some JavaScript) –SQL Server 2000 Internet Map Server (IMS) – Internet App. –MapObjects IMS –Visual Basic –SQL Server 2000 –Shapefile data

33. Application distributed between many servers –Web Server –Database Server –File Server –Application Server Technical Architecture

34. DBMS Advantages Data access very efficient Rapid development of applications High availability Diverse accessibility – Non-proprietary data formats More data sharing – Centralized source Standardization across enterprise Table driven code – updates get made transparently

44. Table driven code - updates get made transparently

45. Unanticipated Outcomes Easier to examine data quality Data being used in new & innovative ways Developing a better understanding of the data An understanding of how efficient set processing is Turf issues with IT Department

46. Easier to examine data quality - Example: Land Use Code

47. Easier to examine data quality - Example: Voting Precinct

48. Data being used in new & innovative ways - Example: Parcels with Transfer Order Activity

49. Developing a better understanding of the data - Example: Property Change Log compare

50. Developing a better understanding of the data - Example: Property Change Log compare PropertyChangeLog (detail)

51. Developing a better understanding of the data - Example: Property Change Log compare PropertyChangeLog (summary)

52. An understanding of how efficient set processing is In contrast to cursor processing –Deal with one record at a time set processing –Deal with groups of records –Huge performance gain

53. Turf Issues with IT Department The GIS Department is operating outside the scope of its mission. As they developed the database and the applications, the GIS Department should have consulted with IT more.

54. The Future of JOCOLand... Implement Situs Address and PropIDRelate tables Incorporate additional land record data stores Include historical as well as in-progress data Integrate better with JOCOGeog (AIMS spatial data accessible via SDE)

55. Economic Data Census Data AIMS Administration –Log of AIMS Map & Data Requests –Accounts Receivable, Accounts Payable –Log of IMS Hits –Customers/Contacts –Data License Agreements AIMS Application Definition Beyond Land Records...