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Introduction
The Knowledge Management (KM) Capability sits at the intersection of enterprise platform service design, semantic data engineering, and taxonomy governance for the organization. The team operates in a multi-faceted role, which includes performing complex data analysis to improve knowledge representation and consumption of unstructured data in systems, develop data transformation pipelines that join multiple data sets in the ASML knowledge graph, and collaborating across the organization to help define the customer experience for knowledge discovery and access on the Progress Semaphore platform. Members of the KM team own the end-to-end development of knowledge graph features for ASML recommendation engines, data, and content domains, using both industry standards and proprietary technical tools.

Role and responsibilities
Planning & Design
Define Technical Architecture: Develop a comprehensive technical architecture for the taxonomy and ontology management system, including components, data flow, and integration points with existing systems.
Select Technology Stack: Choose the appropriate technology stack (e.g., database, server, programming languages) that aligns with the organization's infrastructure and project requirements.

Stakeholder Engagement
Provide training and support to stakeholders on how to use the new taxonomy and ontology management system effectively

Proof of Concept
Technical Design of PoCs: Collaborate with stakeholders to design the technical framework for the two PoCs, including defining the scope, objectives, and success criteria.
Setup PoC Environment: Configure the necessary environments (development, testing) for conducting the PoCs, ensuring that all required tools and resources are available.
Oversee PoC Execution: Manage the technical execution of the PoCs, ensuring that the systems are functioning as intended and that any technical issues are promptly addressed.
Evaluate Technical Outcomes: Analyze the technical results of the PoCs, including performance metrics, user feedback, and system behavior, to determine feasibility for full implementation.

Security Requirements
Identify Security Standards: Work with the security team to identify relevant security standards and compliance requirements that the taxonomy and ontology management system must meet.
Conduct Security Assessments: Facilitate technical security assessments, including vulnerability scans and penetration testing, to identify potential security risks.
Implement Security Measures: Ensure that appropriate security measures are implemented, such as data encryption, access controls, and secure coding practices.

Access Management
Define SSO Requirements: Collaborate with IT and security teams to define the technical requirements for enabling SSO authentication, including supported identity providers and protocols (e.g., SAML, OAuth).
Configure SSO Integration: Oversee the technical configuration of SSO within the taxonomy and ontology management system, ensuring seamless integration with existing authentication mechanisms.
Testing and Validation: Conduct thorough testing of the SSO implementation to ensure that it works correctly across different user scenarios and that users can access the system without issues.
TOMS access approval flow: Ensure right people have right access to manage taxonomy in the tooling

Integration with internal systems
Identify Integration Points: Work with stakeholders to identify key technology platforms (e.g., document management systems, CRM, ERP) that need to be integrated with the taxonomy and ontology management system.
Develop Integration Strategy: Create a technical strategy for integrating the systems, including defining APIs, data formats, and communication protocols.
Initiate Development of Integrations: Coordinate with development teams to initiate the technical development of integrations, ensuring that they align with the overall project timeline and architecture.
Monitor Integration Progress: Regularly monitor the progress of integration efforts, addressing any technical challenges or roadblocks that arise during the development process.

Quality Assurance & Testing
Establish Testing Protocols: Define testing protocols for the taxonomy and ontology management system, including unit testing, integration testing, and user acceptance testing (UAT).
Conduct Testing: Oversee the execution of testing activities, ensuring that all components of the system function correctly and meet performance requirements.
Address Defects: Manage the process of identifying, documenting, and resolving defects or issues discovered during testing.

Documentation & Knowledge Transfer
Create Technical Documentation and keep up to date: Develop comprehensive technical documentation for the taxonomy and ontology management system, including architecture diagrams, API documentation, and user guides.
Facilitate Knowledge Transfer: Ensure that technical knowledge is transferred to relevant teams, including IT support and system administrators, to facilitate ongoing maintenance and support.

Change Management & Training
Design and implement training programs to educate users on the new taxonomy and ontology management system, ensuring they understand how to use it effectively.

Project Monitoring & Reporting
Develop and maintain reports that highlight key performance indicators related to the taxonomy implementation, such as user adoption rates, search effectiveness, and content categorization accuracy, by regularly reporting on KPIs helps stakeholders understand the impact of the taxonomy on organizational processes that support in data-driven decision-making.

Post-Implementation Support & Maintenance
Monitor System Performance: After implementation, monitor the performance of the taxonomy and ontology management system to ensure it meets operational requirements.
Implement Maintenance Procedures: Establish procedures for regular maintenance, updates, and enhancements to the system based on user feedback and changing organizational needs.
Provide Technical Support: Offer ongoing technical support to users and stakeholders, addressing any issues or questions that arise post-implementation.

Risk & Governance
Identify potential risks such as inconsistencies, misalignment with business needs, or user resistance and proactively address risks to minimize disruptions and ensure a smoother implementation.
Contribute to the development of the governance framework supporting the governance model to ensure consistency and accountability in taxonomy usage, helping to maintain data integrity and quality.

Experience and skills
Experience of working with Graphwise PoolParty software.
Experience designing, developing, and managing taxonomies and ontologies for enterprise use.
Strong understanding of metadata modeling, governance, and versioning to ensure consistency across systems.
Familiarity with auto-tagging implementation and optimization using taxonomy management systems.
Experience configuring and maintaining taxonomies for automated tagging in SharePoint.
Knowledge of integrating taxonomy structures with API-driven workflows, including MuleSoft-based implementations.
Understanding of SKOS, RDF, OWL, SPARQL, and other semantic web standards for structuring taxonomies and ontologies.
Ability to conduct taxonomy audits, gap analyses, and performance monitoring to improve tagging accuracy.
Experience collaborating with engineering, IT, and business teams to align taxonomy efforts with enterprise data strategy.
Strong analytical and problem-solving skills for refining taxonomy structures and ensuring usability.
Ability to document taxonomy frameworks, tagging guidelines, and governance policies for long-term scalability.