I chose to examine the “All City Department Payroll” from the LA Controller’s Office. I thought this would be interesting to analyze because it would show just how much Los Angeles is investing in the different departments. I always hear about how different departments deserve more money than others, and how they are underfunded so I thought this data set would let me further examine funding disparities.

The data types include 22 departments and depict the funding for each of them in various visualizations – so essentially 22 records of outlining the departments’ fundings from 2011 to 2013. It also shows how each department is classified (parks & recs or LAPD) and how much tax money they receive for their department. When each department is clicked, a corresponding payroll appears delegated to them. The different visualization tools include various charts such as donuts, column charts, bar charts, pie charts, stacked bars, bubbles, and tree maps.

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To identify a dataset’s ontology, Wallack and Srinivasan define it as the distinctions seen between people’s personal “mental maps of their surroundings” (Wallack and Srinvasan, 1). For this dataset, the ontology is that of the LA Controller’s Office. By delegating specific fundings for specific departments, they decide what is important and needs to be invested in for LA to run smoothly and efficiently. In this dataset seen, there is a massive disparity seen between funding.

The LAPD, LAFD, and DWP departments receive the most amount of funding in comparison to the other departments, their three departments combined receive more than half of total tax payer’s money. Meanwhile the other 19 departments the other half. Departments such as Animal Services, Zoos, and Public Works receive some of the least amount of funding as seen by the stacked column chart.

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If the funding delegation was managed by veterinarians, the ontology of the dataset might differ greatly. This data set then might show Zoos and Animal Services receiving much more funding, while other departments might receive less.

I believe that the LA county public as well as the people who manage and work within these departments would find this data most illuminating. This is because it allows people to understand where exactly their tax money is going and whether they agree or disagree with the LA Controller’s Office. If the public knows how their money is being fractioned, they can better mold what they as a city believe to be important. Meanwhile for the people who work within the department, they can also see how much funding they are receiving and also seen the dominators within the LA county. For example, they can see that the Parks and Recs department is the most funded department underneath LAPD, LAFD, and DWP. If Parks and Recs aren’t needed or used as much as other departments, then maybe their funding can be transferred to other departments. By making this information public, departments can try and figure out the right balance of fundings.

What is left out of this data set is the reasoning behind the fundings. While the public can guess the LA Controller’s justifications for example the LAPD, LAFD, and DWP, some others may not be as obvious. Because everyone has different opinions about what is considered important to them, many different ontologies and funding breakdowns could exist.