This script will prompt the user for a path to a file geodatabase or a sde geodatabase connection file. Then the script will loop through the feature classes\tables and document details about the attribute rules. All of the data gathered is written to a csv file. This is a Jupyter Notebook written using arcpy.Sources used to develop this notebook:Iterate through SDE to find and export FCs with Attribute Rules with python?Attribute Rule propertiesA Python script to Automate Attribute Rules Deployment

The establishment of a BES Multi-User Geodatabase (BES-MUG) allows for the storage, management, and distribution of geospatial data associated with the Baltimore Ecosystem Study. At present, BES data is distributed over the internet via the BES website. While having geospatial data available for download is a vast improvement over having the data housed at individual research institutions, it still suffers from some limitations. BES-MUG overcomes these limitations; improving the quality of the geospatial data available to BES researches, thereby leading to more informed decision-making. BES-MUG builds on Environmental Systems Research Institute's (ESRI) ArcGIS and ArcSDE technology. ESRI was selected because its geospatial software offers robust capabilities. ArcGIS is implemented agency-wide within the USDA and is the predominant geospatial software package used by collaborating institutions. Commercially available enterprise database packages (DB2, Oracle, SQL) provide an efficient means to store, manage, and share large datasets. However, standard database capabilities are limited with respect to geographic datasets because they lack the ability to deal with complex spatial relationships. By using ESRI's ArcSDE (Spatial Database Engine) in conjunction with database software, geospatial data can be handled much more effectively through the implementation of the Geodatabase model. Through ArcSDE and the Geodatabase model the database's capabilities are expanded, allowing for multiuser editing, intelligent feature types, and the establishment of rules and relationships. ArcSDE also allows users to connect to the database using ArcGIS software without being burdened by the intricacies of the database itself. For an example of how BES-MUG will help improve the quality and timeless of BES geospatial data consider a census block group layer that is in need of updating. Rather than the researcher downloading the dataset, editing it, and resubmitting to through ORS, access rules will allow the authorized user to edit the dataset over the network. Established rules will ensure that the attribute and topological integrity is maintained, so that key fields are not left blank and that the block group boundaries stay within tract boundaries. Metadata will automatically be updated showing who edited the dataset and when they did in the event any questions arise. Currently, a functioning prototype Multi-User Database has been developed for BES at the University of Vermont Spatial Analysis Lab, using Arc SDE and IBM's DB2 Enterprise Database as a back end architecture. This database, which is currently only accessible to those on the UVM campus network, will shortly be migrated to a Linux server where it will be accessible for database connections over the Internet. Passwords can then be handed out to all interested researchers on the project, who will be able to make a database connection through the Geographic Information Systems software interface on their desktop computer. This database will include a very large number of thematic layers. Those layers are currently divided into biophysical, socio-economic and imagery categories. Biophysical includes data on topography, soils, forest cover, habitat areas, hydrology and toxics. Socio-economics includes political and administrative boundaries, transportation and infrastructure networks, property data, census data, household survey data, parks, protected areas, land use/land cover, zoning, public health and historic land use change. Imagery includes a variety of aerial and satellite imagery. See the readme: http://96.56.36.108/geodatabase_SAL/readme.txt See the file listing: http://96.56.36.108/geodatabase_SAL/diroutput.txt

Crashes within the City of Hardeeville, via SCDPH.

A combination of stormwater system data throughout Stark County, Ohio. The data is combined using an ETL via the data interoperability extension for ArcGIS Pro. Each weekend, the ETL is automatically ran via Python/Windows Task Scheduler to update the data with any changes from the past week from each of the source datasets. The source data is stored in ArcGIS SDE databases that Stark County GIS (SCGIS) provides for departments, cities, villages, and townships within the county. SCGIS currently maintains SDE databases for Canton, Alliance, Louisville, North Canton, Beach City, Easton Canton, Minerva, Meyers Lake, Stark County Engineer (SCE), and each of the townships. In addition to those datasets (which are updated weekly), this layer also includes data from the cities of Massillon and Canal Fulton, which are not stored in databases maintained by SCGIS. Data for those two cities is updated separately as new iterations become available.As this layer encompasses the entire county, source feature classes are consolidated into 4 layers to improve performance on ArcGIS Online. Discharge points are the point at which water exits part of the stormwater system, such as the outlet of a pipe or ditch. It includes outfalls defined under NPDES Phase II. Structures includes both inlets (catch basins, yard drains, etc.) and manholes. Pipes includes storm sewers, as well as culverts (pipes in which both ends are daylit). Finally, the ditches layer includes roadside ditches, as well as off-road ditches in some areas/instances.

Local Electoral Areas 2014, for Local Area Elections. Also showing Electoral Divisions.

Contact the Parks GIS Team for more information via email: MCParksGIS@montgomeryparks.org.Data LinksAGOL Feature Service: https://mcplanning.maps.arcgis.com/home/item.html?id=a3817537452e48f194aad914f5ee282aServices:https://montgomeryplans.org/server/rest/services/ParkPolice/ParkPoliceBeats_Py/MapServerhttps://montgomeryplans.org/server/rest/services/ParkPolice/ParkPoliceBeats_Py/FeatureServer

NOTE: This dataset holds 'static' data that we don't expect to change. We have removed it from the SDE database and placed it in ArcGIS Online, but it is still considered part of the SGID and shared on opendata.gis.utah.gov.

NOTE: This dataset holds 'static' data that we don't expect to change. We have removed it from the SDE database and placed it in ArcGIS Online, but it is still considered part of the SGID and shared on opendata.gis.utah.gov.

Currently filtered for Storm Date is after 12/1/2023Purpose: This is a feature layer of tornado swaths for the NWS Damage Assessment Toolkit.The National Weather Service (NWS) Damage Assessment Toolkit (DAT) has been utilized experimentally since 2009 to assess damage following tornadoes and convective wind events. The DAT is a GIS-based framework for collecting, storing, and analyzing damage survey data, utilizing the Enhanced Fujita (EF) scale for the classification of damage. Data collected from individual locations via mobile device are transmitted to a central geospatial database where they are quality controlled and analyzed to assign the official EF rating. In addition to the individual point, the data are analyzed to generate track centerlines and damage swaths. High resolution satellite imagery and radar data, through partnership with the NASA Short-term Prediction Research and Transition Center, are also available to aid in the analysis. The subsequent dataset is then made available through a web-based graphical interface and GIS services.Here is the full REST service: https://services.dat.noaa.gov/arcgis/rest/services/nws_damageassessmenttoolkitGeoplatform website: https://communities.geoplatform.gov/disasters/noaa-damage-assessment-toolkit-dat/More InformationWelcome to the National Weather Service Damage Assessment Toolkit. Data on this interface is collected during NWS Post-Event Damage Assessments. While the data has been quality controlled, it is still considered preliminary. Official statistics for severe weather events can be found in the Storm Data publication, available from the National Centers for Environmental Information (NCEI) at: https://www.ncdc.noaa.gov/IPS/sd/sd.html Questions regarding this data can be addressed to: parks.camp@noaa.gov.

A combination of stormwater discharge point data throughout Stark County, Ohio. Discharge points are the point at which water exits part of the stormwater system, such as the outlet of a pipe or ditch. It includes outfalls defined under NPDES Phase II. The data is combined using an ETL via the data interoperability extension for ArcGIS Pro. Each weekend, the ETL is automatically ran via Python/Windows Task Scheduler to update the data with any changes from the past week from each of the source datasets. The source data is stored in ArcGIS SDE databases that Stark County GIS (SCGIS) provides for departments, cities, villages, and townships within the county. SCGIS currently maintains SDE databases for Canton, Alliance, Louisville, North Canton, Beach City, Easton Canton, Minerva, Meyers Lake, Stark County Engineer (SCE), and each of the townships. In addition to those datasets (which are updated weekly), this layer also includes data from the cities of Massillon and Canal Fulton, which are not stored in databases maintained by SCGIS. Data for those two cities is updated separately as new iterations become available.

Updates daily via FME. FME updates this layer and the hosted public-view CIP layers.Any edits to the Shared Use Path locations should be done in SDE.

This dataset represents CEF buffers identified during the development review process since 1995. Prior to 1995, data is either unavailable or lost. CEF buffers were digitized from construction plans, environmental assessments, and City of Austin staff field observations into a versioned SDE database using ArcMap. Actual buffers size for any particular feature may be determined through a process of negotiation with land development interests, and may differ from standard dimensions stated in the Land Development Code.

Utility layer maintained by the City of Salem Public Works Technical Services Team. Features are updated weekly though a Python script from SDE for viewing only in Salem Maps Online. This layer has been filtered (for security) and symbolized in ArcGIS Pro, and has custom popups created from the feature layer's Visualization tab. For unfiltered and data, reference the Internal Data Utilities layers in the SalemPW account.

This view is for our CCS program Workforce tickets and ARCGIS ticket managementThis map includes location information for the Continuous Count Stations (CCS) that collect data in hourly intervals for Volume, Length, and Speed (15 minute intervals are available as of Jan 1, 2017.). These sites were previously known as Automatic Traffic Recorders (ATR's). Location information is updated monthly. Please send questions and feedback related to this map and related CCS data to: Contact UDOT Traffic StatisticsAdditional CCS reports can be found at:https://www.udot.utah.gov/go/trafficstats

Feature layer generated from running the Buffer Features solution. Input from Transit Rail Stations - SDEPUB.SDE.Transit_Rail_Stations were buffered by [0.25] Miles

Number of WNV outbreaks and strains stored in the DMD database since 1994.

Contact the Parks GIS Team for more information via email: MCParksGIS@montgomeryparks.org.Data LinksAGOL Feature Service: https://mcplanning.maps.arcgis.com/home/item.html?id=727bab07c5da4c81b88cabdf16a5cf44Services:https://montgomeryplans.org/server/rest/services/Parks/ParkUnits_Py/MapServerhttps://montgomeryplans.org/server/rest/services/Parks/ParkUnits_Py/FeatureServer

In 1986, parcel polygons [PARPOLY] were digitized from hand drawn 1:2400 half and 1:1200 quarter section maps. 1995, the parcel data layer was converted to an ArcINFO format and held in an ArcStorm database. Parcels polygons were converted in 2005 to an ESRI ArcGIS SDE GeoDatabase. In 2014, Ramsey County migrated to ESRI's Parcel Fabric; Government Lots were created from the Parcel Components.

Map of Mills and Covered Bridges. The data is curated by Vince DiNoto and links to a Esri Collector application.

Polygon features from the GRIP database representing counties in Oklahoma.