Interests

Purpose:Provide general occupational interest (RIASEC) high-point codes and numeric profile data for each O*NET-SOC occupation.
Download: Interests.xlsx
Structure and Description:
ColumnTypeColumn Content
O*NET-SOC CodeCharacter(10)O*NET-SOC Code (see Occupation Data)
TitleCharacter Varying(150)O*NET-SOC Title (see Occupation Data)
Element IDCharacter Varying(20)Content Model Outline Position (see Content Model Reference)
Element NameCharacter Varying(150)Content Model Element Name (see Content Model Reference)
Scale IDCharacter Varying(3)Scale ID (see Scales Reference)
Scale NameCharacter Varying(50)Scale Name (see Scales Reference)
Data ValueFloat(5,2)Rating associated with the O*NET-SOC occupation

This file contains the general occupational interest (RIASEC) high-point codes and numeric profile data for each O*NET-SOC occupation.

Interest ratings are presented as two scales: OI reports the RIASEC level of each interest and IH presents “high-point codes”, the numbers of the RIASEC scales for the first, second and/or third highest ratings.

The high-point values represent the following elements:

 0.00 = No high point available 
 1.00 = Realistic 
 2.00 = Investigative 
 3.00 = Artistic 
 4.00 = Social 
 5.00 = Enterprising 
 6.00 = Conventional 

The file is displayed in 9 tab delimited fields with the columns named O*NET-SOC Code, Title, Element ID, Element Name, Scale ID, Scale Name, Data Value, Date, and Domain Source. The 9 fields are represented by one row. There are a total of 8,307 rows of data in this file.

For more information, see:

File Structure Changes:
Release NumberDescription of Change
5.0Date and Source columns added
5.1 - 28.1No structure changes

Data Example - Interests:
O*NET-SOC CodeTitleElement IDElement NameScale IDScale NameData ValueDateDomain Source
43-4041.00Credit Authorizers, Checkers, and Clerks1.B.1.aRealisticOIOccupational Interests1.0011/2023Machine Learning
43-4041.00Credit Authorizers, Checkers, and Clerks1.B.1.bInvestigativeOIOccupational Interests1.8511/2023Machine Learning
43-4041.00Credit Authorizers, Checkers, and Clerks1.B.1.cArtisticOIOccupational Interests1.0011/2023Machine Learning
43-4041.00Credit Authorizers, Checkers, and Clerks1.B.1.dSocialOIOccupational Interests3.3911/2023Machine Learning
43-4041.00Credit Authorizers, Checkers, and Clerks1.B.1.eEnterprisingOIOccupational Interests4.4711/2023Machine Learning
43-4041.00Credit Authorizers, Checkers, and Clerks1.B.1.fConventionalOIOccupational Interests7.0011/2023Machine Learning
43-4041.00Credit Authorizers, Checkers, and Clerks1.B.1.gFirst Interest High-PointIHOccupational Interest High-Point6.0011/2023Machine Learning
43-4041.00Credit Authorizers, Checkers, and Clerks1.B.1.hSecond Interest High-PointIHOccupational Interest High-Point5.0011/2023Machine Learning
43-4041.00Credit Authorizers, Checkers, and Clerks1.B.1.iThird Interest High-PointIHOccupational Interest High-Point4.0011/2023Machine Learning
29-2034.00Radiologic Technologists and Technicians1.B.1.aRealisticOIOccupational Interests6.2511/2023Machine Learning
29-2034.00Radiologic Technologists and Technicians1.B.1.bInvestigativeOIOccupational Interests4.6311/2023Machine Learning
29-2034.00Radiologic Technologists and Technicians1.B.1.cArtisticOIOccupational Interests1.0011/2023Machine Learning
29-2034.00Radiologic Technologists and Technicians1.B.1.dSocialOIOccupational Interests3.5811/2023Machine Learning
29-2034.00Radiologic Technologists and Technicians1.B.1.eEnterprisingOIOccupational Interests1.0011/2023Machine Learning
29-2034.00Radiologic Technologists and Technicians1.B.1.fConventionalOIOccupational Interests4.8711/2023Machine Learning
29-2034.00Radiologic Technologists and Technicians1.B.1.gFirst Interest High-PointIHOccupational Interest High-Point1.0011/2023Machine Learning
29-2034.00Radiologic Technologists and Technicians1.B.1.hSecond Interest High-PointIHOccupational Interest High-Point6.0011/2023Machine Learning
29-2034.00Radiologic Technologists and Technicians1.B.1.iThird Interest High-PointIHOccupational Interest High-Point2.0011/2023Machine Learning