This dataset contains 2017 registered Condominiums by county in the State of Florida. The layer was derived from the Florida Department of Business & Professional Regulation's condominium database. The database consists of approved, acknowledged, and recorded condominium projects and their managing entities. Terminated, rejected, or withdrawn projects are not included. This data is meant to be used for planning purposes only and is not intended to represent a 100% inventory of condominiums in Florida. Please note that this dataset contains a high number of features with coincident spatial locations. Many condominiums were broken up into specific buildings or units within a community and were given the same address information. As a result, these points were geocoded on top of each other. Keep this data coincidence in mind when using this layer. This layer is an update to the GC_HOA_JAN11 layer.
The data was created to serve as base information for use in GIS for a variety of planning and analytical purposes.
--------------------------------------------------------------------- The Florida Department of Business & Professional Regulation oversee licensing and regulation of a wide range of commercial activities in the state of Florida pursuant to Chapter 20.165, Florida Statutes. ******************************************************************************** Please Note: The following point data represents only Geocoded features, these points HAVE NOT been validated via QAQC methods such as aerials or Google Street View. ******************************************************************************** Please Note: Duplicate address points may exist where more than one condominium building or unit occurs. ******************************************************************************** What is Geocoding? Geocoding is term used to describe the act of address matching. Geocoding is the process of finding a geographic location (x, y point) for an address (such as street number and name, city, state, and ZIP Code) on a map. Geocoding is based off the typical address scheme for the US, in which one side of the street contains even house numbers while the other side of the street contains odd house numbers. The geocoding process uses an algorithm to find the geographic location of addresses. First, a street segment is identified using the zip code and street name. Next, the geographic location of the address is matched using the building number to determine how far down the street and on which side of the street the building is located. Geocoding Accuracy The locational accuracy of geocoded addresses may vary from urban to rural areas due to the algorithm used to generate the geographic locations of addresses. The algorithm assumes that the size of parcels are equivalent along a road route. This assumption tends to be more consistent in urban areas, where the size of parcels vary less than in rural areas. Consequently, the results of geocoded addresses in urban areas are usually more reliable than those in rural areas. For example, the locational accuracy of rural addresses can be slightly off because some parcels along a rural route may be 15 acres while others may be 2.5 acres, but the geocoding algorithm assumes that the addresses are distributed evenly along the route. ---------------------------------------------------------------------
publication date
--------------------------------------------------------------------- Under Chapter 119, Florida Statutes, the Department of Business and Professional Regulation (DBPR) is required to make available for inspection and copying any public record regardless of physical format, which is not otherwise exempted from public access by general law. To fulfill this obligation, the DBPR provides copies of electronic records to the public through free download. DBPR is only required to provide data in the format in which it is maintained and, as a result, does not provide paper copies of this information. In addition, the DBPR is not required to reformat its records to meet a requestor's particular needs. Section 119.01(2)(b), F.S., requires only that the agency provide electronic data in some common format such as, but not limited to, the American Standard Code for Information Interchange (ASCII) text format. As, the download files provided by DBPR are formatted as ASCII text, quote/comma delimited. Due to this, it is important that requestors know the following information before downloading a file: DBPR does not offer technical support during or after the download process. If you require assistance, please refer to your computer manuals or contact your Corporate Help Desk or Internet Service Provider. File sizes may be larger than the space available on your computer. If that is the case, free up additional space before attempting the download. Some features such as tabs, font selection, and graphics may be lost when converting a file to ASCII text. The department is not responsible for damages sustained to existing user data, software and/or hardware from data obtained through the download process. Although data is refreshed weekly, system maintenance may delay the updating of files. To determine the timeliness of the data, please refer to the date posted. For up-to-the-minute license verification, please call our Customer Contact Center at 850.487.1395 or access the DBPR's license search feature at https://www.myfloridalicense.com/wl11.asp. ---------------------------------------------------------------------
131 Architecture PO Box 115706
ww.fgdl.org
Florida Department of Business & Professional Regulation
GeoPlan relied on the integrity of the attribute information within the original data.
This data is provided 'as is'. GeoPlan relied on the integrity of the original data layer's topology
This data is provided 'as is' by GeoPlan and is complete to our knowledge.
This data is provided 'as is' and its horizontal positional accuracy has not been verified by GeoPlan
This data is provided 'as is' and its vertical positional accuracy has not been verified by GeoPlan
Spatial and Attribute Information
---------------------------------------------------------------------------------- GeoPlan Center Process Steps: Condominium information was obtained from the Florida Department of Business & Professional Regulation via their condominiums, timeshares, and mobile homes public records website found here: http://www.myfloridalicense.com/DBPR/condos-timeshares-mobile-homes/public-records/#1506105905579-f9864587-f7ca. Five separate condominium .csv files were downloaded representing different regions of the state. The tables were converted to geodatabase tables and merged together. The compiled geodatabase table was geocoded using Streetmap Premium 2016 R2 on ArcGIS Pro 1.3 and was converted into a shapefile. The shapefile was projected in FGDL Albers HPGN map projection. After geocoding, the following steps were taken: - The original dataset contained 27274 records. Eleven of these records were not geocoded and were removed. - The other records were geocoded using eight different address locators. Five of the eight locators, AdminPlaces, Gazetteer POI 1, Gazetteer POI 2, Postal, and Postal Ext, geocoded a total 3512 records. Of the remaining 23751 records, 10807 were geocoded by the PointAddress locator, 9222 by the StreetAddress locator, and 3722 by the StreetName locator. The final dataset contains 23751 records. - NOTES filed added to provide information about the geocoding. It first describes the geocoding program, them the address locator used, then the match score, then the match address that placed the record in space. - LAT_DD, LONG_DD, MGRS, and GOOGLEMAP fields added and calculated. - DESCRIPT field added based on NAME. - FLAG field added and updated if point locations were verified. - UPDATE_DAY field added based on when the data was updated. - FGDLAQDATE added based on the date GeoPlan acquired the data from the source. - Fields were organized and optimized to fit GeoPlan standards. It is important to note that in the geocoding process it became clear that the condominium dataset contained multiple records with coincident locations. This is because individual buildings or units in a community were not given unique address locations. This dataset is similar to the prior layer, GC_HOA_JAN11.
Dataset copied.
Internal feature number.
ESRI
Feature geometry.
Esri
Condominium project number.
DBPR
Condominium file number.
DBPR
Name of the condominium.
DBPR
Address of the condominium facility.
DBPR
City of the condominium facility.
DBPR
Zipcode of the condominium facility.
DBPR
County of the condominium facility.
DBPR
The type of facility.
GeoPlan
The responsible organization for management and operation of a facility (county, federal, municipal, private, state, wmd, etc).
GeoPlan
Classification of the operating entity (private, public, quasi-public).
GeoPlan
The number of units associated with the condominium (based on the UNITS field from DBPR).
DBPR
Condominium's primary status.
DBPR
Condominium's secondary status.
DBPR
Condominium's recorded date.
DBPR
Condominium's managing entity number.
DBPR
Condominium's managing entity name.
DBPR
Condominium's managing entity route.
DBPR
Condominium's managing entity street.
DBPR
Condominium's managing entity city.
DBPR
Condominium's managing entity zipcode.
DBPR
Feature spatial source.
GeoPlan
Feature data/tabular source.
GeoPlan
Field compiling information about the geocoding process: the program used, the address locator, the score, and the matching address.
GeoPlan
Latitude in decimal degrees.
GeoPlan
Longitude in decimal degrees.
GeoPlan
Military Grid Reference System (MGRS) Coordinate of the Facility. The MGRS is the geocoordinate standard used by NATO militaries for locating points on the earth. The MGRS provides a means to represent any location on the surface of the Earth using an alphanumeric string. Hierarchical references are based on the Universal Transverse Mercator (UTM) coordinate system. The MGRS is used for the entire earth. http://mgrs-data.org/
GeoPlan
Webpage hyperlink to location in Google Maps.
GeoPlan
Field added based on NAME.
GeoPlan
Type of update that occurred
GeoPlan
Not Verified
Verified, in most cases this verification was based on ESRI/Google Imagery, Google Street View, and Parcel Data. The exact facility boundaries are not verified and in many cases only based on parcel boundaries.
The date the data was last updated.
GeoPlan
The date GeoPlan acquired the data from the source.
GeoPlan
Unique ID added by GeoPlan
GeoPlan
431 Architecture PO Box 115706
The Florida Geographic Data Library is a collection of Geospatial Data compiled by the University of Florida GeoPlan Center with support from the Florida Department of Transportation. GIS data available in FGDL is collected from various state, federal, and other agencies (data sources) who are data stewards, producers, or publishers. The data available in FGDL may not be the most current version of the data offered by the data source. University of Florida GeoPlan Center makes no guarantees about the currentness of the data and suggests that data users check with the data source to see if more recent versions of the data exist. Furthermore, the GIS data available in the FGDL are provided 'as is'. The University of Florida GeoPlan Center makes no warranties, guaranties or representations as to the truth, accuracy or completeness of the data provided by the data sources. The University of Florida GeoPlan Center makes no representations or warranties about the quality or suitability of the materials, either expressly or implied, including but not limited to any implied warranties of merchantability, fitness for a particular purpose, or non-infringement. The University of Florida GeoPlan Center shall not be liable for any damages suffered as a result of using, modifying, contributing or distributing the materials. A note about data scale: Scale is an important factor in data usage. Certain scale datasets are not suitable for some project, analysis, or modeling purposes. Please be sure you are using the best available data. 1:24000 scale datasets are recommended for projects that are at the county level. 1:24000 data should NOT be used for high accuracy base mapping such as property parcel boundaries. 1:100000 scale datasets are recommended for projects that are at the multi-county or regional level. 1:125000 scale datasets are recommended for projects that are at the regional or state level or larger. Vector datasets with no defined scale or accuracy should be considered suspect. Make sure you are familiar with your data before using it for projects or analysis. Every effort has been made to supply the user with data documentation. For additional information, see the References section and the Data Source Contact section of this documentation. For more information regarding scale and accuracy, see our webpage at: http://geoplan.ufl.edu/education.html
131 Architecture PO Box 115706