Exhibit_02_-_Technical_Requirements.pdf

EXHIBIT 2 – TECHNICAL SPECIFICATIONS

1. Architecture & Frameworks:

Describe the overall system architecture including front-end frameworks (e.g., React, Angular), back-end microservices (using containerization technologies like Docker/Kubernetes), and the data storage solutions (e.g., cloud-based data warehouse).

2. Data Integration & ETL Processes:

Detail the mechanisms for data ingestion, transformation, and loading, including real-time data updates where applicable. Specify how ETL processes will be designed following best practices (e.g., referencing DAMA-DMBOK).

3. API Integration & Standards:

Outline the API strategy, ensuring the dashboard exposes secure, standard APIs (RESTful or GraphQL) with comprehensive documentation (using OpenAPI specifications) for integration with external systems.

4. Interactive Visualizations & Reporting:

Define the types of visualizations (e.g., interactive maps, charts, graphs) to be provided, ensuring they meet accessibility standards (WCAG 2.1) and are optimized for performance and usability.

5. Scalability & Performance:

Explain how the solution will scale (both horizontally and vertically) and include performance benchmarks (e.g., load times, response times under concurrent usage).

6. Security & Compliance:

Specify security measures to protect sensitive data, including encryption, access controls, and adherence to industry standards (NIST SP 800-53 or ISO/IEC 27001).

7. Development & Deployment Methodologies:

Detail the agile/DevOps practices to be employed, including continuous integration, automated testing (unit, integration, and performance tests), and a defined process for incremental updates and deployment.

8. User Experience (UX) & Accessibility:

Describe the design approach to ensure an intuitive, user-friendly interface that is accessible to all users, in compliance with WCAG 2.1, and includes provisions for iterative user feedback.

9. Documentation & Support:

Outline the plan for technical documentation including system architecture diagrams, data dictionaries, API guides, and user manuals, as well as post-deployment maintenance and support procedures. This task may include but is not limited to providing data, maps, figures, and reports for current and predicted workforce needs and opportunities, and impacts, etc.

The dashboard must also integrate AI-driven scenario analysis and simulation model outputs, allowing user inputs for generating predictive insights. Comprehensive documentation must be provided, including:

• A Technical Architecture Document (aligned with IEEE 1016 and TOGAF standards)

• A complete Data Dictionary and ETL process guide

• API Documentation following OpenAPI specifications

• End-user and technical manuals, including troubleshooting guides and video tutorials.

10. Best Practice Guidance

a. Offer expertise and guidance on best practices for automated data collection and development of dashboards and data integration.

b. Ensure compliance with industry standards including NIST SP 800-53 (or ISO/IEC 27001), WCAG 2.1, and OpenAPI for API documentation.

c. Collaborate with internal teams to troubleshoot issues and optimize existing solutions.

11. Stakeholder Collaboration

a. Plan specific workshops tailored to different target groups to address their unique needs and concerns.

b. Workshops should be designed to evaluate the proposed platform and dashboard, collect feedback and suggestions, and encourage collaboration among stakeholders.

c. Document all stakeholder interactions, including meeting minutes and feedback reports.

12. Dashboard Creation:

a. Design and develop visually appealing and user-friendly dashboards and data system.

b. Utilize industry best practices in UI/UX design and ensure compliance with WCAG 2.1 accessibility standards.

c. Customize dashboards to meet specific business requirements and user needs.

d. Ensure data accuracy, consistency, and relevance in the presented visualizations.

13. Data Source Analysis:

a. Identify and integrate new data sources relevant to the workforce development space in Oklahoma.

b. Follow data governance best practices as outlined in DAMA-DMBOK.

c. Evaluate the quality, accuracy, and timeliness of the data.

d. Access the compatibility of data sources with an integrated model.

e. Establish secure and efficient data connections, ensuring data integrity and reliability.

f. Optimize data retrieval processes to minimize latency and maximize performance.

14. Framework Development for Automated Data Retrieval

a. Design a framework for automated data retrieval.

b. Integrate the framework with the integrated workforce model.

c. Conduct testing to ensure seamless data updates.

d. Design a tool to extract and analyze relevant data from the model on the availability, usage and impact of workforce development across the State of Oklahoma.

e. The framework should adhere to industry standards for data security and performance.

15. Reporting and Documentation

a. Maintain detailed records of all interactions, feedback, and suggestions provided by stakeholders.

b. Generate regular reports on the progress of product design and the degree of stakeholder participation on a schedule to be determined by OWC.

c. Document all processes, updates, and calibration steps.

d. Prepare a comprehensive report outlining findings, recommendations, and the updated system capabilities.

e. Reports should include compliance documentation with relevant industry standards.

16. Dashboard Design and Development

a. Select a suitable platform or tool for creating the dashboard.

b. Design the dashboard layout, visualizations, and interactive components to effectively communicate insights.

c. The solution should be built with a modular and scalable architecture (e.g., microservices) and expose standard APIs (following OpenAPI standards) for integration with other systems.

d. Each domain should have its own set of visualizations, such as maps, graphs, and charts.

e. Ensure that federal performance measure and can be reported, where applicable.

17. Integrate Simulation Model into Dashboard

a. Integrate the simulation model into the Dashboard

b. The dashboard should show the model outputs and have some options to take inputs from the user and produce relevant predictions or trends.

c. This integration must support AI-driven scenario analysis as part of the predictive modeling.

18. Real-time Data Integration (if applicable)

a. If real-time data is available, implement mechanisms to update the dashboard with the latest information periodically.

b. Ensure that real-time integration adheres to industry best practices for data security and performance.

19. User Interface and Interactivity

a. Focus on user experience by making the dashboard intuitive and user-friendly.

b. Users should be able to interact with the dashboard, selecting regions (select cities, counties, census block groups, or a specific area using selection tools like polygons, rectangles, and similar options), time frames, and specific metrics of interest.

UI/UX design must comply with WCAG 2.1 standards to ensure accessibility for all users.

20. Testing and Quality Assurance

a. Thoroughly test the dashboard to ensure its functionality, accuracy, and responsiveness.

b. Identify and fix any bugs or issues.

c. Testing protocols should include unit, integration, and performance testing aligned with industry best practices.

21. On-Demand Consulting:

Provide consulting services as needed, responding promptly to requests for assistance.

22. User Guide Tools

a. Create a comprehensive user guide that explains how to use the dashboard. Include step-by-step instructions on accessing the dashboard, navigating through its various sections, and making the most of its features.

b. Ensure that all user guides and technical documentation are maintained in accordance with industry best practices.

c. Data Dictionary: Provide a data dictionary that defines each variable, metric, or dataset used in the dashboard. Include descriptions, data sources, units of measurement, and any transformations performed on the data.

d. FAQs: Anticipate common questions and issues users might encounter and create a frequently asked questions (FAQ) section in the documentation.

e. Technical Documentation: For users who want to delve deeper into the technical aspects, provide documentation on the architecture, data sources, predictive models used, and any APIs or data pipelines involved.

f. Updates and Versioning: Specify how updates and version changes to the dashboard will be communicated to users. This ensures that users are aware of improvements or changes that might affect their use of the dashboard.

g. Troubleshooting: Include a section on troubleshooting common problems or errors users might encounter while using the dashboard.

23. Onboarding and Training:

a. Conduct training sessions for staff and potential users, especially for the first dashboard launch. These sessions can be in-person or virtual, depending on the audience's location.

b. Create video tutorials that walk users through various tasks and features of the dashboard.

This allows users to learn at their own pace and serves as a valuable resource for new users

c. Offer advanced training sessions for staff who need to extract deeper insights from the dashboard. These sessions can cover topics like interpreting predictive model outputs or performing custom analyses.

d. Use feedback from users during training sessions to make continuous improvements to both the dashboard and the training materials.

24. Deployment and Maintenance

a. Establish a plan for ongoing maintenance, updates, and data refreshes.

b. Implement necessary security measures to protect sensitive data and ensure compliance with privacy regulations.

c. Maintenance plans should include provisions for regular security updates and adherence to standards such as NIST SP 800-53 or ISO/IEC 27001.

25. Advisory Committee Meetings

a. A Project Advisory Committee (PAC) made up of regional partners will help advise OWC and the consultant throughout the process. Updates to the platform will be provided and feedback will be received to improve user interactivity and presentation of data.

b. Meetings to provide updates regarding the proposed platform and dashboard.

c. Meetings to evaluate the final version.

26. Board Review/Approval

OWC Commissioners will be informed throughout the development of the proposed platform and dashboard. At key milestones of the project, presentations may be made to share progress and seek input. It’s anticipated that up to three presentations may be made to OWC Commissioners or State Officials. Presentations should include evidence of adherence to the defined industry standards and detailed documentation of the transition process.