To achieve true data interoperability is to eliminate format and data model barriers, allowing you to seamlessly access, convert, and model any data, independent of format. The ArcGIS Data Interoperability extension is based on the powerful data transformation capabilities of the Feature Manipulation Engine (FME), giving you the data you want, when and where you want it.In this course, you will learn how to leverage the ArcGIS Data Interoperability extension within ArcCatalog and ArcMap, enabling you to directly read, translate, and transform spatial data according to your independent needs. In addition to components that allow you to work openly with a multitude of formats, the extension also provides a complex data model solution with a level of control that would otherwise require custom software.After completing this course, you will be able to:Recognize when you need to use the Data Interoperability tool to view or edit your data.Choose and apply the correct method of reading data with the Data Interoperability tool in ArcCatalog and ArcMap.Choose the correct Data Interoperability tool and be able to use it to convert your data between formats.Edit a data model, or schema, using the Spatial ETL tool.Perform any desired transformations on your data's attributes and geometry using the Spatial ETL tool.Verify your data transformations before, after, and during a translation by inspecting your data.Apply best practices when creating a workflow using the Data Interoperability extension.

The ArcGIS Data Interoperability extension enables you to work with data stored in a significant number of formats that are native and non-native to ArcGIS. From a simple translation between two formats to complex transformations on data content and structure, this extension provides the solution to overcome interoperability barriers.After completing this course, you will be able to:Use existing translation parameters to control data translations.Translate multiple datasets at once.Use parameters to change the coordinate system of the data.

Temperature survey at 2 meters. This web map service (WMS) was published using ArcServer v. 10.1 and is compliant with OGC (Open Geospatial Consortium) version 1.30 specifications. This service provides dynamic, spatially referenced geographic information using data collected for the National Geothermal Data System (http://www.geothermaldata.org/). In addition to the WMS capabilities, this service was designed to be interoperable with both WFS (Web Feature Services) as well as KML (Keyhole Markup Language). The WFS capabilities allow the client to query, make additions and/or modifications to an existing dataset. WFS can be utilized through the interoperability extension in ArcCatalog. For more information on using the ArcGIS data interoperability extension visit http://www.esri.com/software/arcgis/extensions/datainteroperability /common-questions.html. A KML service allows the client to view an image of the data in three dimensions, using free software available for download on the internet such as ArcGIS Explorer or Google Earth. For more information on OGC specifications, visit http://www.opengeospatial.org/standards.

This web map service (WMS) was published using ArcServer v. 10.1 and is compliant with OGC (Open Geospatial Consortium) version 1.30 specifications. This service provides dynamic, spatially referenced geographic information using data collected for the National Geothermal Data System (http://www.geothermaldata.org/). In addition to the WMS capabilities, this service was designed to be interoperable with both WFS (Web Feature Services) as well as KML (Keyhole Markup Language). The WFS capabilities allow the client to query, make additions and/or modifications to an existing dataset. WFS can be utilized through the interoperability extension in ArcCatalog. For more information on using the ArcGIS data interoperability extension visit http://www.esri.com/software/arcgis/extensions/datainteroperability /common-questions.html. A KML service allows the client to view an image of the data in three dimensions, using free software available for download on the internet such as ArcGIS Explorer or Google Earth. For more information on OGC specifications, visit http://www.opengeospatial.org/standards.

Statewide Download (FGDB) (SHP)Users can also download smaller geographic areas of this feature service in ArcGIS Pro using the Copy Features geoprocessing tool.The address service contains statewide address points and related landmark name alias table and street name alias table.The New Jersey Office of Information Technology, Office of GIS (NJOGIS), in partnership with several local GIS and public safety agencies, has built a comprehensive statewide NG9-1-1 database meeting and exceeding the requirements of the National Emergency Number Association (NENA) 2018 NG9-1-1 GIS Data Standard (NENA-STA-006.1-2018). The existing New Jersey Statewide Address Point data last published in 2016 has been transformed in the NENA data model to create this new address point data.The initial address points were processed from statewide parcel records joined with the statewide Tax Assessor's (MOD-IV) database in 2015. Address points supplied by Monmouth County, Sussex County, Morris County and Montgomery Township in Somerset County were incorporated into the statewide address points using customized Extract, Transform and Load (ETL) procedures.The previous version of the address points was loaded into New Jersey's version of the NENA NG9-1-1 data model using Extract, Transform and Load (ETL) procedures created with Esri's Data Interoperability Extension. Subsequent manual and bulk processing corrections and additions have been made, and are ongoing.***NOTE*** For users who incorporate NJOGIS services into web maps and/or web applications, please sign up for the NJ Geospatial Forum discussion listserv for early notification of service changes. Visit https://nj.gov/njgf/about/listserv/ for more information.

The New Jersey Office of Information Technology, Office of GIS (NJOGIS), in partnership with several local GIS and public safety agencies, has built a comprehensive statewide NG9-1-1 database meeting and exceeding the requirements of the National Emergency Number Association (NENA) 2018 NG9-1-1 GIS Data Standard (NENA-STA-006.1-2018). The existing New Jersey Statewide Address Point data last published in 2016 has been transformed in the NENA data model to create this new address point data.The initial address points were processed from statewide parcel records joined with the statewide Tax Assessor's (MOD-IV) database in 2015. Address points supplied by Monmouth County, Sussex County, Morris County and Montgomery Township in Somerset County were incorporated into the statewide address points using customized Extract, Transform and Load (ETL) procedures.The previous version of the address points was loaded into New Jersey's version of the NENA NG9-1-1 data model using Extract, Transform and Load (ETL) procedures created with Esri's Data Interoperability Extension. Subsequent manual and bulk processing corrections and additions have been made, and are ongoing.

Statewide Download (FGDB) (SHP)Users can also download smaller geographic areas of this feature service in ArcGIS Pro using the Copy Features geoprocessing tool.The address service contains statewide address points and related landmark name alias table and street name alias table.The New Jersey Office of Information Technology, Office of GIS (NJOGIS), in partnership with several local GIS and public safety agencies, has built a comprehensive statewide NG9-1-1 database meeting and exceeding the requirements of the National Emergency Number Association (NENA) 2018 NG9-1-1 GIS Data Standard (NENA-STA-006.1-2018). The existing New Jersey Statewide Address Point data last published in 2016 has been transformed in the NENA data model to create this new address point data.The initial address points were processed from statewide parcel records joined with the statewide Tax Assessor's (MOD-IV) database in 2015. Address points supplied by Monmouth County, Sussex County, Morris County and Montgomery Township in Somerset County were incorporated into the statewide address points using customized Extract, Transform and Load (ETL) procedures.The previous version of the address points was loaded into New Jersey's version of the NENA NG9-1-1 data model using Extract, Transform and Load (ETL) procedures created with Esri's Data Interoperability Extension. Subsequent manual and bulk processing corrections and additions have been made, and are ongoing.***NOTE*** For users who incorporate NJOGIS services into web maps and/or web applications, please sign up for the NJ Geospatial Forum discussion listserv for early notification of service changes. Visit https://nj.gov/njgf/about/listserv/ for more information.

Statewide Download (FGDB) (SHP)Users can also download smaller geographic areas of this feature service in ArcGIS Pro using the Copy Features geoprocessing tool.The New Jersey Office of Information Technology, Office of GIS (NJOGIS), in partnership with several local GIS and public safety agencies, as well as the NJ Department of Transportation, has built a comprehensive statewide NG9-1-1 database meeting and exceeding the requirements of the National Emergency Number Association (NENA) 2018 NG9-1-1 GIS Data Standard (NENA-STA-006.1-2018). The previous New Jersey statewide road segment data (Tran_road_centerline_NJ), which included the road name alias information, has been transformed into the NENA data model to create the street name alias table.The existing road centerlines were loaded into New Jersey's version of the NENA NG9-1-1 data model using Extract, Transform and Load (ETL) procedures created with Esri's Data Interoperability Extension. The data subsequently have been updated and corrected.The road centerlines no longer contain any linear referencing information. The linear referencing will only be maintained by the NJ Department of Transportation as part of the NJ Roadway Network.***NOTE*** For users who incorporate NJOGIS services into web maps and/or web applications, please sign up for the NJ Geospatial Forum discussion listserv for early notification of service changes. Visit https://nj.gov/njgf/about/listserv/ for more information.

The dataset is a spatial representation of road centerlines in Somerset County, New Jersey. The New Jersey Office of Information Technology, Office of GIS (NJOGIS), in partnership with several local GIS and public safety agencies, as well as the NJ Department of Transportation, has built a comprehensive statewide NG9-1-1 database meeting and exceeding the requirements of the National Emergency Number Association (NENA) 2018 NG9-1-1 GIS Data Standard (NENA-STA-006.1-2018). The previous New Jersey statewide road segment data (Tran_road_centerline_NJ), which included the road name alias information, has been transformed into the NENA data model to create the street name alias table.The existing road centerlines were loaded into New Jersey's version of the NENA NG9-1-1 data model using Extract, Transform and Load (ETL) procedures created with Esri's Data Interoperability Extension. The data subsequently have been updated and corrected.The road centerlines no longer contain any linear referencing information. The linear referencing will only be maintained by the NJ Department of Transportation as part of the NJ Roadway Network. The data for Somerset County, New Jersey was extracted & processed from the latest NJOGIS dataset by the Somerset County Office of GIS Services (SCOGIS) on April 10, 2024

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.

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.

The New Jersey Office of Information Technology, Office of GIS (NJOGIS), in partnership with several local GIS and public safety agencies, has built a comprehensive statewide NG9-1-1 database meeting and exceeding the requirements of the National Emergency Number Association (NENA) 2018 NG9-1-1 GIS Data Standard (NENA-STA-006.1-2018). The existing New Jersey Statewide Address Point data last published in 2016 has been transformed in the NENA data model to create this new address point data.The initial address points were processed from statewide parcel records joined with the statewide Tax Assessor's (MOD-IV) database in 2015. Address points supplied by Monmouth County, Sussex County, Morris County and Montgomery Township in Somerset County were incorporated into the statewide address points using customized Extract, Transform and Load (ETL) procedures.The previous version of the address points was loaded into New Jersey's version of the NENA NG9-1-1 data model using Extract, Transform and Load (ETL) procedures created with Esri's Data Interoperability Extension. Subsequent manual and bulk processing corrections and additions have been made, and are ongoing.

The New Jersey Office of Information Technology, Office of GIS (NJOGIS), in partnership with several local GIS and public safety agencies, as well as the NJ Department of Transportation, has built a comprehensive statewide NG9-1-1 database meeting and exceeding the requirements of the National Emergency Number Association (NENA) 2018 NG9-1-1 GIS Data Standard (NENA-STA-006.1-2018). The previous New Jersey statewide road segment data (Tran_road_centerline_NJ), which included the road name alias information, has been transformed into the NENA data model to create the street name alias table.The existing road centerlines were loaded into New Jersey's version of the NENA NG9-1-1 data model using Extract, Transform and Load (ETL) procedures created with Esri's Data Interoperability Extension. The data subsequently have been updated and corrected.The road centerlines no longer contain any linear referencing information. The linear referencing will only be maintained by the NJ Department of Transportation as part of the NJ Roadway Network.

The New Jersey Office of Information Technology, Office of GIS (NJOGIS), in partnership with several local GIS and public safety agencies, as well as the NJ Department of Transportation, has built a comprehensive statewide NG9-1-1 database meeting and exceeding the requirements of the National Emergency Number Association (NENA) 2018 NG9-1-1 GIS Data Standard (NENA-STA-006.1-2018). The previous New Jersey statewide road segment data (Tran_road_centerline_NJ), which included the road name alias information, has been transformed into the NENA data model to create the street name alias table.The existing road centerlines were loaded into New Jersey's version of the NENA NG9-1-1 data model using Extract, Transform and Load (ETL) procedures created with Esri's Data Interoperability Extension. The data subsequently have been updated and corrected.The road centerlines no longer contain any linear referencing information. The linear referencing will only be maintained by the NJ Department of Transportation as part of the NJ Roadway Network.

The New Jersey Office of Information Technology, Office of GIS (NJOGIS), in partnership with several local GIS and public safety agencies, as well as the NJ Department of Transportation, has built a comprehensive statewide NG9-1-1 database meeting and exceeding the requirements of the National Emergency Number Association (NENA) 2018 NG9-1-1 GIS Data Standard (NENA-STA-006.1-2018). The previous New Jersey statewide road segment data (Tran_road_centerline_NJ), which included the road name alias information, has been transformed into the NENA data model to create the street name alias table.The existing road centerlines were loaded into New Jersey's version of the NENA NG9-1-1 data model using Extract, Transform and Load (ETL) procedures created with Esri's Data Interoperability Extension. The data subsequently have been updated and corrected.The road centerlines no longer contain any linear referencing information. The linear referencing will only be maintained by the NJ Department of Transportation as part of the NJ Roadway Network.

The New Jersey Office of Information Technology, Office of GIS (NJOGIS), in partnership with several local GIS and public safety agencies, as well as the NJ Department of Transportation, has built a comprehensive statewide NG9-1-1 database meeting and exceeding the requirements of the National Emergency Number Association (NENA) 2018 NG9-1-1 GIS Data Standard (NENA-STA-006.1-2018). The previous New Jersey statewide road segment data (Tran_road_centerline_NJ), which included the road name alias information, has been transformed into the NENA data model to create the street name alias table.The existing road centerlines were loaded into New Jersey's version of the NENA NG9-1-1 data model using Extract, Transform and Load (ETL) procedures created with Esri's Data Interoperability Extension. The data subsequently have been updated and corrected.The road centerlines no longer contain any linear referencing information. The linear referencing will only be maintained by the NJ Department of Transportation as part of the NJ Roadway Network.

A combination of stormwater pipe data throughout Stark County, Ohio. Pipes includes storm sewers, as well as culverts (pipes in which both ends are daylit). 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.

The New Jersey Office of Information Technology, Office of GIS (NJOGIS), in partnership with several local GIS and public safety agencies, has built a comprehensive statewide NG9-1-1 database meeting and exceeding the requirements of the National Emergency Number Association (NENA) 2018 NG9-1-1 GIS Data Standard (NENA-STA-006.1-2018). The existing New Jersey Statewide Address Point data last published in 2016 has been transformed in the NENA data model to create this new address point data.The initial address points were processed from statewide parcel records joined with the statewide Tax Assessor's (MOD-IV) database in 2015. Address points supplied by Monmouth County, Sussex County, Morris County and Montgomery Township in Somerset County were incorporated into the statewide address points using customized Extract, Transform and Load (ETL) procedures.The previous version of the address points was loaded into New Jersey's version of the NENA NG9-1-1 data model using Extract, Transform and Load (ETL) procedures created with Esri's Data Interoperability Extension. Subsequent manual and bulk processing corrections and additions have been made, and are ongoing.

The region is the top tier of local government in New Zealand. There are 16 regions of New Zealand (Part 1 of Schedule 2 of the Local Government Act 2002). Eleven are governed by an elected regional council, while five are governed by territorial authorities (the second tier of local government) who also perform the functions of a regional council and thus are known as unitary authorities. These unitary authorities are Auckland Council, Nelson City Council, Gisborne, Tasman, and Marlborough District Councils. The Chatham Islands Council also perform some of the functions of a regional council, but is not strictly a unitary authority. Unitary authorities act as regional councils for the purposes of a wide range of Acts and regulations. Regional council areas are based on water catchment areas. Regional councils are responsible for the administration of many environmental and public transport matters.Regional Councils were established in 1989 after the abolition of the 22 local government regions. The local government act 2002, requires the boundaries of regions to confirm as far as possible to one or more water catchments. When determining regional boundaries, the local Government commission gave consideration to regional communities of interest when selecting water catchments to included in a region. It also considered factors such as natural resource management, land use planning and environmental matters. Some regional boundaries are conterminous with territorial authority boundaries but there are many exceptions. An example is Taupo District, which is split between four regions, although most of its area falls within the Waikato Region. Where territorial local authorities straddle regional council boundaries, the affected area have been statistically defined in complete area units. Generally regional councils contain complete territorial authorities. The unitary authority of the Auckland Council was formed in 2010, under the Local Government (Tamaki Makarau Reorganisation) Act 2009, replacing the Auckland Regional Council and seven territorial authorities.The seaward boundary of any costal regional council is the twelve mile New Zealand territorial limit. Regional councils are defined at meshblock and area unit level.Regional Councils included in the 2013 digital pattern are:Regional Council CodeRegional Council Name01Northland Region02Auckland Region03Waikato Region04Bay of Plenty Region05Gisborne Region06Hawke's Bay Region07Taranaki Region08Manawatu-Wanganui Region09Wellington Region12West Coast Region13Canterbury Region14Otago Region15Southland Region16Tasman Region17Nelson Region18Marlborough Region99Area Outside RegionAs at 1stJuly 2007, Digital Boundary data became freely available.Deriving of Output FilesThe original vertices delineating the meshblock boundary pattern were digitised in 1991 from 1:5,000 scale urban maps and 1:50,000 scale rural maps. The magnitude of error of the original digital points would have been in the range of +/- 10 metres in urban areas and +/- 25 metres in rural areas. Where meshblock boundaries coincide with cadastral boundaries the magnitude of error will be within the range of 1–5 metres in urban areas and 5 - 20 metres in rural areas. This being the estimated magnitude of error of Landonline.The creation of high definition and generalised meshblock boundaries for the 2013 digital pattern and the dissolving of these meshblocks into other geographies/boundaries were completed within Statistics New Zealand using ESRI's ArcGIS desktop suite and the Data Interoperability extension with the following process: 1. Import data and all attribute fields into an ESRI File Geodatabase from LINZ as a shapefile2. Run geometry checks and repairs.3. Run Topology Checks on all data (Must Not Have Gaps, Must Not Overlap), detailed below.4. Generalise the meshblock layers to a 1m tolerance to create generalised dataset. 5. Clip the high definition and generalised meshblock layers to the coastline using land water codes.6. Dissolve all four meshblock datasets (clipped and unclipped, for both generalised and high definition versions) to higher geographies to create the following output data layers: Area Unit, Territorial Authorities, Regional Council, Urban Areas, Community Boards, Territorial Authority Subdivisions, Wards Constituencies and Maori Constituencies for the four datasets. 7. Complete a frequency analysis to determine that each code only has a single record.8. Re-run topology checks for overlaps and gaps.9. Export all created datasets into MapInfo and Shapefile format using the Data Interoperability extension to create 3 output formats for each file. 10. Quality Assurance and rechecking of delivery files.The High Definition version is similar to how the layer exists in Landonline with a couple of changes to fix topology errors identified in topology checking. The following quality checks and steps were applied to the meshblock pattern:Translation of ESRI Shapefiles to ESRI geodatabase datasetThe meshblock dataset was imported into the ESRI File Geodatabase format, required to run the ESRI topology checks. Topology rules were set for each of the layers. Topology ChecksA tolerance of 0.1 cm was applied to the data, which meant that the topology engine validating the data saw any vertex closer than this distance as the same location. A default topology rule of “Must Be Larger than Cluster Tolerance” is applied to all data – this would highlight where any features with a width less than 0.1cm exist. No errors were found for this rule.Three additional topology rules were applied specifically within each of the layers in the ESRI geodatabase – namely “Must Not Overlap”, “Must Not Have Gaps” and “"Area Boundary Must Be Covered By Boundary Of (Meshblock)”. These check that a layer forms a continuous coverage over a surface, that any given point on that surface is only assigned to a single category, and that the dissolved boundaries are identical to the parent meshblock boundaries.Topology Checks Results: There were no errors in either the gap or overlap checks.GeneralisingTo create the generalised Meshblock layer the “Simplify Polygon” geoprocessing tool was used in ArcGIS, with the following parameters:Simplification Algorithm: POINT_REMOVEMaximum Allowable Offset: 1 metreMinimum Area: 1 square metreHandling Topological Errors: RESOLVE_ERRORSClipping of Layers to CoastlineThe processed feature class was then clipped to the coastline. The coastline was defined as features within the supplied Land2013 with codes and descriptions as follows:11- Island – Included12- Mainland – Included21- Inland Water – Included22- Inlet – Excluded23- Oceanic –Excluded33- Other – Included.Features were clipped using the Data Interoperability extension, attribute filter tool. The attribute filter was used on both the generalised and high definition meshblock datasets creating four meshblock layers. Each meshblock dataset also contained all higher geographies and land-water data as attributes. Note: Meshblock 0017001 which is classified as island, was excluded from the clipped meshblock layers, as most of this meshblock is oceanic. Dissolve meshblocks to higher geographiesStatistics New Zealand then dissolved the ESRI meshblock feature classes to the higher geographies, for both the full and clipped dataset, generalised and high definition datasets. To dissolve the higher geographies, a model was built using the dissolver, aggregator and sorter tools, with each output set to include geography code and names within the Data Interoperability extension. Export to MapInfo Format and ShapfilesThe data was exported to MapInfo and Shapefile format using ESRI's Data Interoperability extension Translation tool. Quality Assurance and rechecking of delivery filesThe feature counts of all files were checked to ensure all layers had the correct number of features. This included checking that all multipart features had translated correctly in the new file.

A combination of stormwater ditch data throughout Stark County, Ohio. Ditches includes roadside ditches, as well as off-road ditches in some areas/instances. 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.