Explanation: Skill Harmonization
TechWolf is set on playing nice in the Skills ecosystem. This means we must be able to speak everyone’s language. Languages have dictionaries to translate between them; for skills we have mappings.
Mapping
Comparing two ontologies and creating the most optimal translation between skills themselves generates a mapping.
Additionally, when we translate full sentences between languages (French and Mandarin Chinese), we don’t translate each word individually, context is important. This is also the case for translating skill profiles for entities. Simply translating each skill without context does not drive optimal value and insights.
Harmonization
Skill harmonization is the process of using the mapping to display the correct set of skills for an entity, in different ontologies.
The difference is best explained using an example. See the mapping and harmonization sections.
Lastly, just like French and Mandarin Chinese translation has its own peculiarities compared to Hindi to Italian, mapping and harmonizing skills between TechWolf and different vendors can have its own peculiarities. We strive to reduce the amount of such differences.
Example: Mapping
Consider the following mapping from Vendor 1 to Vendor 2.
| Skill Vendor 1 | Skill Vendor 2 |
|---|---|
| Python 3.12 (Programming) | Python |
| Python 3.13 (Programming) | Python |
| Power BI | Microsoft Power BI |
| JavaScript (Web Development) | JavaScript |
| Data Analytics | Data Analysis |
| AI & Machine Learning | Machine Learning |
| SQL Database Querying | SQL |
| UX Design | User Experience Design |
While Vendor 1 has two representations for the skill python, Vendor 2 only has
one. As we want both Vendor 1 skills to be correctly mapped, they both map to
the same skill for Vendor 2.
It is clear what should be done when we map from Python 3.12 (Programming) to
Python. The other way around is more complex, as a decision has to be made:
- add
Python 3.12 (Programming) - add
Python 3.13 (Programming) - add both
TechWolf leverages complex algorithms to figure out the most optimal skill, and
selects only one as “primary” mapping (for example, 2. in the scenario above).
Each skill in both TechWolf and vendors can have multiple mappings in TechWolf, with an order of precedence for each mapping item. The primary mapping is the highest ranked mapping and is most often the closest (an exact match is ideal).
Example: Harmonization
Now that we know the mapping, we can translate profiles. This is where harmonization is used. Consider Lisa, a junior software engineer:
| Skill Vendor 1 Skill |
|---|
| Python 3.12 (Programming) |
| Power BI |
| JavaScript (Web Development) |
| Data Analytics |
| AI & Machine Learning |
| SQL Database Querying |
| UX Design |
If we want to harmonize Lisa’s profile, we must map her
Python 3.12 (Programming) skill to Python in Vendor 2. But now Lisa’s
profile is not following the most optimal mapping anymore! (that would be to
change her original profile to contain Python 3.13 (Programming), but that
would change Lisa’s original input).
Instead, when we harmonize, we keep track of all existing skills, and will opt for using non-primary mappings when it drives consistency in profiles.
TechWolf considers existing profiles when harmonizing profiles between ontologies, and will keep the non-primary skills in user input to drive consistency and trust.
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