My GitHub Website for BDA 594 —
Census data is critial for allocation of resources across the county. At a federal level, it impacts how much the budget is allocated to provide social services like food stamps, housing assistance, and Medicaid. At a local level, it helps us understand the type of people we have and ensure we can identify community needs for the region. This dataset is also important for political reasons as it drives the number of members of the House of Representatives each state has depending on populations change, seats will be impacted. I work for the County of San Diego, and we look at Census data constantly. When are assessing social services programs to ensure we strategically identify where gaps exist, such as housing, food insecurity, access to healthcare, proximity to transportation, etc. Making sure we are addressing community needs based of data is key. At the County, I use this data to identify the most common languages spoken in San Diego. We assumed it was Spanish due to historical information but in the last 10 years, we learned that our community spoke Arabic, Haitian-Creole, Korean, et. This data was valuablue as we were able to ensure we provided communication for those social services resources in the threashold languages.
Author: Murtha Baca
Intro - Introduction to metadata showcases the important of metadata (data about data), how keeping this data helps us stay organized and find online resouces. It covers topics about “metasearching” which covers how search engine utilizing metadata and the dominance Google has had. This topic is interesting to me because over the last years, we’ve seen the rise of other social search engines that people are defaulting over Google, such as TikTok and Instagram. So understanding how metadata is used across these platforms and what fundamental topics they share is something that has lots of value.
Metadata is a topic that I grew interest in the last few years because it’s provides so much information about your data. I was into photography a few years ago, and reviewing the metadata of each photo such as: where the photo was taken, at what time, what camera settings the photo had, etc. Help me figure out why some shots were overexposed and also keep track of exactly where certain photo was taken. That is how Apple is able to index our photos by location, and dates. Now it’s using Apple intelligence to create “moments” and it takes context of photo like birthday signs to create those. Simply by using data about data.