1. MetroGIS Regional Parcel Dataset An Overview

2. Areal Coverage 7 Counties – Anoka, Carver, Dakota, Hennepin, Ramsey, Scott and Washington Area : 6,924 km 2 Polygon: one record for each real estate/tax parcel Point: provides information where multiple tax parcels are represented by a single polygon (e.g., condominiums) Polygon counts: 962,653 Point counts: 1,061,182 http://www.datafinder.org/metadata/metrogis_regional_parcels.htm

3. Temporal Coverage 2002 – 2006 polygon shapefiles for 7 counties YearAnokaCarverDakotaHennepinRamseyScottWashington 2002116,908127,846349,662148,19645,79489,491 2003119,51631,906129,463352,024148,19647,407 2004124,04232,910130,989353,759148,26649,95893,794 2005125,85235,197134,302354,778148,72452,98996,303 2006129,39237,021135,586358,064148,96754,74197,922 Temporal change in the number of parcels by County, 2002 - 2006

4. Attributes 61 attributes/fields 8 numeric fields: polygon acreage, deeded acreage, estimated market value (EMV) of land, EMV-building, EMV-total, tax capacity, total tax, special assessments 3 date fields (last sale date, Ag. Preserve enrolled and expiration) Year built? Given – numeric field but should be a date field All other fields are text/string http://www.datafinder.org/metadata/MetroGIS_Regional_Parcels_Attributes.pdf

5. Attribute Completeness Assessment (Updated April, 2007) The selected attributes are present for at least 3 counties and above 90% of completeness report AttributeTypeAnokaCarverDakotaHennepinRamseyScottWashington Unique County ID TextYYYYYYY Unique Parcel ID TextYYYYYYY City (Actual) TextYYYYYYY City (Mailing) TextYYY Polygon Acreage NumYYYYYY Use-Type1TextYYYYYYY Multiple Use Type TextYYY Owner Name TextYYYYYY

6. Attribute Completeness Assessment (Updated April, 2007) The selected attributes are present for at least 3 counties and above 90% of completeness report AttributeTypeAnokaCarverDakotaHennepinRamseyScottWashington Owner Address TextYYYYY Tax Payer Name TextYYYY Tax Payer Address TextYYYY Homestead Status TextYYYYYYY EMV landNumYYYYYYY EMV - TotalNumYYYYYYY Tax Capacity NumYYYY Total TaxNumYYYY

7. Attribute Completeness Assessment (Updated April, 2007) The selected attributes are present for at least 3 counties and above 90% of completeness report AttributeTypeAnokaCarverDakotaHennepinRamseyScottWashington Tax Exempt Status TextYYYYY School Districts TextYYYYYYY Watershed District TextYYYYYYY Green Acres TextYYYY Agricultural Preserve TextYYY Parcel Polygon to Point and PIN Rel NumYYYY http://www.datafinder.org/metadata/MetroGIS_Regional_Parcels_Attributes.pdf

8. Examples of Incomplete Attribute Two fields indicate multiple uses for parcels, both are not used by all counties and are incomplete –Multiple Uses -- > 90% for Carver, Dakota, Ramsey; minimal or no data for rest –Use Type 2 -- < 2% complete for all counties EMV – Buildings –> 90% complete for Ramsey & Hennepin –74% - 86% for others

9. Examples of Incomplete Attributes 10 fields indicate characteristics of structures on parcels –Most of these are <90% complete and have values for only two or three counties –Only one (year built) has values for all counties Sale dates and values –<64% complete for all counties –Dates covered vary (e.g., Hennepin: 1970- 12/06, Carver: 1982-12/06, Anoka 2000- 12/06)

10. Attri- bute AnokaCarverDakotaHen- nepin RamseyScottWashing- ton Dwell -ing Type 65 residential and non- residential categories based on use Not used67 residential and non- residential categories based on use Not used 16 residential categories based mainly on # of units Not used Hous- ing Style 120 residential and non- residential categories 15 residential categories based on architectur al style 8 single- family residential categories related to # of stories Not used 17 residential categories based on architectual style 19 residential categories based on construction material, # of stories, or architectural style 26 residential categories based on construction material, use, and # of stories Data Quality and Consistency Many counties use different classification schemes for text variables (e.g., Use Type 1, Dwelling Type, Home Style, Heating, Cooling)

11. Inconsistency in classification schemes complicates multi-county analyses Additionally, inaccuracies may exist in field completion that further complicate analyses Data Quality and Consistency