Washington State Parcel Data User Survey Results

1. Washington State Parcel Data User Survey Results Luke Rogers Rural Technology Initiative College of Forest Resources University of Washington Seattle, WA

2. Intent • Qualify and understand the need for parcel data • Quantify current efforts by state, private and federal organizations • Assess the interest in a statewide parcel database • Build interest in a statewide parcel database effort

3. Methodology • Construct survey to collect quantifiable data and anecdotal observations about parcel data use • Focus on state and federal agency use but also solicit local government and private organizations where possible • Sent e-mail solicitations to UW-GIS, WAGIC, FMG and CPS-GIS lists

4. Respondents • 43 responses representing: • 12 state agencies • 5 federal agencies • 8 local agencies • 8 private

5. Response Types

6. What software is most used?

7. Reasons for parcel data use • Most respondents had multiple reasons for collecting parcel data • Land ownership is clearly the most motivating reason for collecting parcel data

8. Public agency rationale • If you represent a public agency, is there a law or mandate that provides the rationale for parcel collection or use?

9. Comments about reasons why organizations collect parcel data • Increased accuracy • Decreased time associated with projects or ongoing initiatives • Corresponding decreased cost

10. How is parcel data collected?

11. For what geographic extent is parcel data needed? • Geographic extent varies widely among respondents • Many have project specific needs which range from sub-county to the entire state

12. License agreements & Data sharing agreements • State and local agencies tend to have a low percentage of license agreements • Private companies tend to have a high percentage of license agreements • Federal agencies have almost no license agreements or are not aware if they do • Very few entities have data sharing agreements. The disparity among users may suggest proactive behavior.

13. How many counties do people have data for? • Again responses vary widely having to do mainly with project specific work vs. ongoing initiatives • Some have attribute data only and others have linework only

14. How many prohibit the sharing or re-distribution of parcel data? • No clear trend or differential between public/private.

15. In what geographic data formats do you receive data?

16. How often does your organization collect parcel data?

17. Comments about collecting parcel and assessor data • Needs tend to be project specific although there are a few ongoing initiatives • Many users unsure about license agreements • Inconvenience of collecting data causes some to utilize outdated information • Appears to be a general perception of difficulty or hassle associated with acquiring and preparing parcel data

18. Is parcel feature geometry important to your organization? • Other: • Tax assessment • Compliance • Surveys • property lines • road planning • evaluation of forest fire protection assessment • identifying land owners at specified points • lease rights

19. Which assessor attributes are important?

20. Other important assessor attributes • mobile home, utility types, septic type, number of housing units, year built, bedrooms, number of floors, structure type • sales history, sale price, land and building values from previous years • forest fire protection assessment, fire district number, forest patrol/protection acres • building permit information if available, such as: permit ID, permit type, permit issue date, permit completion date, issuing authority • vacant/undeveloped status, boundary line adjustments, legal descriptions, plat info, taxing jurisdictions, township-range-sect-qtrsect, document numbers, water well number, special restrictions on property, land type, site city (legal city), tax account numbers

21. How is parcel and assessor data shared? • Other ways data is shared • Librarian • Email • FTP • CD/DVD • SQL Server

22. Are derivative products created from parcel data?

23. Examples of derivative products • impervious surfaces, land use, risk models and assessments, planning priorities, build out scenarios, developments, population estimates, housing density • conservation, suspected septic systems, habitat improvement opportunities • real estate classification/prospects, economic development • annexations, forestlands, crime analyses, election maps, fire risk • normalized statewide parcel database

24. Are derivative products publicly available?

25. What prohibits organizations from sharing products with counties? • Other: network security, incomplete products, no mechanism to share/distribute, restrictive license agreements, confidentiality, staff resources, business advantage

26. Comments about the way parcel data is used or shared • Project specific data rarely shared due to privacy/completeness/interest • Map products may be shared but the underlying data is not • General suggestions that sharing is good and should be encouraged but time/money, privacy and liability are concerns

27. Cost estimates

28. Value of parcel and assessor data to organizations • Agencies tasked with legislative or legal mandates view the data as critical and many state it would not be possible to do their jobs without it. • General perception of efficiency and improved accuracy • “The associated value is intangible in that it is both hard to value and invaluable.“

29. Assuming it met your needs and was available for your use, what dollar value would you place on an integrated, normalized statewide parcel database with a limited set of assessor attributes?

30. If an integrated database was available for your use, how often would updates be desired?

31. Any additional comments about the costs of parcel data collection? • Many organizations have no funds to acquire or manage parcel data • Many organizations acquire data infrequently due to costs and hassle. Would get updates more often if it was convenient. • Consistency among counties desired

32. Additional comments • Concern that a statewide database would be large • Desire to be able to acquire regions or sub-county areas • Majority of respondents see value in statewide database • Some confusion with cost data expressed

33. Next steps • Summarizing survey results into a brief document • Constructing a survey of county data producers • Drafting possible data standard • Drafting a catch-all pass-thru license agreement