People's knowledge and skills connect companies with consultants and employees. Mapping skills also maps the IT landscape. We use the graph database #Neo4J to show some examples. This presentation was given as part of the 2018 GraphTour by Neo4J.

1. Mapping the IT Landscape
as a Knowledge Graph
Ignaz Wanders

2. IT consultancy business
Companies Consultants

3. IT consultancy business
Customers Consultants
Skills
Company
:KNOWS
:WORKS_FOR
:DELIVERS
:SEARCHES

4. By publicly searching for skills, companies give
a little bit of information about their internal
business.
Companies like Vector.Consulting offer skills
through the knowledge of the consultants, both
employees and freelancers.
Consultants show off their skills through all kinds
of media, notably a CV, but also through
presence in social media and other channels.

5. Skills are central
๏ Matching consultants to customer requests
๏ Who is the best available consultant for the requested job?
๏ Knowing which companies seek what skills
๏ Who are my most important customers?
๏ Watching skill trends
๏ Do consultants need to learn new skills?

6. The conceptual model
Consultant Skill Opening Customer
Vectr.
Consulting
:WORKS_FOR :KNOWS
:NEEDS
:OFFERS
:INTERESTED_IN

7. Automated flow
๏ Customer submits a job opening, requesting specific skills
๏ Opening is scanned for skills and added to the model
๏ Consultants are scored against the opening
๏ Notification sent via Slack channel
๏ When consultant has
new skill, it is added to
the model
๏ New consultants are
also added to the model
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10. testing
agile
scrum
jira
java
oracle
css
COMPANY
COMPANY

13. MATCH (m:Monitor {name: “vectr"})-[]-(s:Skill)
RETURN m,s
Our skill ontology

14. MATCH (m:Monitor {name: "vectr"})-[]-(s:Skill {name: “neo4j"})-[]-
(o:Opening)<-[]-(c:Company)
RETURN m,s,o,c

15. MATCH (m:Monitor {name: "vectr"})-[:INTERESTED_IN]-(s:Skill {name: “iot"})-
[:NEEDS]-(o:Opening)<-[:HAS]-(c:Company)
RETURN m,s,o,c

16. MATCH (s:Skill)-[:NEEDS]-(o:Opening)<-[:HAS]-(c:Company {name: "Digipolis"})
RETURN s,o,c

17. MATCH (s:Skill)-[:NEEDS]-(o:Opening)<-[:HAS]-(c:Company {name: "Digipolis"})
WITH s,count(o) as openings
RETURN s,sum(openings) ORDER BY sum(openings) DESC

18. Key take aways
Ontology for your business
Connect ontology and dynamic business entities in a graph
Matching, mapping, trending
Graphs provide excellent business insights