Where I am from
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For the past five years, I have devoted myself to the study and practice of visual communication design. I was interested in developing my practice in the field of Data Visualization because, while there is arguably an increasing emphasis on output and aesthetics alone, I think data visualization gives us an opportunity to focus more on the narrative and the message in design outputs.  

Visualization is a medium that helps to deliver the narrative within data to the world and translate information into knowledge (Braun, 2017). As data visualization keeps balancing the functionality and aesthetic, what I am aiming to do is to use this visual language to form an easy and straightforward way for people to access and understand data and its meaning.

What I’ve learned and experienced
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In the unit 02 session throughout the last 8 months, I constantly got to understand more and deeper about what Tiz (2021) has told us –how data visualization could tell a good story in a narrative way. I have started to use the process that she taught us later on from building the title/subtitle to defining the audience and writing the first/second paragraph of the data story, and finally to the ‘call to action’ step. It is similar to the process that Beyond World Studio (2022) (BWS) gave us that how to build a strong concept of what we want to say while using the dataset.

A delicate infographic does not just rely on accurate programming technic, but more important is it should tell a ‘factual or linear story’ (Heller and Lannders, 2014). Lupi (2017) also mentioned that we can write rich and dense stories with data, and transform raw information into interconnected knowledge. This ‘mission’ of data visualization is something that I have practiced and worked on throughout my unit 02 sessions.

While working with BWS on endangered plants, I and my groupmates spent time building the whole concept and using the forest-inspired chart as the main design element to clearly show the endangered plants' condition and the natural biodiversity in different countries. For the second project with Joana about AI machine learning based on makeup, we started to write our story from daily life and got know-how an AI algorithm would work. Then we used the visual language we specialize in to simulate the process of AI learning applications. In this endeavor, I drew on the principles I had read about in Helen Kennedy’s work (2020). She said data visualization shows statistical, numerical data in visual ways, in order to help communicate what the data means. In addition to this, in our work on the BWS project and with Joana, we also made the data contextualized in a story, which could make this communication contain more connected and intimate narratives (Lupi, 2017). In this way, my work in these workshops was, to me, an implementation of the theories I have engaged with in other parts of the course. Overall, I am increasingly aware of how to orderly arrange information to show the depth and breadth of data and narrative in an artistic language, and how to get the both creator and audience's perspective involved.

During this several projects process, I also received a lot of technical learning and support, such as experimenting with new software and skills to compose data with the help of Jovan and Llewelyn's teaching. Parts of my projects were supported by the software Tableau and P5 editor, which enhances my personal skills and the opportunity to experiment with more methods of data visualization.

However, I still tend and prefer to choose the tools and software I am most familiar with – the way I think I handle data best. This has allowed me to be comfortable with the process of the project and reasonably predict the outcome and realized what I intended. In many cases newly learned software skills did not help me achieve the results I had hoped for. In the future, I hope to take more risks with these new technologies, and with greater familiarity to push myself out of my technical comfort zone.  

I am conscious that, because of the limited time available for this unit and limited workshop resources, I have not finished all my projects from research to outcome steps, and haven't experimented with more alternative mediums to express my data, which I found somewhat frustrating and want to have more opportunities for developing my projects further.

For the future
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Data visualization has enormous potential to challenge our understandings of the world and our place in it. Multimodal and interdisciplinary in nature it holds the potential to change our conceptions of perceived divisions between disciplines, methodologies, and ways of knowing.’(Braun, 2017) As a discipline based on working around research methods that are both rational and creative(Friendly, 2006), I will continue to experiment with more materials and media to make more exciting data stories. For example, in the production of Unit05, I will try to incorporate the software technologies I have learned so far, as well as other printing processes and 3D digital printing, VR, AR, and other technologies if possible to broaden the possibilities of my data stories, so that the participants can rely on the data to experience the changes in the history of the 'access to information medium' and the feedback from society, presenting the audience with a data feast of perception.

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References 

/for reflection writing

Braun, S. (ed) 2017. Data Visualisation for Sucess. Victoria The Images Publishing Group.

Heller, S., Landers. R., 2014. Infographics Designers' Sketchbooks. Thames & Hudson Ltd.

Lupi, G. 2017. Data Humanism – A Visual Manifesto, Available at http:// giorgialupi.com/data-humanismmy- manifesto-for-a-new-data-wold, Accessed 08.06.2022

Kennedy, H. et al. 2020. Seeing Data http://seeingdata.org/developing- visualisation-literacy/
Friendly, M. (2006). "A Brief History of Data Visualization" (PDF). York University. Springer-Verlag.


/for portfolio

Perera, P.R.H., Soysa,E.S.S.,De Silva,H.R.S.,Tavarayan,A.R.P., Gamage M.P., and Weerasinghe,K.M. L.P.(2021) Virtual Makeover and Makeup Recommendation Based on Personal Trait Analysis, International Conference on Advancements in Computing (ICAC), 2021, pp. 288-293


Bella, M. and Bruce, H., 2012, Universal Methods of Design