Open Government Transparency Search for sandra albertson shea in us

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Preview of information for sandra albertson shea in us

SANDRA ALBERTSON-SHEA, who retired on December 31, 2003, at age 61, received an annual pension of $37,450.56. She worked for the Middlesex Community College agency (821) for 210,602 hours, with an average salary of $58,476.28. Her retirement type is SA. She held the title of PROFESSOR at the time of her retirement. Her monthly pension is $3,120.88, and her person ID is 213192. The pension data provided is as of 2016, and her transaction number is 45410109.

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Total datasets: 1 load time 0.06 min

ALLPENSIONS null 2016-11-30T18:14:04.000Z Search

{"serviceMillis":52,"searchMillis":[19,14]}

type_of_retirementannual_pensionagency_last_worked_increditable_serviceaverage_salarytitle_at_retirementdate_of_retirementfirst_namelast_nameyeartrans_noage_at_retirementdepartment_last_worked_inmonthly_pensionperson_id
SA37450.56821210602.0058476.28PROFESSOR2003-12-31T00:00:00.000SANDRAALBERTSON-SHEA20164541010961MIDDLESEX COMMUNITY COLLEGE3120.88213192


  data:
    [
   {
      "type_of_retirement": "SA",
      "annual_pension": "37450.56",
      "agency_last_worked_in": "821",
      "creditable_service": "210602.00",
      "average_salary": "58476.28",
      "title_at_retirement": "PROFESSOR",
      "date_of_retirement": "2003-12-31T00:00:00.000",
      "first_name": "SANDRA",
      "last_name": "ALBERTSON-SHEA",
      "year": "2016",
      "trans_no": "45410109",
      "age_at_retirement": "61",
      "department_last_worked_in": "MIDDLESEX COMMUNITY COLLEGE",
      "monthly_pension": "3120.88",
      "person_id": "213192"
   }
]

  keys:
    [
   "type_of_retirement",
   "annual_pension",
   "agency_last_worked_in",
   "creditable_service",
   "average_salary",
   "title_at_retirement",
   "date_of_retirement",
   "first_name",
   "last_name",
   "year",
   "trans_no",
   "age_at_retirement",
   "department_last_worked_in",
   "monthly_pension",
   "person_id"
]
    

directoryQuery: https://api.us.socrata.com/api/catalog/v1?ids=3zah-qrsj&limit=100

permalink: https://cthru.data.socrata.com/d/3zah-qrsj

dataQuery: https://cthru.data.socrata.com/resource/3zah-qrsj.json?$select=type_of_retirement%2Cannual_pension%2Cagency_last_worked_in%2Ccreditable_service%2Caverage_salary%2Ctitle_at_retirement%2Cdate_of_retirement%2Cfirst_name%2Clast_name%2Cyear%2Ctrans_no%2Cage_at_retirement%2Cdepartment_last_worked_in%2Cmonthly_pension%2Cperson_id%2Cmiddle_initial&$order=first_name%20desc&$limit=10&$offset=0&$q=sandra%20albertson%20shea

Sites such as socrata.com appear to be tools to bring transparency to our governments. But what do they actually do in practice. This site attempts to use socrata.com (and hopefully all other "open transparency sites") to understand what the state of affairs are at the moment.

A summary view of the catalog when you filter for the word salary shows the lack of standarization.

Employee Salaries This dataset provides base salary information abou... Ramona Benson, Department of Human Resources Search
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Budget - Salaries Budgeted Salaries by Position null Search
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The screenshot shows a sample of name and descriptions of government uploaded salary transparency information. First of all, the information appears to be not easy to find for the general public. And even if the general public finds it, it is hard to tell what government it applies to. For example, there are datasets that simply have the name "Employee Salaries" and some that have no attribution at all. The column names are a mix of whatever the hundreds of individuals decided to use. This makes organization difficult, but not impossible.

Let's organize the information and overcome the obstacles!

Socrata Meta Catalog API

The Socrata Meta Catalog API provides access to metadata about the datasets and tables available on the Socrata Open Data Portal.

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  1. Create a Socrata developer account at https://dev.socrata.com.
  2. Get an API access token from the API Access Tokens page.
  3. Send a GET request to the /catalog/v1 endpoint with the following parameters:

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The response will be a JSON object containing an array of dataset objects. Each dataset object will contain the following properties:

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    debug: columns: name:
    [
   "AGE AT RETIREMENT",
   "AGENCY LAST WORKED IN",
   "ANNUAL PENSION",
   "AVERAGE SALARY",
   "CREDITABLE SERVICE",
   "DATE OF RETIREMENT",
   "DEPARTMENT LAST WORKED IN",
   "FIRST NAME",
   "LAST NAME",
   "MIDDLE INITIAL",
   "MONTHLY PENSION",
   "PERSON ID",
   "TITLE AT RETIREMENT",
   "TRANS NO",
   "TYPE OF RETIREMENT",
   "YEAR"
]

    debug: columns: type:
    [
   "Calendar date",
   "Number",
   "Number",
   "Number",
   "Number",
   "Number",
   "Number",
   "Number",
   "Number",
   "Text",
   "Text",
   "Text",
   "Text",
   "Text",
   "Text",
   "Text"
]