Week Nine: Face It

A trend has begun within these classes moving towards this class today I think. Ways in which we can utilise cultural heritage data to make it more engaging, and accessible using digital tools – and today really empathised that with the use of computer vision technology. We have looked at neatening data, making it into a variety of visual graphs and so forth. This week was all about images, and how to help computers see images in ways that are more useful and tangible for us (and sometimes accidental like Redaction ‘Art’). The most visceral and moving example was the images of the faces of people under the White Australian Policy. I think this is a beautiful way of fleshing out an issue that is widely known, but more in a way of dates and laws, rather than the actual who. Visual aids appeal to our humanity because a face is so recognisable and emotive, it instantly builds empathy because this is another person just like you or me.

Tim was discussing that the goal for another example, the Trovebot, putting faces on people who sent in photos was to try and connect people to the past in new ways. I love this as it continues to makes this data significant, because without interaction its meaning is lost. Face detection technology is a lot of fun too and I can see how this can be used in a variety of different ways, perhaps even at cultural institution with a photo booth like set up putting images of faces from the museum on to your own.

The face detection subject just reminded me a lot of the Snapchat filters that are popular, and sometimes they do have historically relevant ones (such as Marilyn Monroe on her birthday or the faceswap option where you can upload and image to swap with your own which I have seen is quite popular to do at classical art galleries). This is engaging, shareable and fun and this is another outlet that is potentially significant for cultural heritage as it is very good and well known technology.

Facial recognition on the other hand, a little creepy, but without obvious benefits used by the right people. Being able to identify historical figures in object would be great for example.

Week 6 Visualising Data

In previous weeks we have looked at data in numerical or even alphabetical form, and I think we got a lot out of that information such as trends as well as what data is out there, where and how to get it. However a lot of data is very boring to look at and very long. This means, in particular for humanities data it looses a lot of its feeling and understanding. This week we looked at tools that can take in data and then churn it out in one of the visualisations, and how much customisation we can do like in Plotly and Raw. Examples like Mapping Police Violence and The Preservation of Favoured traces utilise movement and colour to very effectively and viscerally portray data. Mapping Police Violence had data points pop up like gun shots, and the rate at the changes of The Origin of the Species physically showed the theme of the progress of science. I thought these were really fascinating examples and summed up what we were trying to identify and explore in the class. Although I am more interested in mapping for my project I gained from the class that some visualisations match some data better, which can help me in selecting visual components for my project.

 

Here is my stacked bar graph using plotly rather than QueryPic


 

Week Four: What Data

This week we looked at the myriad of options concerning data and metadata, where to find it, what to do with it and what it is. I think that the Posner article really set the tone this week for me from doing the reading prior to the class, when he drew an analogy of what you would feel like if someone called your photo album a data set. I though that summarised his article well, illustrating the difference between humanities data and scientific data. Humanities data is most prominently linked intrinsically to people, culture, religion and real lives. This makes context and interpretation even trickier, but more interesting, to deal with, and I think that that was addressed well in acitivites and discussion during the class.

The class really opened up to me how much data there is, not how many records because obviously there’s lots of records of things especially in Western culture, but how many categories of ‘stuff’ is out there. Colonists bank records, water qualities, I even found how a dataset of average fruit intake for an Indigenous Australian primary school student. This class highlighted the importance of digital heritage, in particular in unlocking, fixing, and making sense of historic data to then churn it out in accessible format. What is the point of data otherwise? All of the things we found are super important and interesting to a plethora of people, cultures, organisations and have so many uses whether research, predictive or even personal. As I mentioned before because this is humanities data that stakes are so much higher as they are more actualised in the real world. However there’s no point if data is not in context, can not be categorised, understand or even read properly if there is mistake. The tools we used in the class fixed all these problems, plotly developed visual representations of data to be interacted and understood, openrefine to fix and categorise. Not only did we learn to use these tools, we understood in a broader sense what data is, how it can be used and finally how we can utilised in our own research contexts in cultural heritage.

One thing that I find really interesting was one of the graphs on plotly someone else had made, a pie chart illustrating the most used colours in Van Gogh’s artworks. What a cool use of data as well as graphing to portray something so organically creative and artistic and well non-mathmatical into a tangible piece of data – a good balance between the scientific data and humanities data Posner was discussing.

Here is my graph for male and females in 1901 – silly outlier Adelaide 🙂

 

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