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A Technology Service to Realize Intelligent Assessments

Prediction Services

Assessment Service Architecture

This project is composed of services and resources to implement, configure and deploy intelligent assessments services for a specific domain utilizing AI techniques to infer contextual information derived from implicit relations.

The implementation follows a service-oriented approach to provide the required flexibility with respect to domain-specific adaptation (during data collection and analysis phases). This flexibility results in the implementation of service for data collection, enhancement and visualisation .

Each service is implemented technically as a function that is deployable in your own AWS Lambda. Controller and support services are provided to handle composite tasks that involve several other service of different types.

The deployment process is supported by powershell scripts that build on AWS CLI to run your services in the cloud.


We encourage you to contribute to the project! Feel free to branch the code repository, commit your changes and comment on your/other implementation results Join us!

In case of technical inqueries, please use the Issues functionality in our source code management system. This allows us to collaborate and support individual endevours.

Quick Start

Follow the steps below to have your first assessment service up and running!



Download the source code to your local machine

git clone https://code.omilab.org/services/assessment-service.git

The repository contains all service source code, deployment scripts, documentation for implementation, deployment and usage as well as example cases.


The source code of the services can be found in https://code.omilab.org/services/assessment-service/-/tree/master/src and each service type is complemented with the necessary deployment scripts.

In case you want to evaluate the current functionality, skip this step and deploy the available AWS Lambda functions directly.


Scripts are available (called deploy_…ps1) that perform the code integration/packaging and deployment in AWS and return the routes to the service (as a text file called AWSRoutes-….txt). The script can be controlled using deployment command defined here

Run the following commands to perform the initial deployment using PowerShell. Replace the “lambda-role” with the AWS role created during account setup.

# deployment of HTMLFormQuestionnaire
controller-services/HtmlFormQuestionnaire/deploy_HtmlFormQuestionnaire.ps1 -LambdaRoleName "lambda-role" -Verbose

# deployment of question-services (including the required dynamoDB tables)
question-service/deploy_allQS.ps1 -LambdaRoleName "lambda-role" -Verbose

# deployment of enhancement-services
enhancement-services/deploy_allEHS.ps1 -LambdaRoleName "lambda-role" -Verbose

# deployment of visualisation-services
visualization-services/deploy_allVIS.ps1 -LambdaRoleName "lambda-role" -Verbose

The result of the above deployments are service endpoints that are used to configure the concrete assessment service.

Follow the steps outlined here to configure your first basic questionnaire service.

A Technology-Service by OMiLAB (info@omilab.org).