Week 3 Blog: Open Data

The articles that we read about today talked about all of the kinds of projects we can make using open data sources. Mia Ridge describes open data as data made usable outside of the institution that collected the data. As a result, projects like the digital visualization projects of the Museum of Modern Art are made possible. This made me think about what other kinds of analysis with open cultural data.

This weekend I was watching the democratic debate. Throughout the debate there would small showing of Twitter trends in response to the debate. There was also a Google Trends report after the debate (below)that showed that after the debate, Bernie Sanders was the more searched for candidate in every state.

Going back to the article by Mia Ridge, she says that she believes that the future of data is that it will become more and more open which will allow for better analysis and understanding of what the data means. This is what made the Cooper-Hewitt project possible. With the archives of thousands of photos, he was able to create a visualizations for what colors were most popular in art throughout the 1900s decades. As more and more data becomes readily available, we will start to see more analysis and understanding of the data that has been privately examined and represented.

Mia also makes a fair point that in order to maximize the usefulness of the open data, it must have a standard ontology. A standard is going to be needed in order to represent the most honest data possible. It also is needed when working with algorithms in order to avoid duplicates or some categories being left out or null. The Bellander script was able to run because he had a common ontology for the single of data that he was working with. Once we start to collaborate with other data sets and begin to take larger samples of data, we are going to need a standard that unify the data so that we can then make sense of it. How this standard will come about is left question.