Create a Word Model to generate Taxonomy for catalog.data.gov categories

[nickumia-reisys]

User Story

In order to make data more discoverable on catalog.data.gov, the Data.gov NLP team wants to create model from which a word taxonomy can be created.

Acceptance Criteria

[ACs should be clearly demoable/verifiable whenever possible. Try specifying them using BDD.]

• GIVEN [a contextual precondition]
  [AND optionally another precondition]
  WHEN [a triggering event] happens
  THEN [a verifiable outcome]
  [AND optionally another verifiable outcome]

Background

The theory behind this issue stems from extracting meaningful connections from our data to describe our data. We have partnerships with various federal/state/local governments/agencies. These organizations were created for a purpose and their mission drives the data that they create. If a tag such as water appears on a dataset within department of energy and another dataset from department of health, a different sense of the word can be understood and used to inform contextual information for further processing.

Security Considerations (required)

[Any security concerns that might be implicated in the change. "None" is OK, just be explicit here!]

Sketch

[Notes or a checklist reflecting our understanding of the selected approach]

• Create a word model highlighting frequency of tags per organization
• Determine if tags can be correlated with organizations to give rise to categories based on organizational missions.