Guide: Create a request

only project managers and workforce managers can create new requests annotation work in the kognic platform is organized and conducted through annotation requests each request specifies what data to annotate, how it should be annotated, the process required, and who is responsible for each task in said process to create a request, you first need a project you can learn how to create a project in the guide create a new project docid\ f4u4tgqwmj1zxpcnznjsh requests can be created in two ways fully from scratch or by using an existing request as a template both ways will be described below create a request from scratch to get started, open the project in which you want to create a new request then, locate the "create request" button at the top right corner of the project page configure the request general configuration request name the request name functions as an identifier in multiple locations ensure you choose a name that makes the request easy to identify request producers the organization with the request role producer is responsible for producing annotated data in the request users from this organization are allowed more detailed monitoring and management options and can configure the request workforce in detail all to ensure they can successfully monitor and manage the production process additional non producer organizations with access to the request will be limited in regard to their monitoring and management options request inputs specify what data the request should contain and where to upload it input batch name and id an input batch is a group of inputs an input is a set of input data that you want to be annotated when creating a request, you need to create an input batch alongside it it is to this input batch you later upload your data to have it annotated in the request input type defines what type of data the input batch can contain input type description lidar and cameras a single frame, containing both camera data (from one or multiple cameras) and lidar data lidar and cameras sequence a sequence of frames, containing both camera data (from one or multiple cameras) and lidar data cameras a single frame of camera data the data can be from one or multiple cameras cameras sequence a sequence of camera frames the data can be from one or multiple cameras aggregated lidars and cameras sequence a sequence of frames, containing both camera data (from one or multiple cameras) and lidar data the lidar data will be aggregated with respect to the first frame of the sequence annotation instruction an annotation instruction specifies what you want to annotate and provides guidance on how to perform the annotation when creating a request, you select which instruction to use as well as which revision (version) read more about annotation instruction on the page annotation instruction docid\ aibhomp8oboyzmbeuvl j request workflow the request workflow defines the specific phases and tasks used to produce and deliver annotations the most suitable workflow for your request will depend on several factors such as quality requirements, time constraints, and budget considerations the currently available workflows are listed and linked below currently available workflows workflow name phases availablity two tier review docid\ nfxqay29jqu2ulbmqvpn7 annotate > full review > sampled review > delivery full two tier sampled review docid\ qlczrsolsxc2jud3uo6xn annotate > sampled review > sampled review > delivery full configuring a default request workflow for your project ensure process consistency in your project by configuring a default request workflow with this setup, all new requests must follow your defined workflow, except those created using the "use request as template" feature learn more about configuring a default request workflow in general settings review error types the error types are available in the feedback tools during review tasks, and during follow up correction tasks if your organization has many error types configured, you might want to select a subset of error types that are relevant for this request you can learn more about error types on the page error types docid 7sa8 gk8s48crtht3ypmz create the request once everything above has been specified, you can create your new request 🎉 prepare the request for production after creating your request, you need to ensure the following things are done upload data to the input batch you can read more about this process in our api documentation if questions remain, reach out to your kognic contact prepare an annotation instruction docid\ aibhomp8oboyzmbeuvl j a guideline and a taxonomy are needed to start the production of annotations in the request these specify what types of annotations should be created in the request and are needed to ensure the relevant information and tools are available to the workforce members the taxonomy and guideline are part of what we call an annotation instruction you can create and publish annotation instructions in the app, see annotation instruction docid\ aibhomp8oboyzmbeuvl j when you have set the revision in annotation instruction to published, kognic will then add the additional settings and set it to ready for production you will then be able to select the revision when creating a request add workforce members to get the data label according to your selected workflow, you need a workforce this workforce will be responsible for completing tasks during production in the tab workforce docid\ fiopd5ytqela7kyahrpyl you can add workforce members and configure what type of tasks they should access and if they should get them automatically or not read more about adding workforce members in the chapter workforce docid\ fiopd5ytqela7kyahrpyl activate automatic task allocation when all configuration is completed and you are ready to start producing annotations in the request we encourage you to activate our automatic task allocation system you can read how the system works and how to activate it in guide automatic task allocation docid\ c7ebfn74omk zk2b3n 9o create a request using an existing request as a template when using an existing request as a template, the new request will use the same input type and workflow as the original request you also have the option of using the same annotation instruction, which saves you time in preparing the request for production if a default request workflow has been configured for the selected request’s project it won’t be considered when using this feature if you don't want your new request to use the same input type and workflow as an existing request in the project, create the request from scratch instead 1\ open the request that you want to use as a template to get started, open the request you want to use as a template for your new request then open the context menu at the top right corner of the page, and select the menu option "use as template" the new request will be created in the same project as the request that is used as a template 2\ configure the request add request and input batch information name the request the request name functions as an identifier in multiple locations ensure you choose a name that makes the request easy to identify name the input batch when creating a request, you need to create a new input batch alongside it to this input batch, you later upload your data to have it annotated in the request an input batch is a group of inputs an input is a set of input data you want to annotate it usually consists of at least one image/frame it can also contain images from several cameras, a point cloud, a video, or a sequence of images 3\ create the request once everything above has been specified, you can create your new request 🎉 4\ prepare the request for production after creating your request, you need to collaborate with kognic to ensure the request is ready for production this means ensuring the following things are done upload data to the input batch you can read more about this process in our api documentation if questions remain, reach out to your kognic contact prepare an annotation instruction docid\ aibhomp8oboyzmbeuvl j and ask kognic to connect it to the request note! this step can be skipped if you selected "use same instruction" in the "use as template" dialog a guideline and a taxonomy are needed to start the production of annotations in the request these specify what types of annotations should be created in the request and are needed to ensure the relevant information and tools are available to the workforce members the taxonomy and guideline are part of what we call an annotation instruction you can create and publish annotation instructions in the app, see annotation instruction docid\ aibhomp8oboyzmbeuvl j when the annotation instruction is published and ready for production, you need to communicate to your kognic contact which request you want to use it for add workforce members to get the data label according to your selected workflow, you need a workforce this workforce will be responsible for completing tasks during production in the tab workforce docid\ fiopd5ytqela7kyahrpyl you can add workforce members and configure what type of tasks they should access and if they should get them automatically or not read more about adding workforce members in the chapter workforce docid\ fiopd5ytqela7kyahrpyl activate automatic task allocation when all configuration is completed and you are ready to start producing annotations in the request we encourage you to activate our automatic task allocation system you can read how the system works and how to activate it in guide automatic task allocation docid\ c7ebfn74omk zk2b3n 9o