Abstract : The search for the most appropriate GIS data model to integrate, manipulate and analyse spatio-temporal data raises several research questions about the conceptualisation of geographic spaces. Although there is now a general consensus that many environmental phenomena require field and object conceptualisations to provide a comprehensive GIS representation, there is still a need for better integration of these dual representations of space within a formal spatio-temporal database. The research presented in this paper introduces a hybrid and formal dual data model for the representation of spatio-temporal data. The whole approach has been fully implemented in PostgreSQL and its spatial extension PostGIS, where the SQL language is extended by a series of data type constructions and manipulation functions to support hybrid queries. The potential of the approach is illustrated by an application to underwater geomorphological dynamics oriented towards the monitoring of the evolution of seabed changes. A series of performance and scalability experiments are also reported to demonstrate the computational performance of the model.Data Description : The data set used in our research is a set of bathymetric surveys recorded over three years from 2009 to 2011 as Digital Terrain Models (DTM) with 2m grid spacing. The first survey was carried out in February 2009 by the French hydrographic office, the second one was recorded on August-September 2010 and the third in July 2011, both by the “Institut Universitaire Européen de la Mer”.

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

JSONLayer: City Limits (ID:0)Name: City LimitsDisplay Field: CITYType: Feature LayerGeometry Type: esriGeometryPolygonDescription: Digital, spatially georeferenced graphic representation of the city limits of the City of Dallas, Texas.Copyright Text: City of Dallas GIS ServicesMin. Scale: 577792Max. Scale: 0Default Visibility: trueMax Record Count: 1000Supported query Formats: JSONUse Standardized Queries: TrueExtent:XMin: 2430144.56888622YMin: 6909399.42103373XMax: 2592859.12567431YMax: 7061339.44851789Spatial Reference: 102738 (2276)Drawing Info:{"renderer":{"type":"simple","symbol":{"type":"esriSFS","style":"esriSFSSolid","color":[115,156,156,255],"outline":{"type":"esriSLS","style":"esriSLSSolid","color":[115,156,156,255],"width":1}},"label":"","description":""},"transparency":0,"labelingInfo":null}HasZ: falseHasM: falseHas Attachments: falseHas Geometry Properties: trueHTML Popup Type: esriServerHTMLPopupTypeAsHTMLTextObject ID Field: OBJECTIDUnique ID Field:Name : OBJECTIDIsSystemMaintained : TrueGlobal ID Field:Type ID Field:Fields:OBJECTID (type: esriFieldTypeOID, alias: OBJECTID, SQL Type: sqlTypeOther, length: 0, nullable: false, editable: false)CITY (type: esriFieldTypeString, alias: CITY, SQL Type: sqlTypeOther, length: 20, nullable: true, editable: true)Shape_Area (type: esriFieldTypeDouble, alias: Shape_Area, SQL Type: sqlTypeDouble, nullable: true, editable: false)Shape_Length (type: esriFieldTypeDouble, alias: Shape_Length, SQL Type: sqlTypeDouble, nullable: true, editable: false)Templates:Name: City LimitsDescription:Drawing Tool: esriFeatureEditToolPolygonPrototype:Attributes:Is Data Versioned: falseSupports Rollback On Failure Parameter: trueLast Edit Date: 7/29/2020 3:52:44 PMSupported Operations: Query Query Top Features Query Analytic Generate Renderer Validate SQL

The Calls for Service dataset includes police service requests for which patrol officers, traffic officers, bike officers and, on occasion, detectives will be dispatched to public safety response. It also includes self-initiated calls for service where an officer witnesses a violation or suspicious activity for which they would respond.Contact E-mailContact Phone: N/ALink: N/AData Source: Versaterm Informix RMSData Source Type: Informix and/or SQL ServerPreparation Method: Preparation Method: Automated View pulled from CADWSQL (SQL Server) and duplicated on the GIS ServerPublish Frequency: WeeklyPublish Method: AutomaticData Dictionary

Contact E-mail Contact Phone: N/A Link: N/A Data Source: Versaterm Informix RMS Data Source Type: Informix and/or SQL Server Preparation Method: Preparation Method: Automated View pulled from CADWSQL (SQL Server) and duplicated on the GIS Server Publish Frequency: Weekly Publish Method: Automatic Data Dictionary

The Geographic Management Information System (GeoMIS) is a FISMA Moderate minor application built using ArcGIS Server and portal, Microsoft SQL, and a web-facing front-end. The system can be accessed over the internet via https://www.usaidgiswbg.com using a web browser. GeoMIS is based on a commercial off-the-shelf product developed by Esri. Esri is creates geographic information system (GIS) software, web GIS and geodatabase management applications and is based in California. GeoMISIt is maintained by an Israeli company, Systematics (see Attachment 3) which is EsriI's agent in Israel. The mission has an annual maintenance contract with Systematics for GeoMIS. GeoMIS has 100 users from USAID staff (USA Direct Hire and Foreign Service Nationals) and 200 users from USAID contractors and grantees. The system is installed at USAID WBG office in Tel Aviv/Israel inside the computer room in the DMZ. It has no interconnections with any other system.

2017, 2016. Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. 500 cities project city-level data in GIS-friendly format can be joined with city spatial data (https://chronicdata.cdc.gov/500-Cities/500-Cities-City-Boundaries/n44h-hy2j) in a geographic information system (GIS) to produce maps of 27 measures at the city-level. There are 7 measures (all teeth lost, dental visits, mammograms, Pap tests, colorectal cancer screening, core preventive services among older adults, and sleep less than 7 hours) in this 2019 release from the 2016 BRFSS that were the same as the 2018 release.

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

Line features representing existing and proposed fiber lines (buried & aerial) owned by Chatham County MIS in Chatham County, NC. These fiber lines are utilized for the NC811 notification system that Chatham County MIS participates in.

The buried fiber line features are utilized to create a buffer polygon that is imported into NC811's notification system serving as the basis for all Chatham County MIS notifications. The original data was collected by Performance Cabling using industry standard GPS collection methods. The data was delivered to Chatham County MIS / GIS in May of 2015. The data was imported into the ChathamGIS SQL database in August 2015 and stored in the "infrastructure" dataset.

The ongoing data updates and maintenance will be conducted by Chatham County GIS in collaboration with Performance Cabling on an as needed basis.Chatham GIS SOP: "MAPSERV-74"

Treasure County Cadastral Data ResourcesA snapshot of property and parcel data for June 2022.Department of Revenue Orion SQL property record database provided as both an SQL database and as tables in a file geodatabase.File Geodatabase and Shapefile options for parcel polygon GIS data.Visit the Montana State Library Cadastral MSDI page for more information on cadastral data and Orion property database : MSDI Cadastral (mt.gov)The Montana Cadastral Framework shows the taxable parcels and tax-exempt parcels for most of Montana. The parcels contain selected information such as owner names, property and owner addresses, assessed value, agricultural use, and tax district information that were copied from the Montana Department of Revenue's ORION tax appraisal database. The data are maintained by the MT Department of Revenue, except for Ravalli, Silver Bow, Missoula, Flathead and Yellowstone counties that are maintained by the individual counties. The Revenue and county data are integrated by Montana State Library staff. Each parcel contains an attribute called ParcelID (geocode) that is the parcel identifier. View a pdf map of the counties that were updated this month here: https://ftpgeoinfo.msl.mt.gov/Data/Spatial/MSDI/Cadastral/Parcels/Statewide/MonthlyCadastralUpdateMap.pdf The parcel boundaries were aligned to fit with the Bureau of Land Management Geographic Coordinate Database (GCDB) of public land survey coordinates. Parcels whose legal descriptions consisted of aliquot parts of the public land survey system were created from the GCDB coordinates by selecting and, when necessary, subdividing public land survey entities. Other parcels were digitized from paper maps and the data from each map were transformed to fit with the appropriate GCDB boundaries.

The General Offense Crime Report Dataset includes criminal and city code violation offenses which document the scope and nature of each offense or information gathering activity. It is used to computate the Uniform Crime Report Index as reported to the Federal Bureau of Investigation and for local crime reporting purposes.Contact: Carlena Orosco - Police Planning and Research SupervisorContact E-mailLink: N/AData Source: Versaterm Informix RMS - CADWSQLData Source Type: Informix and/or SQL ServerPreparation Method: Preparation Method: Automated View pulled from CADWSQL (SQL Server) and duplicated on the GIS ServerPublish Frequency: WeeklyPublish Method: AutomaticData Dictionary

The Kid Zone Enrichment Program provides a safe and enriching place for students to be in out-of-school time. This dataset provides the percentage of students who are currently enrolled in after school community programs. Data are broken down by school, including school and Kid Zone enrollment.

This page provides data for the Kid Zone Participation performance measure.

These data are the source of the summary values for Performance Measure 1.18

The performance measure dashboard is available at 1.18 Kid Zone Participation

Additional Information

Source: SQL Server

Contact: Jeremy King

Contact E-Mail: jeremy_king@tempe.gov

Data Source Type: SQL Server

Preparation Method: Extracted to Excel and combined with data given by the Tempe and Kyrene School districts (school enrollment, Free and Reduced Lunch Percentages). These data are generated from from SQL counts the participants by site with an enrollment end date greater or equal to the report date.

Publish Frequency: Annually

Publish Method: Manual

Data Dictionary

This layer was compiled by the Cape Cod Comission (CCC). It consists of parcel centroid points representing A) those addresses that the Board of Health has determined to have failing Title 5 System(s), B) modeled locations where the CCC has used environmental and parcel characteristics to determine those areas where Title 5 Systems may have the potential to fail and C) those addresses that have submitted Title 5 Loans through the Barnstable County Community Septic Management Loan Program. The CCC-modeled locations are based on the CCC's Base_Layers.DBO.cape_Parcels SQL layer. CCC developed a layer consisting of (1) all parcels

This example demonstrates how to use PostGIS capabilities in CyberGIS-Jupyter notebook environment. Modified from notebook by Weiye Chen (weiyec2@illinois.edu)

PostGIS is an extension to the PostgreSQL object-relational database system which allows GIS (Geographic Information Systems) objects to be stored in the database. PostGIS includes support for GiST-based R-Tree spatial indices, and functions for analysis and processing of GIS objects.

Resources for PostGIS:

Manual https://postgis.net/docs/ In this demo, we use PostGIS 3.0. Note that significant changes in APIs have been made to PostGIS compared to version 2.x. This demo assumes that you have basic knowledge of SQL.

The Calls for Service dataset includes police service requests for which patrol officers, traffic officers, bike officers and, on occasion, detectives will be dispatched to public safety response. It also includes self-initiated calls for service where an officer witnesses a violation or suspicious activity for which they would respond.Contact E-mailContact Phone: N/ALink: N/AData Source: Versaterm Informix RMSData Source Type: Informix and/or SQL ServerPreparation Method: Preparation Method: Automated View pulled from CADWSQL (SQL Server) and duplicated on the GIS ServerPublish Frequency: WeeklyPublish Method: AutomaticData Dictionary

OR-Trans is a GIS road centerline dataset compiled from numerous sources of data throughout the state. Each dataset is from the road authority responsible for (or assigned data maintenance for) the road data each dataset contains. Data from each dataset is compiled into a statewide dataset that has the best available data from each road authority for their jurisdiction (or assigned data maintenance responsibility). Data is stored in a SQL database and exported in numerous formats.

OR-Trans is a GIS road centerline dataset compiled from numerous sources of data throughout the state. Each dataset is from the road authority responsible for (or assigned data maintenace for) the road data each dataset contains. Data from each dataset is compiled into a statewide dataset that has the best avaialble data from each road authority for their jurisdiction (or assigned data maintenance responsibility). Data is stored in a SQL database and exported in numerous formats.

A polygon depiction of property sales from 2010 to the present that occurred in Stark County, Ohio. The Stark County Auditor's Office (SCAO) maintains records of property sales using a Computer-Assisted Mass Appraisal (CAMA) Database. This layer is a SQL view combining the sales records from the CAMA database with the Stark County parcel layer. A new view is created every morning through a combination of python scripts and SQL stored procedures. The data always reflects the most-recent information available from the previous day for both sources.

Affiliate Associations consists of a group of non-profits or organizations involving business members or residents comprised of multiple neighborhoods with a common purpose and interest in neighborhoods. The data imported in this feature layers highlights the nine organizations that make up Tempe’s Affiliate Associations. They are represented as points when utilized. Contact: Will DukeContact E-Mail: will_duke@tempe.govContact Phone: N/ALink: N/AData Source: SQL Server/ArcGIS ServerData Source Type: GeospatialPreparation Method: N/APublish Frequency: As information changesPublish Method: AutomaticData Dictionary

This data has been collected as part of a larger project by the City of Austin's Watershed Protection and Development Review Department to inventory its drainage infrastructure and create a GIS to store this information. The project includes an internal team developing a GIS based on record documents and an external team locating ground level appurtenances using GPS field collection units. The data in this data set represents the former.

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

Contains approximately 38,447 point locations of Wyoming well permit locations on file with the Wyoming State Engineer's Office. The wells have been located to the to the nearest 40 acre parcel. All locational information and attributes were imported from the Wyoming State Engineer's Office Well Permits Database stored in SQL-Server