This document discusses how NASA uses knowledge graphs and algorithms to identify hidden skills in employees. It explains that enterprise knowledge graphs combine structured and unstructured data to enable faster search and decision making. NASA creates knowledge graphs using tools like Neo4j and analyzes the graphs using algorithms like node similarity. The knowledge graphs connect data on occupations, skills, abilities, and projects. The graphs can be used to discover employee skills, support diversity initiatives, and compare occupations based on required skills. Contact information is provided for two NASA data scientists working on these knowledge graphs.

1. National Aeronautics and Space Administration
www.nasa.gov
KSATT - Knowledge, Skills,
Abilities, Tasks and Technology
David Meza
Sr. Data Scientist
Office of the Chief Human Capital Officer
1
Combining Knowledge Graphs and Algorithms to Find
Hidden Skills

2. HR Executives Say Skills Most Important
2

3. Enterprise Knowledge Graphs
• Enterprise Knowledge Graphs help companies create their
specific web of knowledge representing their very own domain. As
a result, they can seamlessly break down data silos to use
information assets in an agile way.
• Brings together structured and unstructured data
• Speedier search enabling faster decisions
• Can connect knowledge graphs across domains
• Algorithms (NLP)
• Text annotation
• Knowledge graph enrichment – Path Finding, Centrality, Community Detection
• Text rank
• Similarity
• Sentiment analysis

4. Creating Knowledge Graphs
Tools Used
• Neo4j
• Graph algorithms – node similarity
• Evaluating graph neural nets (gnn)
• Python / R
• Doc2vec
• Entity extraction
• BERT, RNN and Spacy
4

5. Comparison – RDF - LPG
5

6. KSAT Knowledge Graph Model Workflow
6

7. Different Domain Sources
7

8. ONET-SOC 2019 Taxonomy
8

9. KSATT Data Model

10. Expand Model to Create Profiles

11. Connect to External Data Sources

12. Connect to Mission Data

13. KSATT DATA MODEL
13

14. 14

15. 15

16. KSATTs by Project
16

17. Graph Data Science
17
Courtesy of Dr. Alicia Frame, Neo4j

18. Algorithms
Node Similarity
compares a set of nodes based
on the nodes they are
connected to. Two nodes are
considered similar if they share
many of the same neighbors.
Node Similarity computes pair-
wise similarities based on the
Jaccard metric, also known as
the Jaccard Similarity Score.
18
// Compare IT jobs with Program Analyst
CALL gds.graph.create.cypher(
'IT_Program_Knowledge',
'MATCH (n) WHERE (n:Occupation) OR (n:Knowledge) RETURN id(n) AS id',
'MATCH (opm:OPM_Series)-[r:IN_OPM_SERIES]-(occ:Occupation) WHERE
opm.title IN ["GS-2210", "GS-0080", "GS-0340", "GS-0343"] WITH occ, opm
MATCH (occ)-[f:FOUND_IN]-(s:Knowledge) WHERE f.IM > 0.5 RETURN id(occ)
AS source, id(s) AS target'
)
// Stream Reuslts
CALL gds.nodeSimilarity.stream('IT_Program_Knowledge')
YIELD node1, node2, similarity
WHERE gds.util.asNode(node1).title = 'Management Analysts'
RETURN gds.util.asNode(node1).title AS Occupation1,
gds.util.asNode(node2).title AS Occupation2, similarity
ORDER BY similarity DESCENDING, Occupation1, Occupation2

19. Career Change
19
Occupation1 Occupation2 similarity
Management Analysts Information Technology Project Managers 72.22%
Management Analysts Document Management Specialists 68.75%
Management Analysts Sustainability Specialists 68.42%
Management Analysts Online Merchants 62.50%
Management Analysts Business Continuity Planners 61.11%
Management Analysts Health Informatics Specialists 60.00%
Management Analysts Database Administrators 52.94%
Management Analysts Information Security Analysts 47.06%
Management Analysts Web Administrators 47.06%
Management Analysts Computer Network Support Specialists 44.44%

20. Discover Connections

21. Support DEI Initiatives

22. Rank Skills by Occupation
OPM Occupation SOC Group Element Value
GS-1550
computer and information research
scientists
15-
1111.00
['Basic_Skills
']
understanding written sentences and paragraphs in work
related documents. 4.5
GS-1550
computer and information research
scientists
15-
1111.00
['Basic_Skills
'] using mathematics to solve problems. 4.38
GS-1550
computer and information research
scientists
15-
1111.00
['Basic_Skills
']
giving full attention to what other people are saying, taking time
to understand the points being made, asking questions as
appropriate, and not interrupting at inappropriate times. 4.12
GS-1550
computer and information research
scientists
15-
1111.00
['Basic_Skills
']
communicating effectively in writing as appropriate for the
needs of the audience. 4.12
GS-1550
computer and information research
scientists
15-
1111.00
['Basic_Skills
'] talking to others to convey information effectively. 4.12
22
MATCH (opm:OPMSeries)-[r:IN_OPM_Series]-(occ:Occupation)
WHERE opm.series IN ["GS-2210", "GS-1550", "GS-854", "GS-855"]
WITH occ, opm
MATCH (occ)-[f:Found_In]-(s:Basic_Skills)
WHERE f.datavalue > 3.75
RETURN opm.series AS OPM, occ.title AS Occupation, occ.onet_soc_code AS SOC, labels(s) AS Group, s.description AS Element, f.datavalue AS
Value
ORDER BY Value Descending

23. Employees Similar to an Occupation Based on Abilities
23
Similarity Employee
35Bradford
29Constance
29Craig
29David
29Eric
29Jason
29Mehti
29Naimah
29Steven
29Ted

24. Contact Information
David Meza – david.meza-1@nasa.gov
Twitter - @davidmeza1
Linkedin - https://www.linkedin.com/in/davidmeza1/
Github – davidmeza1
Madison Gipson
Website: https://madisongipson.com/
LinkedIn: https://linkedin.com/in/mgip
Github: https://github.com/mgipson
Email: madison.gipson@nasa.gov or mgipson@stetson.edu