For this week’s blog post, I decided to take a look at the Animal Services Intake Data for 2011, 2012, and 2013 from the City of L.A. I chose this dataset because I personally have a pet dog that has run away multiple times, and I am curious to know what kind of breeds and conditions shelters take in dogs as.
Dataset’s Ontology
Created by the Department of Animal Services, the dataset is categorized into 9 columns: Shelter, Animal ID, Intake Date, Intake Type, Intake Condition, Animal Type, Group, Breed 1, Breed 2. It gives information on the type of animal a shelter takes in and the condition it’s in.
Point of View of Ontology
Although the information provided in the dataset can be useful for outsiders looking for their lost pet or even a potential new one, the data would be most useful for the shelter workers because it gives them an idea of how many new animals they are taking in, allowing them to know when they are reaching the shelter capacity.
Phenomenon Described
Because most of the animals are not strays but animals left behind by their owners, you can infer that the dataset is created for the shelters to have a headcount of the animals they bring in. Dead or alive, by filtering through the animal type and breed of animal, you can get a sense of how many unwanted animals are in the city of Los Angeles at the time.
What gets left out?
Although this is a pretty comprehensive list of the type of animal that gets sent to which shelter in LA, it’s missing the reasoning behind why each animal was taken in and the reasoning behind their condition. You can infer from the intake type why they were brought to the shelter, however, it only really tells you the type of owner, not their personal reason why they decided to bring their pet to the shelter. By including a column detailing the exact reason why each pet was left behind, we can possibly investigate and improve on the number of pets that get sent to shelters. Furthermore, the dataset only tells the reader whether or not the animal is dead or alive. If the animal is dead, a column describing the reason for the death can allow for a more comprehensive understanding of the situation.
A new POV
If I were to start over data collection with a new POV, I would do it in the perspective of the animal owner. If they lost their pet, an explanation of how their pet looks like and where they last saw them was would be helpful for the owners to have a database to look for their pet.
Hi there!
I didn’t even see this data set when I was looking through potential sets to write my blog post on! Super cool topic! I think if this database was to become larger, it would benefit a lot of more people looking for their lost dogs. I agree with you that it’s important to describe what the pets look like/where they were last seen. Adding that can make a huge impact to owners with lost dogs.
This is a very interesting dataset! It is saddening to hear that a majority of the pet in shelters wound up there due to neglect from their owners. I agree, including information such as why the animals are taken in can help the community, in which the animal shelter resides, improve the number of animals sent to the shelters. I think expanding this dataset in order to help pet owners look for their dogs is be a great idea as well!