TITLE: GOVERNMENT BUILDINGS
Geodataset Name: GC_GOVBUILD Geodataset Type: SHAPEFILE Geodataset Feature: POINTGENERAL DESCRIPTION:
This dataset contains 2004 Government Building Information for the State of Florida. It is a combination of General Government, General Government Administration, County Government, Federal Government, Local Government, State Government, Government Administration General, and Motor Vehicle Licensing & Drivers Licenses Building addresses from the Yellow Pages online. Also included is 2004 United States Post Office Facility Information for the State of Florida. It is a set of Post Office addresses from the Yellow Pages online and the Super Pages online.This dataset contains fields denoting the physical address, and contact information for government buildings located in Florida. |
DATA SOURCE(S): Yellow Pages Online / Super Pages Online SCALE OF ORIGINAL SOURCE MAPS: N/A DATE OF AUTOMATION OF SOURCE: 2004 GEODATASET EXTENT: State of Florida
FEATURE ATTRIBUTE TABLES:
Datafile Name: GC_GOVBUILD.DBF
ITEM NAME | WIDTH | TYPE | N. DECIMAL DEGREES |
FID
|
4 | OID | --- |
Shape
|
0 | Geometry | --- |
Status
|
1 | String | --- |
Score
|
4 | Number | --- |
Side
|
1 | String | --- |
NAME
|
100 | String | --- |
ADDRESS
|
65 | String | --- |
CITY
|
40 | String | --- |
ZIPCODE
|
9 | Number | --- |
OPERATING
|
60 | String | --- |
OP_CLASS
|
25 | String | --- |
YR_BUILT
|
4 | Number | --- |
COMMON_USE
|
4 | String | --- |
USE
|
50 | String | --- |
DESCRIPT
|
40 | String | --- |
FLAG
|
5 | String | --- |
UPDATE_DAY
|
8 | Date | --- |
AUTOID
|
6 | Number | --- |
FEATURE ATTRIBUTE TABLES CODES AND VALUES:
Item | Item Description | |
FID |
Internal feature number. |
|
Shape |
Feature geometry. |
|
Status |
ESRI item which denotes the status of the geocoded address whether it was matched or not). |
|
Score |
ESRI item which denotes the score with which the address was matched to a feature in the reference data. |
|
Side |
ESRI item which denotes the side of the street to which the address was matched (for geocoding service styles that can match an address to a particular side of a street). |
|
NAME |
Building Designation |
|
ADDRESS |
A description of a facility's physical location providing direction for delivery and provision of emergency services |
|
CITY |
City of facility's physical location |
|
ZIPCODE |
US postal delivery designation of facility's physical location |
|
OPERATING |
The responsible organization for management and operation of a facility (e.g., public, private, quasi-public) |
|
OP_CLASS |
Classification of the operating entity |
|
YR_BUILT |
The year a structure was built for determining possible historical significance |
|
COMMON_USE |
Location of two or more uses in one facility or on common grounds so as to share common facilities |
|
USE |
Description of co-located use, if applicable |
|
DESCRIPT |
FGDL added layer based on OP_CLASS |
|
FLAG |
Type of update the occurred
|
|
UPDATE_DAY |
The last day the file was updated |
|
AUTOID |
Internal ID # |
GeoPlan relied on the integrity of the attribute information within the original data. |
This dataset is a combination of government addresses from the
Yellow Pages online. 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. |
A note concerning data scale: Scale is an important factor in data usage. Certain scale datasetsare not suitable for some project, analysis, or modelling 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. 1:250000 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 analyses. Every effort has been made to supply the user with data documentation. For additional information, see the References sectionand the Data Source Contact section of this documentation. For more information regarding scale and accuracy, see our web pages at: http://www.geoplan.ufl.edu/education.html |
Yellow Pages website: www.yellowpages.com Super Pages website: www.superpages.com |
Government building locations were obtained from the online Yellow Pages in 2004. GeoPlan downloaded this data in textfile format and converted it to a dbf. The dbf was then geocoded against ARC Logistics Route GDT Roads and converted into a shapefile with the FGDL Albers HPGN map projection. Process Steps for Yellow Pages Government Locations: -Searched for government addresses in www.yellowpages.com -Selected government addresses under following categories: General Government (40) General Government Administration (141) General Government Administration, County Government (4014) General Government Administration, Federal Government (561) General Government Administration, Local Government (1638) General Government Administration, State Government (550) Government Administration General (227) -All addresses from sections above were copied and pasted into a textfile, which was then formatted so that it could be imported into Excel and converted to a database file format. Process Steps for Yellow Pages data: -The addresses were geocoded against ARC Logistics Route GDT Roads Shapefile created using FGDL Albers HPGN map projectio Process Steps for Super Pages U.S. Post Office Oriented Locations: -Searched for Post Office addresses in http://www.superpages.com/ -Selected Post Office addresses under following categories: Community & Government Government Offices Federal - Post Offices (911) -All addresses from sections above were copied and pasted into a textfile, which was then formatted so that it could be imported into Excel and converted to a database file format. -Removed Duplicates. -The addresses were geocoded against ARC Logistics Route GDT Roads Shapefile created using FGDL Albers HPGN map projection. (See "Map Projection Parameters" below). Process Steps for Yellow Pages U.S. Post Office Oriented Locations: -Searched for post office oriented addresses in www.yellowpages.com -Selected post office oriented addresses under following categories: United States Postal Service United States Postal Service - U S Postal Service (412) -All addresses from sections above were copied and pasted into a textfile, which was then formatted so that it could be imported into Excel and converted to a database file format. Process Steps for Yellow Pages data: -The addresses were geocoded against ARC Logistics Route GDT Roads Shapefile created using FGDL Albers HPGN map projection (See "Map Projection Parameters" below). -The two datasets were combined and duplicate records were removed. Total Records = 829 Process Date: 20030000 |
Projection ALBERS Datum HPGN Units METERS Spheroid GRS1980 1st Standard Parallel 24 0 0.000 2nd Standard Parallel 31 30 0.000 Central Meridian -84 00 0.000 Latitude of Projection's Origin 24 0 0.000 False Easting (meters) 400000.00000 False Northing (meters) 0.00000
DATA SOURCE CONTACT (S):
Name: Super Pages Online Address: 651 Canyon Drive Coppell, TX 75019 Phone: 1 (800) 343-7390 Web site: www.SuperPages.com Name: Yellow Pages Online Web site: www.YellowPages.comFGDL CONTACT: Name: FLORIDA GEOGRAPHIC DATA LIBRARY Abbr. Name: FGDL Address: Florida Geographic Data Library 431 Architecture Building PO Box 115706 Gainesville, FL 32611-5706 Web site: http://www.fgdl.org Contact FGDL: Technical Support: http://www.fgdl.org/fgdlfeed.html FGDL Frequently Asked Questions: http://www.fgdl.org/fgdlfaq.html FGDL Mailing Lists: http://www.fgdl.org/fgdl-l.html For FGDL Software: http://www.fgdl.org/software.html |