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Employing an RDBMS to Integrate and Enhance the Usability of Land Record Data

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

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Employing an RDBMS to Integrate and Enhance the Usability of Land Record Data

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

  2. Employing an RDBMSto Integrateand Enhance the Usability ofLand Record Data Dan Steen Steve Yoder AIMS, Johnson County, Kansas

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

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

  5. Our Situation ... 4th Qtr 2000 • County’s 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 (72Gb’s 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. Replicated from Mainframe OASIS and CAMA Real Estate Properties/Parcels ownership, situs address, legal description, appraisal characteristics, appraised value

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

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

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

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

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

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

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

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

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

  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”)

  23. How is JOCOLand being used?

  24. Development of LandRecords 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

  25. 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, …

  26. Goal of JCLR

  27. JCLR & IMS • 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 • Property Id • Situs Address • Owner Address • Owner Names • Mail Names • Parcel Spatial History • Zip Code • Legal Description • Planimetric Features • Spatial Intersections • Spatial Buffering

  28. 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

  29. Technical Architecture • Application distributed between many servers • Web Server • Database Server • File Server • Application Server

  30. 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

  31. Table driven code • - updates get made transparently

  32. 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

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

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

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

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

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

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