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FME Hub user bwn just uploaded a new transformer to the FME Hub.AttributeTruncationCheckerThis Transformer compares Workspace Features to separate Reference Schema Features to find and report where Attribute value string widths exceed the maximum widths of the Reference Schema(s) Attributes/Fields. This allows workflows to detect in advance which Features and Attribute values will likely be Truncated during Writing.The Transformer must have input Reference Schema Feature(s), with it being recommended to use FeatureReader to generate these from a sample/production destination Schema. The workspace features being inspected must have either an Exposed Attribute set to values equal to the corresponding Feature Type Name value as the Schema Feature to compare against, or have this value able to be calculated through an FME expression, otherwise the Features will pass through the Transformer with no comparison/detection performed if it cannot match the inspected features feature type name

FME Hub user lizatsafe just uploaded a new template to the FME Hub.Purpose & ObjectivesThis workspace retrieves closed road JSON data from an API, fragments and flattens the JSON response into line features with attributes, and then writes the data out to a SpatiaLite database. Key TransformersCreator: Creates a single feature to trigger the workspaceHTTPCaller: Makes a GET request to the data sourceJSONFragmenter: Fragments JSON into FME features and attributesData Source(s) - Reader Feature TypeA GET request to Vancouver Open Data: https://opendata.vancouver.ca/api/explore/v2.1/catalog/datasets/road-ahead-current-road-closures/records?limit=5 Data Output - Writer Feature TypeVanRoads.sqlite SpatiaLiteParameters:Table Name: ClosedGeometry: db_linestring CustomizationTo customize this workspace, it is recommended to build the workspace from scratch as your dataset will have different attributes and schema (structure). Instructions to build this workspace: Getting Started with FME F

FME Hub user lizatsafe just uploaded a new template to the FME Hub.Purpose & ObjectivesThis workspace demonstrates identifying street food vendor points that may be impacted by upcoming road construction projects. It illustrates several common spatial and tabular data processing steps.Key TransformersBufferer: buffering line segments (representing noise impact areas from road construction)AttributeValidator: validating attribute valuesSpatialFilter: finding points that intersect polygons (the buffered construction areas)Tester: filtering features based on attribute valuesFeatureJoiner: joining features based on a shared keyAttributeManager: removing and renaming attributesData Source(s) - Reader Feature Typeroad-ahead-upcoming-projects.shp Esri Shapefile - road-ahead-upcoming-projects worksheetfood-vendors CSV - CSVbusiness-licences SQLite - business-licences tableData Output - Writer Feature TypeAffectedVendors Microsoft Excel - Newly created AffectedVendors worksheetParameters:Ov

FME Hub user ardadurmus just uploaded a new transformer to the FME Hub.OvertureMaps Downloader custom transformer allows FME users to directly access and download geospatial data from the OvertureMaps Foundation using DuckDB a high-performance SQL-based analytical database system. Runs with Executable file or command line system variable duckdb or duckdb.exe using System Caller. This transformer retrieving and storing overture map data in a local environment or temp folder that can be accesible during your process enabling integration with FME workflows for further spatial analysis transformation or export into other formats. It's designed for users who need fast access to large-scale open-source geospatial datasets in a seamless and efficient way.Would you like to know more? Click here to find out more details!

FME Hub user takashi.pss just uploaded a new template to the FME Hub.PLATEAU標準製品仕様書第4.x版に基づいて作成された橋梁、トンネル、地下街モデルCityGMLデータについて、位相一貫性に関する品質検査を行います。 使用方法や検査結果についてのお問い合わせは、次のアドレスあてのメールでお願いします。plateau-helpdesk@aigid.jp 今後も必要に応じて、ワークスペースの機能追加、改良をし、FME Hubを更新することがあります。FME Hubを更新した場合は、Slack PLATEAUコミュニティ の「2024技術支援 チャンネル」でお知らせしますので、適宜ダウンロードしてお手元の環境も更新してください。 このワークスペースはいつまでもご利用になれますが、上記のメールやSlackによるサポートは2024年度末で終了します。あらかじめご承知おきくだいますよう、お願いいたします。Would you like to know more? Click here to find out more details!

FME Hub user takashi.pss just uploaded a new template to the FME Hub.PLATEAU標準製品仕様書4.x版に基づいて作成された地形モデルCityGMLデータ (TINRelief) について、位相一貫性等に関する品質検査を行います。 注1: MassPointRelief (gml:MultiPoint) で記述された地形データには対応していません。 注2: TINを構成する三角形の辺が隣接する三角形の辺と共有されていない場合 (辺の一方または両方の頂点が鉛直方向でずれている場合も含む) に「共有先のない辺」エラーが検出されますが、データ作成範囲内に部分的に原典データが存在しない領域 (水域) が穴のように存在した場合に、その境界を構成する三角形の辺も「共有先のない辺」として誤認識されることがあります。この検査項目は標準製品仕様書において品質要求として規定されたものでもありませんので、このエラーが検出されても検査不合格とはしませんが、水域境界以外ではこのエラーが生じていないことをご確認ください。また、「共有先のない辺を検出する」パラメーターに No を設定することにより、「共有先のない辺」エラーの検出を省略することもできます。使用方法や検査結果についてのお問い合わせは、次のアドレスあてのメールでお願いします。plateau-helpdesk@aigid.jp 今後も必要に応じて、ワークスペースの機能追加、改良をし、FME Hubを更新することがあります。FME Hubを更新した場合は、Slack PLATEAUコミュニティ の「2024技術支援」チャンネルでお知らせしますので、適宜ダウンロードしてお手元の環境も更新してください。 このワークスペースはいつまでもご利用になれますが、上記のメールやSlackによるサポートは2024年度末で終了します。あらかじめご承知おきくだいますよう、お願いいたします。Would you like to know more? Click here to find out more details!

FME Hub user takashi.pss just uploaded a new template to the FME Hub.PLATEAU標準製品仕様書第4.x版に基づいて作成された土砂災害警戒区域CitGMLデータについて、位相一貫性等に関する品質検査を行います。 使用方法や検査結果についてのお問い合わせは、次のアドレスあてのメールでお願いします。plateau-helpdesk@aigid.jp 今後も必要に応じて、ワークスペースの機能追加、改良をし、FME Hubを更新することがあります。FME Hubを更新した場合は、Slack PLATEAUコミュニティ の「2024技術支援 チャンネル」でお知らせしますので、適宜ダウンロードしてお手元の環境も更新してください。 このワークスペースはいつまでもご利用になれますが、上記のメールやSlackによるサポートは2024年度末で終了します。あらかじめご承知おきくだいますよう、お願いいたします。Would you like to know more? Click here to find out more details!

FME Hub user takashi.pss just uploaded a new template to the FME Hub.PLATEAU標準製品仕様書第4.x版に基づいて作成された洪水・津波・高潮・内水浸水想定区域モデルCitGMLデータについて、位相一貫性等に関する品質検査を行います。 使用方法や検査結果についてのお問い合わせは、次のアドレスあてのメールでお願いします。plateau-helpdesk@aigid.jp 今後も必要に応じて、ワークスペースの機能追加、改良をし、FME Hubを更新することがあります。FME Hubを更新した場合は、Slack PLATEAUコミュニティ の「2024技術支援」チャンネルでお知らせしますので、適宜ダウンロードしてお手元の環境も更新してください。 このワークスペースはいつまでもご利用になれますが、上記のメールやSlackによるサポートは2024年度末で終了します。あらかじめご承知おきくだいますよう、お願いいたします。Would you like to know more? Click here to find out more details!

FME Hub user martin_ekstrand just uploaded a new transformer to the FME Hub.Uses the ArcGIS for Python API to get information for different item types (currently supported: Layers, WebMaps/Scenes, Web mapping applications, Experiences, Dashboards and Story maps).It outputs metadata for each item and also the connections between items. The AllPortalItems output port outputs one feature per unique item. The other output ports outputs one unique feature per Portal item ID and connection. For example, a Web Map using 3 services will be output as 3 features in the Web Map output port.Each item type is meant to be used as input for the ArcGISAutomagicDocumenterReportGenerator.This transfomer is part of the ArcGISAutomagicDocumenter series. It is meant to be used together with the other transformers, but it can also be used on is own.Sample workflow for the ArcGISAutomagicDocumenter series can be found hereWould you like to know more? Click here to find out more details!

FME Hub user martin_ekstrand just uploaded a new transformer to the FME Hub.Fetches metadata for all tables in an ArcGIS Enterprise geodatabase.Outputs raw data and a metadata_html meant to be used as an optional input for ArcGISAutomagicDocumenterReportGenerator. If you want to create a custom metadata_html, you can use the raw data to overwrite the metadata_html attribute before connecting to ArcGISAutomagicDocumenterReportGenerator.This transfomer is part of the ArcGISAutomagicDocumenter series. It is meant to be used together with the other transformers, but it can also be used on is own.Sample workflow for the ArcGISAutomagicDocumenter series can be found hereNote: this transfomer can be very slow, especially for large databases - you may want to write the result to a database table instead, and use that table as input for the ReportGeneratorWould you like to know more? Click here to find out more details!

FME Hub user martin_ekstrand just uploaded a new transformer to the FME Hub.Uses the ArcGIS Server Rest API to list all services data sources (Enterprise and file geodatabase tables) and publish sources (APRX/MXD).This transfomer is part of the ArcGISAutomagicDocumenter series. It is meant to be used together with the other transformers, but it can also be used on is own. It is meant to be used as an input for the ArcGISAutomagicDocumenterReportGeneratorSample workflow for the ArcGISAutomagicDocumenter series can be found hereWould you like to know more? Click here to find out more details!

FME Hub user martin_ekstrand just uploaded a new transformer to the FME Hub.This transfomer is part of the ArcGISAutomagicDocumenter series. It must be used together with the other transformers.Outputs an index.html file listing:Portal/Online items (currently supported: Layers, WebMaps/Scenes, Web mapping applications, Experiences, Dashboards and Story maps)Standalone ArcGIS Server services - ArcGIS database tables connectionDatabase tables, if you only use the ArcGISServerServices input, you will get a report for published tables. If you also use the SDE_tables_metadata input, you will get a report for all tables in each database, published or not.FME workspaces with an ArcGIS connection (reads or writes ArcGIS tables)In addition, each item (no matter which item type) will get it's own HTML report listing all connections found in both directions. For example, a report of a Web Map will show which services it uses and which tables those services uses. It will also show which applicatio

FME Hub user mkriger just uploaded a new transformer to the FME Hub.SupervisedImageClassificatorOverviewThe SupervisedImageClassificator is a FME Custom Transformer designed for performing supervised image classification on raster datasets, such as satellite or aerial imagery, using machine learning techniques. This transformer automates the process of classifying pixels based on input raster bands and training polygons, producing a classified raster output. It enables users to train their own machine learning models and apply them to perform image classification.RequirementsR installed: Ensure that R is installed on your system. R Interpreter in FME: R must be properly integrated into FME by configuring the RCaller to use R as its interpreter. R Packages: Caret: Used for training machine learning models (install with install.packages("caret")). Terra: Used for raster data manipulation and analysis (install with install.packages("terra")).Inputs and OutputsInputsRed: The red raster ban

FME Hub user ardadurmus just uploaded a new transformer to the FME Hub.Turkish National Topographic Grid System TransformerThis custom transformer generates national topographic map sheets for Turkey based on a given point or area. It uses the official Turkish national grid system to identify and create map sheets corresponding to the input location.Input: Point(s) Line(s) or Area(s)(polygon) within TurkeyOutput: National topographic map sheet(s) based on the national topographic grid system in various scales.Available Scales:1/100,0001/50,0001/25,0001/10,0001/5,0001/2,0001/1,0001/500Key Features:Works with both single points and larger areasAutomatically determines the correct map sheet for the locationSupports various scales for map sheet generationWould you like to know more? Click here to find out more details!

FME Hub user kketola just uploaded a new transformer to the FME Hub.Mass Fetches Sequence Number for Number of FeaturesAllows the ability to query Oracle once for a large group of sequence numbers to be used on the feature set instead of retrieving one by one so that the sequence might be used for multiple transformers and writers throughout the workspace. This is much more performant than querying the sequence for each feature. This is for the case that you need to use the sequence for multiple spots. For individual writes, there is an option in stock writers.Would you like to know more? Click here to find out more details!

FME Hub user takashi.pss just uploaded a new template to the FME Hub.PLATEAU標準製品仕様書第4.x版に基づいて作成された都市設備モデルまたは植生モデルCitGMLデータについて、位相一貫性等に関する品質検査を行います。 使用方法や検査結果についてのお問い合わせは、次のアドレスあてのメールでお願いします。plateau-helpdesk@aigid.jp 今後も必要に応じて、ワークスペースの機能追加、改良をし、FME Hubを更新することがあります。FME Hubを更新した場合は、Slack PLATEAUコミュニティ の「2024技術支援」チャンネルでお知らせしますので、適宜ダウンロードしてお手元の環境も更新してください。 このワークスペースはいつまでもご利用になれますが、上記のメールやSlackによるサポートは2024年度末で終了します。あらかじめご承知おきくだいますよう、お願いいたします。Would you like to know more? Click here to find out more details!

FME Hub user takashi.pss just uploaded a new template to the FME Hub.PLATEAU標準製品仕様書第34x版に基づいて作成された土地利用モデル、都市計画決定情報モデル、または区域モデルのCitGMLデータについて、位相一貫性等に関する品質検査を行います。 使用方法や検査結果についてのお問い合わせは、次のアドレスあてのメールでお願いします。plateau-helpdesk@aigid.jp 今後も必要に応じて、ワークスペースの機能追加、改良をし、FME Hubを更新することがあります。FME Hubを更新した場合は、Slack PLATEAUコミュニティ の「2024技術支援 チャンネル」でお知らせしますので、適宜ダウンロードしてお手元の環境も更新してください。 このワークスペースはいつまでもご利用になれますが、上記のメールやSlackによるサポートは2024年度末で終了します。あらかじめご承知おきくだいますよう、お願いいたします。Would you like to know more? Click here to find out more details!

FME Hub user takashi.pss just uploaded a new template to the FME Hub.PLATEAU標準製品仕様書第r.x版に基づいて作成された交通モデル (道路, 鉄道, 徒歩道, 広場, 航路) CityGMLデータについて、位相一貫性等に関する品質検査を行います。 注1: LOD3の道路・鉄道・徒歩道・広場、交通領域、交通補助領域の面のうち、路肩立ち上がり部などの鉛直の面については、面の向きが識別できずに「面の向き不正」エラーが検出されることがあります。そのため、LOD3についてこのエラーが検出されても不合格とはしませんが、検出結果に基づいてデータを確認のうえ、必要に応じて修正を行ってください。注2: 道路の立体交差部においては、標準製品仕様書の品質要求 No. L-tran-01, 02 に該当するエラー (隣接インスタンス間の重複) と誤認識されることがあります。そのため、このエラーが検出されても不合格とはしませんが、検出結果に基づいてデータを確認のうえ、必要に応じて修正を行ってください。使用方法や検査結果についてのお問い合わせは、次のアドレスあてのメールでお願いします。plateau-helpdesk@aigid.jp 今後も必要に応じて、ワークスペースの機能追加、改良をし、FME Hubを更新することがあります。FME Hubを更新した場合は、Slack PLATEAUコミュニティ の「2024技術支援 チャンネル」でお知らせしますので、適宜ダウンロードしてお手元の環境も更新してください。 このワークスペースはいつまでもご利用になれますが、上記のメールやSlackによるサポートは2024年度末で終了します。あらかじめご承知おきくだいますよう、お願いいたします。Would you like to know more? Click here to find out more details!

FME Hub user takashi.pss just uploaded a new template to the FME Hub.PLATEAU標準製品仕様書第4.x版に基づいて作成された建築物モデルCityGMLデータについて、位相一貫性、一部の属性等に関する品質検査を行います。 注1: 現時点では標準製仕様書の品質要求No.L-bldg-03「LOD3建築物の開口部が境界面内にあること」、および、標準製品仕様書第3.x版,4.x版で追加され品質要求についての検査処理は未実装です。注2: 3次メッシュ区画境界をまたぐ建築物の所属先メッシュ区画 (ファイル) の判定にあたって使用した3次メッシュ区画境界座標の精度が低い (有効桁数が小さい) 場合、このツールは異なる判定をして「図郭不正」エラーを検出することがあります。使用したデータの精度に依存することなので「図郭不正」エラーが検出されても不合格とはしませんが、標準製品仕様書の規定に基づいて所属先ファイルが決定されていることを再確認してください。使用方法や検査結果についてのお問い合わせは、次のアドレスあてのメールでお願いします。plateau-helpdesk@aigid.jp 今後も必要に応じて、ワークスペースの機能追加、改良をし、FME Hubを更新することがあります。FME Hubを更新した場合は、Slack PLATEAUコミュニティ の「2024技術支援 チャンネル」でお知らせしますので、適宜ダウンロードしてお手元の環境も更新してください。 このワークスペースはいつまでもご利用になれますが、上記のメールやSlackによるサポートは2024年度末で終了します。あらかじめご承知おきくだいますよう、お願いいたします。Would you like to know more? Click here to find out more details!

FME Hub user sids_halton just uploaded a new template to the FME Hub.The Environmental Registry of Ontario (ERO) website is a platform provided by the Ontario government of Canada that allows the public to stay informed about environmental matters and participate in decision-making processes. It allows public to search for various environmental notices, proposals, and decisions. This information is valuable for individuals, organizations and businesses interested in how government decisions might impact the environment in Ontario. Extracting data from ERO platform involves interacting with the website's search engine, navigating multiple pages of results, and accessing detailed spatial and non-spatial information within each record. Manually navigating through pages and pulling relevant information can be time-consuming. This workspace demonstrates how to automate the data extraction process from the ERO website using FME Workbench and output the results into a spatial format such a

FME Hub user oliver.morris just uploaded a new transformer to the FME Hub.OverviewThis transformer works with Azure OpenAI and supports vision models including GPT4 and GPT4o. This transformer enables FME to pass images to the model and answer questions about the images with a text response.An Azure OpenAI deployment is required, including an API Key. Azure OpenAI OverviewMore information about the models, including limitations: https://platform.openai.com/docs/guides/visionCurrently this transformer supports JPG, JPEG and PNG file formats of any size or dimension.This is a ‘no cost’ Publisher Tensing License: It has no license restrictions.If you have any questions regarding this transformer please email uk@avineon-tensing.comTensing is a partner of Safe Software and a Value Added Reseller, with over 80 FME Certified Professionals and FME Certified Trainers in the Netherlands, UK, France and Belgium. Tensing provides bespoke training services, consultancy and technical support for bot

FME Hub user sids_halton just uploaded a new template to the FME Hub.The Environmental Registry of Ontario (ERO) website is a platform provided by the Ontario government of Canada that allows the public to stay informed about environmental matters and participate in decision-making processes. It allows public to search for various environmental notices, proposals, and decisions. This information is valuable for individuals, organizations and businesses interested in how government decisions might impact the environment in Ontario. Extracting data from ERO platform involves interacting with the website's search engine, navigating multiple pages of results, and accessing detailed spatial and non-spatial information within each record. Manually navigating through pages and pulling relevant information can be time-consuming. This article demonstrates how to automate the data extraction process from the ERO website using FME Workbench and output the results into a spatial format such

FME Hub user sanaeatsafe just uploaded a new transformer to the FME Hub.DescriptionThis transformer leverages the Cityworks REST API to send employee labour costs to work orders within Cityworks from FME. It is designed to be used with an authenticated web connection to Cityworks.DetailsThis transformer uses an HTTPCaller to make a call to Cityworks REST API. The API returns a response body that is parsed and made into attributes using JSONExtractor. Additional information and context can be found in the _response_body attribute. Tester transformers reroute Cityworks generic error page in addition to Error and Warning messages to the <Rejected> port. Additional parameters can be provided in the Additional Request Parameters field to send a more detailed request to Cityworks. Would you like to know more? Click here to find out more details!

FME Hub user dmitribagh just uploaded a new transformer to the FME Hub.The transformer enables importing of USDZ files into FME using Blender as an intermediary. This transformer converts USDZ files to a format that FME can read (Collada), preserving the geometry, colors, and textures of the original model.InputThe transformer accepts USDZ files as input. These files can be imported from your local file system.OutputThe output is an FME-native 3D model representation.ParametersPath to BlenderThe file path to the Blender executable. Ensure this points to the Blender application on your system to enable the conversion.USDZ file(s)The file path(s) to the USDZ file(s) that you want to import.Usage notesBlender Installation: Ensure Blender (https://www.blender.org) is installed on your system and the path to the Blender executable is correctly set in the transformer parameters.Material Properties: While Collada supports various material properties, not all properties from USDZ may be accura

FME Hub user lizatsafe just uploaded a new template to the FME Hub.Purpose & ObjectivesThis workspace demonstrates how to read data from a Microsoft Excel workbook containing employee information, filter for active employees using a transformer, and write the filtered data to a new worksheet in the same workbook.Key TransformersTester: Used to filter the data based on conditional statementsData Source(s) - Reader Feature TypeEmployeeRecord.xlsx Microsoft Excel - Employees worksheetData Output - Writer Feature TypeEmployeeRecord.xlsx Microsoft Excel - Newly created Active worksheetParameters:Drop Existing Sheet set to Yes (the sheet will be dropped and recreated each time the workspace is run)CustomizationTo customize this workspace, it is recommended to build the workspace from scratch as your dataset will have different attributes and schema (structure). Instructions to build this workspace: Getting Started with FME Form: Working with Table/Tabular Data. Additional ResourcesMicros