This week I decided to explore The Payroll by Job Class data set located at the LA Controller’s Office. The data set is a comprehensive collection of payroll information from Los Angeles City Departments dating back to 2013 to present.
The data is organized into 34 different categories including year, department title, payroll department, job class title, employment title, hourly/event rate, and projected annual salary. A record is constituted by a single individuals profile on his or her payroll information. However, individual names are not given and instead record numbers are assigned. There are 285,008 rows included in the data, and are arranged alphabetically by department title starting at 2016 and moving down in the same alphabetical order to 2013.
In Wallack and Srinivasan’s Local-Global: Reconciling Mismatched Ontologies in Development Information Systems, they state that a state ontology “sheds much of the local context in order to ensure tractable management for policy purposes including taxation, defense, provision of infrastructure and service, and economic management”(2). In short, because state officials manage the data, the information mainly exists for political reasons such as policy creations or revisions. A data set such as this Payroll collection is useful mainly for officials within the Los Angeles County, as they can have easy access to their employees’ salary information if they ever need it for taxation reasons, etc. The data set simply tells whoever is looking at it detailed numerical information about LA County job salaries.
What are left out from this data are specific details about the different jobs within the departments that account for wage differences. For example, in the Aging department, Senior Management Analyst 1 earns $53.46/ hr. while Senior Management Analyst 2 makes $66.23/hr. No differences between the two jobs are given besides one being called 1 and the other 2. Missing details like this make it unclear whether employees are being discriminated by being paid less for the same job or if there are actual differences between the two jobs that make one more difficult than the other, thus creating the wage difference.
If I were to write the ontology over with a non-government point of view, this data may then become useful for someone who is considering job within the county and would like to see how much he or she would be paid for said job. In a lot of cases, a major deciding factor for pursuing a career would be if the salary were high enough or not. This data set could easily help someone determine whether she wants to pursue a certain career or not or even give ideas for different careers based purely on the salary.
This is a good analysis on the ontologies of the chosen dataset. However, besides the taxation purpose, what other functions of this dataset could have? Perhaps transparency could be another reason for this dataset. For the two job titles of different salaries, I think they could just name them differently based on the differed tasks reflected in their salaries. I like the ontologies you envisioned since you pointed out the perspective from potential employees which those governmental documents normally ignore.