Data Dictionary: Clean Employee API

Data dictionary for data retrieved using Clean Employee API endpoints. This data dictionary shows all available data points, explains their values, and provides data samples from the Clean Employee API data.

The data provided in the samples is strictly intended for illustrative purposes, allowing you to visualize its appearance and format.

Metadata

Data point

Processing

Description

Data type

last_updated

Cleaned

Date the record was last updated

String

is_deleted

Raw

Indicates whether the profile was accessible: 1 – deleted or private 0 – publicly available

Integer

Meta data

"last_updated": "2023-07-29",
"is_deleted": 0

Cleaning actions

Data point

Cleaning action

last_updated

Value is converted to the yyyy-mm-dd format.

Identifiers

Data point

Processing

Description

Data type

id

Raw

Employee record identification key in our database

Integer

full_name

Cleaned

Full name

String

name_first

Raw

First name

String

name_middle

Enriched

Middle name

String

name_last

Enriched

Last name

String

websites_professional_network

Raw

Professional network profile URL

String

shorthand_names

Raw

Historical shorthand name list

Array of strings

picture_url

Raw

Profile picture URL

String

follower_count

Raw

Profile follower count

Integer

Identifiers

{
  "id": 4290,
  "full_name": "John Leonardo Doe",
  "name_first": "John",
  "name_middle": "Leonardo",
  "name_last": "Doe",
  "websites_professional_network": "https://www.professional_network.com/in/john-leonardo-doe",
  "shorthand_names": [
    "john-leonardo-doe"
  ],
  "picture_url": "https://static.lnk.com/sc/h/9c8pery4andzj6ohjkjp54ma2",
  "follower_count": 445,

Cleaning actions

Data point

Cleaning action

full_name

Special characters/emojis are removed;

Any words that follow a comma or in parentheses are removed;
Titles (preceding or following the name) are removed.

name_middle

Parsed from member_full_name.

name_last

Parsed from member_full_name.

Skills

Data point

Processing

Description

Data type

skills

Enriched

Skill list

Array of strings

Skills

"skills": [
        "3d",
        "3d printing",
        "creative",
        "design",
        "electronics",
        "photography",
        "programming"
    ]

Enriching action

Data point

Enriching action

skills

Enriched with our ML model from different description fields.

Experience

Data point

Processing

Description

Data type

description

Raw

Job position description

String

company_id

Enriched

Employer's identification key

Integer

headline

Raw

Title found in the profile headline

String

generated_headline

Raw

A user-written headline that can be found in web search, also viewed and other publicly available spaces. It serves the same purpose as the title but is derived from a different source, potentially providing more accurate and up-to-date profile information. This field should be used in place title as it reflects the latest user activity.

String

job_title

Cleaned

Current job position title

String

is_decision_maker

Enriched

Indicates whether the employee is a decision-maker based on job_title 1 – Employee is marked a decision-maker in the current role 0 – Employee is not marked a decision-maker in the current role

Integer

job_description

Raw

Current job position description

String

total_experience_duration

Enriched

Summed up experience. Converted to Professional network-like text, e.g.,2 Years 11 Months

String

total_experience_duration_months

Enriched

Summed up experience (displayed as months)

Integer

Experience

"company_id": 10101010,
"description": "Examples Engineer, with a Master's Degree in Examples.",
"headline": "Examples Engineer @ Example Company",
"generated_headline": "Examples Engineer @ Example Company",
"job_title": "Examples Engineer",
"job_description": "Advice on the Examples generation.\\\\nWe develop Examples Modeling and Custom Examples",
"total_experience_duration": "2 Years 11 Months"
"total_experience_duration_months": 35,

Cleaning and enriching actions

Data point

Cleaning/enriching action

company_id

Company ID from an active experience record from member_experience.

job_title

Special characters are removed.

date_from

-Value is converted to the yyyy-mm-dd format.

total_experience_duration

Values converted to readable text.

total_experience_duration_months

Field aggregated from duration values.

The experience table is mapped with our historical data due to source's policy of hiding the work experience on certain employees' profiles.

Data point

Processing

Description

Data type

experience

Work experience details

Array of objects

company_id

Raw

Workplace (company) identifier in our database

Integer

date_from

Cleaned

Employment start date

String (date)

date_from_year

Cleaned

Employment start year

Integer

date_from_month

Cleaned

Employment start month

Integer

date_to

Cleaned

Employment end date

String (date)

date_to_year

Cleaned

Employment end year

Integer

date_to_month

Cleaned

Employment end month

Integer

company_url

Raw

Employer's professional network profile URL

String

company_name

Raw

Employer company

title

Raw

Job title

String

department

Enriched

Associated department

String

management_level

Enriched

Management level

String

description

Cleaned

Job description

String

order_in_profile

Raw

Record order as seen on the employee's profile

Integer

duration

Enriched

Employment duration

String (date)

duration_months

Cleaned

Employment duration in months

Integer

location

Cleaned

Job/workplace location

String

Experience

"experience": [
    {
      "title": "Product Owner, Sr. Salesforce Administrator",
      "description": "Best practice declarative management of Salesforce for the organization. Responsible for security protocols, permissions and profiles and daily maintenance of Salesforce. Custom declarative development for the organization.",
      "order_in_profile": 9,
      "company_id": 9975614,
      "company_name": "Example Company",
      "company_url": "https://www.professional_network.com/company/example-company",
      "date_from": "2013-10-01",
      "date_from_year": 2013,
      "date_from_month": 10,
      "date_to": "2015-07-01",
      "date_to_year": 2015,
      "date_to_month": 7,
      "duration": "1 year 10 months",
      "duration_months": 22,
      "department": "Product",
      "management_level": "Senior"
    }
],

Cleaning and enriching actions

Data point

Cleaning/enriching action

company_id

Company ID from an active experience record from member_experience.

job_title

Special characters are removed.

total_experience_duration

Values converted to readable text.

total_experience_duration_months

Field aggregated from duration values.

Information in the table below is enriched using Clean and Base Company datasets.

Data point

Description

Data type

experience

Employer (company) details

Array of objects

company_type

Type

String

company_founded

Founding year

String

company_followers_count

Follower count

Integer

company_website

Official website

String

company_facebook_url

Facebook profile URL

Array of strings

company_twitter_url

Twitter profile URL

Array of strings

company_professional_network_url

Professional network profile URL

String

company_size_range

Size (as a range)

String

company_size_employees_count

Headcount

Integer

company_industry

Associated industry

String

company_location_hq_full_address

Full address of company headquarters

String

company_location_hq_country

Headquarters location (country)

String

company_location_hq_regions

Headquarters location (regions)

Array of strings

company_location_hq_country_iso2

Headquarters location (country, ISO alpha-2 code)

String

company_location_hq_country_iso3

Headquarters location (country, ISO alpha-3 code)

String

company_location_hq_city

Headquarters location (city)

String

company_location_hq_state

Headquarters location (state)

String

company_location_hq_street

Headquarters location (street)

String

company_location_hq_zipcode

Headquarters location (zipcode)

String

company_last_updated

The last update date of the company profile

String

company_categories_and_keywords

Categories and keywords assigned to the profile

Array of strings

company_stock_ticker

Stock ticker

Array of strings

company_is_b2b

Marks if the company sells B2B or B2C products 1 – b2b company 0 – b2c company

Integer

company_annual_revenue

Annual revenue

Integer

company_annual_revenue_currency

Annual revenue currency

String

company_employees_count_change_yearly_percentage

Percentage of employee count change

String

company_last_funding_round_announced_date

Date of last funding round

String (date)

company_last_funding_round_amount_raised

Amount of last funding round

Integer

Experience + company

  "experience": [
    {
      "company_type": "Privately Held",
      "company_founded": "1939",
      "company_followers_count": 256699,
      "company_website": "www.example-company.com",
      "company_facebook_url": [
        "https://www.facebook.com/example-company"
      ],
      "company_twitter_url": [
        "https://www.twitter.com/example-company"
      ],
      "company_professional_network_url": "https://www.professional_network.com/company/example-company",
      "company_size_range": "5001-10,000 employees",
      "company_size_employees_count": 4488,
      "company_industry": "Truck Transportation",
      "company_location_hq_full_address": "15047; Lima, Lima Perú, PE",
      "company_location_hq_country": "Peru",
      "company_location_hq_regions": [
        "Americas",
        "Latin America and the Caribbean",
        "South America",
        "AMER"
      ],
      "company_location_hq_country_iso2": "PE",
      "company_location_hq_country_iso3": "PER",
      "company_location_hq_city": "Lima",
      "company_location_hq_state": "Example State",
      "company_location_hq_street": "Example Street",
      "company_location_hq_zipcode": "0033",
      "company_last_updated": "2024-08-29",
      "company_categories_and_keywords": [
        "Logistics"
      ],
      "company_stock_ticker": [
        "EXMP"
      ],
      "company_is_b2b": 1,
      "company_annual_revenue": 2500000000,
      "company_annual_revenue_currency": "$",
      "company_employees_count_change_yearly_percentage": 9.463414634146341,
      "company_last_funding_round_announced_date": "2023-06-05",
      "company_last_funding_round_amount_raised": 15600000
    }
  ]

Data point

Processing

Description

Data type

department

Enriched

Departments derived from the job_title

String

management_level

Enriched

Management levels identified from the job_title

String

is_working

Enriched

Current employment marker1 – Currently employed 0 – Currently unemployed

Boolean

Experience

"department": "Project",
"management_level": "Other",
"is_working": 1

Enriching actions

Data point

Cleaning/enriching action

department

Enriched with our ML model.

management_level

Enriched with our ML model.

is_working

Based on date_to and date_from values of employee experience.

Education

Data point

Processing

Description

Data type

education

Education details

Array of objects

major

Cleaned

Field of study

String

title

Cleaned

Educational institution

String

date_to

Cleaned

Graduation date

Integer

date_from

Cleaned

Enrolment date

Integer

institution_url

Cleaned

Institution's profile URL

String

description

Cleaned

Education description

String

activities_and_societies

Cleaned

Details about activities and societies

String

Education

 "education": [
        {
            "major": "Associate's degree, Business Administration and Management, General",
            "title": "Example College",
            "date_to": "1997",
            "date_from": "1996",
            "institution_url": "https://www.professional_network.com/school/example-college",
            "description": "Attended Business College from 1996 to 1997",
            "activities_and_societies": "Activities and Societies: Chess"
        }
    ],

Cleaning actions

Data point

Cleaning action

title

Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None;
Values are capitalized.

major

Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.

date_from

Value is converted to the yyyy format.

date_to

Value is converted to the yyyy format.

institution_url

Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.

description

Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None;

Text styling tags are removed;
Multiple spaces are replaced with single ones.

activities_and_societies

Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None;

Text styling tags are removed;
Multiple spaces are replaced with single ones.

Hidden collections

Data point

Description

Data type

is_hidden

Marks if the profile has a hidden education/experience collection.

0 – education/experience information was available at the time of profile scraping 1 – education/experience information was not available at the time of profile scraping

Integer

is_hidden + experience

"experience": [
    {
        "title": "IT Project Manager",
        "description": "Lead cross-functional teams to deliver complex software solutions on time and within budget, overseeing all phases of project lifecycle from conception to deployment.",
        "order_in_profile": 1,
        "company_id": 11110108,
        "company_name": "Example Company",
        "professional_network_company_url": "https://www.professional_network.com/company/example-company",
        "date_from": "2022-06-01",
        "date_to": null,
        "duration": "1 year"
    }
],
"is_hidden": 0,

is_hidden + education

"education": [
    {
        "title": "Massachusetts Institute of Technology",
        "major": "Master of Science - MS, Information Technology Project Management",
        "date_from": 2021,
        "date_to": 2022
    }
],
"is_hidden": 0,

Location

Data point

Processing

Description

Data type

location_raw_address

Cleaned

Associated location

String

location_country

Cleaned

Parsed country

String

location_regions

Cleaned

Geographical regions parsed from associated location

Array of strings

Location

"location_raw_address": "Peru",
"location_country": "Peru",
"location_regions": [
        "AMER",
        "South America",
        "Latin America and the Caribbean"
    ],

Cleaning actions

Data point

Cleaning action

location_raw_address

Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None;

Special trailed characters are trimmed;
Value is set to None if it is shorter than three characters;
The value of member_location_country is added at the end of the string.

location_country

Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.

Recommendations and connections

Data point

Processing

Description

Data type

recommendations

Cleaned

Recommendations from other users

Array of objects

recommendation

Cleaned

Recommendation text

String

referee_name

Raw

Referee's name

String

referee_url

Raw

Referee's profile URL

String

recommendations_count

Cleaned

Number of received recommendations

Integer

connections_count

Raw

Number of connections with other users

Integer

Recommendations and connections

"recommendations": [
    {
      "recommendation": "“John was a great asset in collaborating the tasks in different departments to produce the same goal. He was great at providing advice and asking questions to avoid even a tiny error during the process. Great to work with him!”",
      "referee_name": "Marry Moe",
      "referee_url": "www.professional_network.com/in/marry-moe",
      "order_in_profile": 1
    }
  ],
  "recommendations_count": 1,
  "connections_count": 65535,

Cleaning actions

Data point

Cleaning action

recommendations

Deleted rows are filtered out.

recommendation

Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None;

Value is set to None if it is shorter than three characters;
Text styling tags are removed;
Multiple spaces are replaced with single ones;
Empty recommendations are filtered out.

recommendations_count

Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None;

None values are replaced with 0 and made an integer.

Languages

Data point

Processing

Description

Data type

languages

Language knowledge

Array of objects

language

Cleaned

Language

String

proficiency

Cleaned

Language proficiency

String

order_in_profile

Raw

Record order in the section

Integer

Languages

"languages": [
        {
            "language": "English",
            "proficiency": "Intermediate",
            "order_in_profile": 1
        }
    ],

Cleaning actions

Data point

Cleaning action

language

Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.

proficiency

Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.

Certifications

Data point

Processing

Description

Data type

certifications

Held certifications

Array of objects

title

Cleaned

Certificate title

String

issuer

Cleaned

Certificate issuer

String

credential_id

Cleaned

Record order in the section

Integer

certificate_url

Cleaned

Certificate URL

String

date_from

Cleaned

Issue date

String

date_to

Cleaned

Expiration date

String

issuer_url

Cleaned

Issuer profile URL

String

order_in_profile

Raw

Section record order

Integer

date_from_year

Cleaned

Issue year

Integer

date_from_month

Cleaned

Issue month

Integer

date_to_year

Cleaned

Expiration year

Integer

date_to_month

Cleaned

Expiration month

Integer

Certifications

"certifications": [
        {
            "title": "Yellow Certificate",
            "issuer": "Example Studio",
            "credential_id": 3344,
            "certificate_url": "http://example-studio.com/public_profile_certification-title",
            "date_from": "2020-08-01",
            "date_from_year": 2020,
            "date_from_month": 8,
            "date_to": "2023-08-01",
            "date_to_year": 2023,
            "date_to_year": 8,
            "issuer_url": "https://www.professional_network.com/company/example-studio",
            "order_in_profile": 1
        }
    ],

Cleaning actions

Data point

Cleaning action

title

Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.

issuer

Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.

date_from

Value is converted to the yyyy-mm-dd format.

date_to

Value is converted to the yyyy-mm-dd format.

issuer_url

Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.

date_from_year date_to_year

Year value from date is converted to an integer.

date_from_month date_to_month

Month value from date is converted to an integer.

Courses

Data point

Processing

Description

Data type

courses

Attended courses

Array of objects

organizer

Cleaned

Course organizer

String

title

Cleaned

Course title

String

order_in_profile

Raw

Record order in the section

Integer

Courses

 "courses": [
        {
            "organizer": "Example Academy",
            "title": "Microsoft Certified Excel Expert",
            "order_in_profile": 1
        }
    ],

Cleaning actions

Data point

Cleaning action

organizer

Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.

title

Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.

Awards

Data point

Processing

Description

Data type

awards

Held awards

Array of objects

title

Cleaned

Award

String

issuer

Cleaned

Award issuer

String

description

Cleaned

Award description

String

date

Cleaned

Issue date

String

order_in_profile

Raw

Section record order

Integer

date_year

Cleaned

Issue year

Integer

date_month

Cleaned

Issue month

Integer

Awards

"awards": [
        {
            "title": "Certified in Example Management",
            "issuer": "Example Association",
            "description": "Certification in Example Management",
            "date": "2011-08-01",
            "order_in_profile": 4,
            "date_year": 2011,
            "date_month": 8
        }
    ],

Cleaning actions

Data point

Cleaning action

title

Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None;
Values are capitalized.

issuer

Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None.

date

Value is converted to the yyyy-mm-dd format.

date_year

Year value from date is converted to an integer.

date_month

Month value from date is converted to an integer.

Activity

Data point

Processing

Description

Data type

activity

Interaction with posts on Professional network

Array of objects

activity_url

Raw

Post URL

String

title

Cleaned

Post title

String

action

Cleaned

Interaction type

String

order_in_profile

Raw

Section record order

Integer

Activity

"activity": [
        {
            "activity_url": "https://www.professional_network.com/posts/example-company-post1",
            "title": "Example Company would like to introduce our \"Team Spotlight”, John Doe @Example Company #example #company",
            "action": "Liked by",
            "order_in_profile": 1
        }
    ],

Cleaning actions

Data point

Cleaning action

title

Values ["None"; "Unknown"; "NaN"; "nan"; "na"; "null"; "Null"; "NULL"; "-"; "--"] are replaced with value None;

Text styling tags removed;
Multiple spaces are replaced with single ones.

Organizations

Data point

Description

Data type

member_organizations

Memberships in organizations

Array of structs

organization

Organization title

String

position

Position in the organization

String

description

Description of the activity/experience in the organization

String

date_from

Membership start date

String

date_from_year

Membership start year

Integer

date_from_month

Membership start month

Integer

date_to

Membership end date

String

date_to_year

Membership end year

Integer

date_to_month

Membership end month

Integer

order_in_profile

The exact position of the organization in the profile

Integer

Organizations

  "member_public_profile_id": "123456789",
  "member_organizations": [
    {
      "organization": "Example Organization",
      "position": "Lead Software Engineer",
      "description": "Led a team of developers providing great services.",
      "date_from": "2019-06",
      "date_from_year": 2019,
      "date_from_month": 6,
      "date_to": "2023-09",
      "date_to_year": 2023,
      "date_to_month": 9,
      "order_in_profile": 1
    }
  ],

Patents

Data point

Description

Data type

member_patents

Authored patents

Array of structs

title

Patent title

String

status

Patent status

String

inventors

Inventors of the patent

Array of structs

full_name

Full name of the inventor

String

profile_url

Profile URL

String

order_in_profile

Order in profile

Integer

date

Patent filing date

String

date_year

Filling year

Integer

date_month

Filling month

Integer

date_day

Filling day

Integer

patent_url

Patent URL

String

description

Patent description

String

patent_or_application_number

Patent or application number

String

order_in_profile

The exact position of the patent in the profile

Integer

Patents

  "member_patents": [
    {
      "title": "Data Synchronization System",
      "status": "Granted",
      "inventors": [
        {
          "full_name": "John Doe",
          "profile_url": "https://www.professional-network.com/profile/johndoe",
          "order_in_profile": 1
        },
        {
          "full_name": "Jane Smith",
          "profile_url": "https://www.professional-network.com/profile/janesmith",
          "order_in_profile": 2
        }
      ],
      "date": "2022-01-01",
      "date_year": 2022,
      "date_month": 1,
      "date_day": 1,
      "patent_url": "https://wwww.patents.example.com/US1234567",
      "description": "A method for efficient synchronization of distributed systems in real-time environments.",
      "patent_or_application_number": "US1234567B2",
      "order_in_profile": 1
    }

Publications

Data point

Description

Data type

member_publications

Memberships in organizations

Array of structs

title

Publication title

String

publisher

Publisher name

String

date

Publication release date

String

date_year

Release year

Integer

date_month

Release month

Integer

date_day

Release day

Integer

description

Publication description

String

authors

Authors of the publication

Array of structs

full_name

Full name of the author

String

profile_url

Profile URL

String

order_in_profile

Order in the profile

Integer

publication_url

Publication website URL

String

order_in_profile

The exact position of the publication in the profile

Integer

Publications

   "member_publications": [
    {
      "title": "Microservices Architecture in Cloud Environments",
      "publisher": "Journal of Software Systems",
      "date": "2024-08-01",
      "date_year": 2024,
      "date_month": 8,
      "date_day": 1,
      "description": "An in-depth analysis of architectural patterns and scalability challenges in cloud-native microservices.",
      "authors": [
        {
          "full_name": "John Doe",
          "profile_url": "https://www.professional-network.com/profile/johndoe",
          "order_in_profile": 1
        }
      ],
      "publication_url": "https://www.publications.example.com/microservices-architecture",
      "order_in_profile": 1
    }
  ]
}

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