NASA (National Aeronautics and Space Administration) implemented a knowledge graph for identifying well-trained and motivated staff, particularly for filling critical positions from its ranks for the Artemis-2-Mission. The knowledge graph enabled their HR (Human Resources) managers to recognize and promote the full potential of the employees. It also helped establish the relationships between the diverse expertise of its pool of specialists and their skills.
NASA began the implementation of the knowledge graph by first developing a taxonomy to classify both the extensive job requirements and the various personal characteristics simply and clearly. The data scientists followed the KSAO classification (Knowledge, Skills, Abilities, and Other Characteristics), which offered a framework for assessing potential candidates for a particular role. Additionally, they used the O * NET Online of the US Department of Labor and the classification system ESCO (European Skills, Competences, Qualifications, and Occupations) for classification. Using the taxonomy, the team developed categories for nodes and edges in the next step, created a data model for the knowledge graph, and integrated important personnel data.
The knowledge graph offered a semantic context so that competence profiles could be viewed on a project-specific basis or in connection with specific training courses. At the click of a mouse, personnel characteristics and particular combinations of skills and competencies could be queried in a targeted manner and compared with the job requirements of a position. Implementing a knowledge graph opened the door to recognizing patterns and relationships contained in data, refine search using artificial intelligence and machine learning. If used correctly, it would help optimize the accuracy of machine learning models and make talent management smart.
For NASA, the potential of knowledge graphs for human resource management is vast. The search for experts for the planned lunar mission in 2024 is just one of the many tasks. Qualified specialists are also required for other projects. Significantly, knowledge graphs in connection with KI, ML, and NLP allow NASA’s HR managers to think outside the box and open up new, more creative ways of talent management.
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