02 CRITICAL REFLECTION
MA DATA/23 UNIT 02
JUNE 2023
Following my love for visual communication, I first became interested in Data Visualisation through the design and the work of Casey Reas, and Laurie Frick, and later the highly accessible approach of Dear Data (2016), by practitioners Stefanie Posavec and Giorgia Lupi. Since then I have been fascinated in exploring how shape and colour can be used to share rich and multi-faceted information; make the invisible tangible; the unshared available and the complex digestible. During my 28 weeks so far on the MA, I have continuously had the opportunity to challenge, redefine and adapt what data visualisation means to me; through synthesising with new materials, questions and collaborations.
01 LAYERS, MULTIPLICITY, SUBJECTIVITY:
Drucker (2014) asserts that “Visualisations are always interpretations—data does not have an inherent visual form that merely gives rise to a graphic expression.”, revealing how there are endless ways to interpret and in turn decide how we visualise data.
Early in the course, we discussed the subjectivity, ambiguity and abstraction of data. During my first few weeks on the course, I came across the book All the Things I Lost in the Flood (2018) by Laurie Anderson. The quote “Language is approximate-it is a complicated code. Even when you say a simple word like "dog," everyone envisions a completely different dog.“ (Anderson, 2018, p.12), really stuck in my mind and led me to consider how there are infinite options of deciphering, processing and interpreting information, aligning with Giorgia Lupi’s (2017) Data humanism approach that advocates for a “personal approach” because “subjectivity and context play a big role in understanding” (Lupi, 2017).
While working on the PLASTIC CARRIER BAGS book I considered these ideas of multiple perspectives and interpretations. I was interested in how I could clearly “Show the data” (Tufte, 2001) from the supermarkets, and then further show layers of qualitative context, and information extracted from the bag itself. I integrated these perspectives as ‘layers’, by creating a modular publication that allowed the viewer to explore different combinations and presentations of the data.
Exploring ways to show and embrace multiple interpretations and perspectives is highly positive to me because it allows us to question the objectivity of data and expose how it is constructed, further embodying Drucker’s questioning of how can “interpretation, ambiguity, inference, and qualitative judgement take priority over quantitative statements and presentations of ''facts’’?“ (Drucker, 2014, p.7).
02 MATERIALS, POSSIBILITIES, COLLABORATIVE LEARNING:
A real highlight of the course has been the opportunity to learn and ideate through physical making. Practitioners like Lupi embody this interdisciplinary approach and welcome the “opportunity to play with materials and contexts that are normally not associated with this discipline” as a means to “change our relationship with data” (Lupi, cited in Olsen, 2019).
This interdisciplinary approach became an essential driving force during our COLLABORATIVE PRACTICE. As a group, we each led workshops that involved: collaborative drawing, collage and creating shared drawing tools from various materials. This further allowed us to form unexpected outcomes through adapting to each other, new materials and physical space.
Experimentation with new materials was also an exciting way to ideate and sketch when working on FADING COLOURS. We experimented with watercolour, salt and bleach to form visual textures to communicate data about coral reef bleaching. Through using these textures in our final visual we could communicate our storytelling in a more emotive way, resonating with the third Data Feminism principle “Elevate emotion and embodiment.” (Klein and D’Ignazio, 2020)
My experiences with an interdisciplinary approach have opened up new improvisations, ways of thinking, fluidity and playfulness that have manifested into the ideation and iteration stages in my practice. I am further intrigued by how using physical materials can align with the seventh Data Feminism Principle to “Make Labor Visible” so that it can be “recognized” and “valued” (Klein and D’Ignazio, 2020, p.18) whilst allowing room for interpretation, alluding to Lupis’ argument to “embrace imperfection and approximation” (Lupi, 2017).
03 PERCEPTIONS, FLUCTUATIONS AND ENGAGEMENT:
I am interested in the ways we perceive data, and how data is always framed as being something that we collect by “making sense of the world through exclusion” (Onuoha, 2018), in a similar way to how “the photographic image is always framed, selected out of the profilmic experience in which the photographer stands, points, shoots” (Gitelman, 2013, p.5).
This helps me to consider the limitations of what the data can show, as Thorp observes, data is “as much a record of the human doing the measuring as it is of the thing that is being measured” (Thorp, 2021, p.47). When collecting live data for SOLAR SHADOWS, it highlighted the limitations of quantity, accuracy, duration and scale of data we could collect first-hand and as a result translate in our visual outcomes.
Furthermore, Ikeda explains that he views data as “a building block of information, like a note of a frequency” (Ikeda, cited in Bruce-Jones, 2021) this alludes to how data is not static because it can change or be added to, further suggesting a limit to how much can be perceived by the viewer. I considered this for SOUND, CHAOS AND THE SKY by developing a real-time generative pattern, allowing viewers' experience of their individual commute to be translated into a visual language that forms an interconnected pattern.
Going forward in my practice, I am interested in developing the ways I can use live data to implement interactions and fluctuation in my visual output. I would further like to explore how I can use design to give options to engage at different levels depending on my viewer's interest and time allocation, implementing a layered approach to complexity, inspired by the Ben Shneiderman mantra:'Overview first, zoom and filter, then details-on-demand' (Shneiderman cited in Craft and Cairns, n.d.).
CONCLUDING THOUGHTS:
The experiences on the course so far have been very formative to how I will carry forward data visualisation into my final major project and future career. Reflecting on these experiences, I have realised the various ‘pivot points’ that have (re)shaped my practice and (re)thinking towards data visualisation, revealing new possibilities and outcomes.
I feel very excited and optimistic about the direction of data visualisation. I am greatly interested in continuing to consider how I can communicate fluctuation and constraints in data, present multiple perspectives and perhaps change perceptions about data.
REFERENCES:
Anderson, L. (2018). All the things I lost in the flood : essays on pictures, language, and code. New York, Ny: Rizzoli Electa.
Bruce-Jones, H. (2021). Ryoji Ikeda Presents: data-verse. [online] Fact Magazine. Available at: https://www.factmag.com/2021/05/20/ryoji-ikeda-presents-data-verse/ [Accessed 28 Dec. 2022].
Craft, B. and Cairns, P. (n.d.). Beyond Guidelines: What Can We Learn from the Visual Information Seeking Mantra? Ninth International Conference on Information Visualisation (IV’05). doi:https://doi.org/10.1109/iv.2005.28.
D’Ignazio, C. and Klein, L. (2019). Feminist Data Visualization. [online] Academia.edu. Available at: https://www.academia.edu/28173807/Feminist_Data_Visualization [Accessed 5 Dec. 2022].
Drucker, J. (2014). Graphesis : visual forms of knowledge production. Cambridge, Massachusetts: Harvard University Press.
Frick, L. (2019). LAURIE FRICK. [online] LAURIE FRICK. Available at: https://www.lauriefrick.com/ [Accessed 7 Jun. 2023].
Gitelman, L. (2013). Raw data is an oxymoron. Erscheinungsort Nicht Ermittelbar: Verlag Nicht Ermittelbar, p.5.
Klein, L.F. and D’Ignazio, C. (2020a). Data feminism. Cambridge, Massachusetts: The Mit Press.
Lupi, G. (n.d.). giorgialupi. [online] giorgialupi. Available at: http://giorgialupi.com/ [Accessed 7 Jun. 2023].
Lupi, G. and Posavec, S. (2016). Dear Data. Chronicle Books.
Olsen, K. (2019). Giorgia Lupi on Joining Pentagram, Data and Finding Inspiration Everywhere. [online] COOL HUNTING. Available at: https://coolhunting.com/design/giorgia-lupi-joining-pentagram-interview/ [Accessed 9 Jan. 2023].
Onuoha, M. (2018). Nichons-Nous Dans L’Internet “What is Missing Is Still There” [online] Available at: https://static1.squarespace.com/static/5147c437e4b096a97cf3defd/t/5af0698e8a922ddd8dd4cd87/1525705104023/nichons-nous-onuoha1.pdf [Accessed 12 Dec. 2022].
Posavec, S. (n.d.). Stefanie Posavec. [online] Stefanie Posavec. Available at: https://www.stefanieposavec.com/ [Accessed 7 Jun. 2023].
PrintMag (2017). Data Humanism: The Revolutionary Future of Data Visualization. [online] PrintMag. Available at: https://www.printmag.com/article/data-humanism-future-of-data-visualization/ [Accessed 22 Oct. 2002].
Reas, C. (2001). REAS.com is a database for Casey REAS. [online] reas.com. Available at: https://reas.com/ [Accessed 7 Jun. 2023].
Thorp, J (2021). Living in Data. New York: MCD Farrar, Straus & Giroux.
Tufte, E.R. (2001). The Visual Display of Quantitative Information. Connecticut: Graphics Press.
01 LAYERS, MULTIPLICITY, SUBJECTIVITY:
Drucker (2014) asserts that “Visualisations are always interpretations—data does not have an inherent visual form that merely gives rise to a graphic expression.”, revealing how there are endless ways to interpret and in turn decide how we visualise data.
Early in the course, we discussed the subjectivity, ambiguity and abstraction of data. During my first few weeks on the course, I came across the book All the Things I Lost in the Flood (2018) by Laurie Anderson. The quote “Language is approximate-it is a complicated code. Even when you say a simple word like "dog," everyone envisions a completely different dog.“ (Anderson, 2018, p.12), really stuck in my mind and led me to consider how there are infinite options of deciphering, processing and interpreting information, aligning with Giorgia Lupi’s (2017) Data humanism approach that advocates for a “personal approach” because “subjectivity and context play a big role in understanding” (Lupi, 2017).
While working on the PLASTIC CARRIER BAGS book I considered these ideas of multiple perspectives and interpretations. I was interested in how I could clearly “Show the data” (Tufte, 2001) from the supermarkets, and then further show layers of qualitative context, and information extracted from the bag itself. I integrated these perspectives as ‘layers’, by creating a modular publication that allowed the viewer to explore different combinations and presentations of the data.
Exploring ways to show and embrace multiple interpretations and perspectives is highly positive to me because it allows us to question the objectivity of data and expose how it is constructed, further embodying Drucker’s questioning of how can “interpretation, ambiguity, inference, and qualitative judgement take priority over quantitative statements and presentations of ''facts’’?“ (Drucker, 2014, p.7).
02 MATERIALS, POSSIBILITIES, COLLABORATIVE LEARNING:
A real highlight of the course has been the opportunity to learn and ideate through physical making. Practitioners like Lupi embody this interdisciplinary approach and welcome the “opportunity to play with materials and contexts that are normally not associated with this discipline” as a means to “change our relationship with data” (Lupi, cited in Olsen, 2019).
This interdisciplinary approach became an essential driving force during our COLLABORATIVE PRACTICE. As a group, we each led workshops that involved: collaborative drawing, collage and creating shared drawing tools from various materials. This further allowed us to form unexpected outcomes through adapting to each other, new materials and physical space.
Experimentation with new materials was also an exciting way to ideate and sketch when working on FADING COLOURS. We experimented with watercolour, salt and bleach to form visual textures to communicate data about coral reef bleaching. Through using these textures in our final visual we could communicate our storytelling in a more emotive way, resonating with the third Data Feminism principle “Elevate emotion and embodiment.” (Klein and D’Ignazio, 2020)
My experiences with an interdisciplinary approach have opened up new improvisations, ways of thinking, fluidity and playfulness that have manifested into the ideation and iteration stages in my practice. I am further intrigued by how using physical materials can align with the seventh Data Feminism Principle to “Make Labor Visible” so that it can be “recognized” and “valued” (Klein and D’Ignazio, 2020, p.18) whilst allowing room for interpretation, alluding to Lupis’ argument to “embrace imperfection and approximation” (Lupi, 2017).
03 PERCEPTIONS, FLUCTUATIONS AND ENGAGEMENT:
I am interested in the ways we perceive data, and how data is always framed as being something that we collect by “making sense of the world through exclusion” (Onuoha, 2018), in a similar way to how “the photographic image is always framed, selected out of the profilmic experience in which the photographer stands, points, shoots” (Gitelman, 2013, p.5).
This helps me to consider the limitations of what the data can show, as Thorp observes, data is “as much a record of the human doing the measuring as it is of the thing that is being measured” (Thorp, 2021, p.47). When collecting live data for SOLAR SHADOWS, it highlighted the limitations of quantity, accuracy, duration and scale of data we could collect first-hand and as a result translate in our visual outcomes.
Furthermore, Ikeda explains that he views data as “a building block of information, like a note of a frequency” (Ikeda, cited in Bruce-Jones, 2021) this alludes to how data is not static because it can change or be added to, further suggesting a limit to how much can be perceived by the viewer. I considered this for SOUND, CHAOS AND THE SKY by developing a real-time generative pattern, allowing viewers' experience of their individual commute to be translated into a visual language that forms an interconnected pattern.
Going forward in my practice, I am interested in developing the ways I can use live data to implement interactions and fluctuation in my visual output. I would further like to explore how I can use design to give options to engage at different levels depending on my viewer's interest and time allocation, implementing a layered approach to complexity, inspired by the Ben Shneiderman mantra:'Overview first, zoom and filter, then details-on-demand' (Shneiderman cited in Craft and Cairns, n.d.).
The experiences on the course so far have been very formative to how I will carry forward data visualisation into my final major project and future career. Reflecting on these experiences, I have realised the various ‘pivot points’ that have (re)shaped my practice and (re)thinking towards data visualisation, revealing new possibilities and outcomes.
I feel very excited and optimistic about the direction of data visualisation. I am greatly interested in continuing to consider how I can communicate fluctuation and constraints in data, present multiple perspectives and perhaps change perceptions about data.
Anderson, L. (2018). All the things I lost in the flood : essays on pictures, language, and code. New York, Ny: Rizzoli Electa.
Bruce-Jones, H. (2021). Ryoji Ikeda Presents: data-verse. [online] Fact Magazine. Available at: https://www.factmag.com/2021/05/20/ryoji-ikeda-presents-data-verse/ [Accessed 28 Dec. 2022].
Craft, B. and Cairns, P. (n.d.). Beyond Guidelines: What Can We Learn from the Visual Information Seeking Mantra? Ninth International Conference on Information Visualisation (IV’05). doi:https://doi.org/10.1109/iv.2005.28.
D’Ignazio, C. and Klein, L. (2019). Feminist Data Visualization. [online] Academia.edu. Available at: https://www.academia.edu/28173807/Feminist_Data_Visualization [Accessed 5 Dec. 2022].
Drucker, J. (2014). Graphesis : visual forms of knowledge production. Cambridge, Massachusetts: Harvard University Press.
Frick, L. (2019). LAURIE FRICK. [online] LAURIE FRICK. Available at: https://www.lauriefrick.com/ [Accessed 7 Jun. 2023].
Gitelman, L. (2013). Raw data is an oxymoron. Erscheinungsort Nicht Ermittelbar: Verlag Nicht Ermittelbar, p.5.
Klein, L.F. and D’Ignazio, C. (2020a). Data feminism. Cambridge, Massachusetts: The Mit Press.
Lupi, G. (n.d.). giorgialupi. [online] giorgialupi. Available at: http://giorgialupi.com/ [Accessed 7 Jun. 2023].
Lupi, G. and Posavec, S. (2016). Dear Data. Chronicle Books.
Olsen, K. (2019). Giorgia Lupi on Joining Pentagram, Data and Finding Inspiration Everywhere. [online] COOL HUNTING. Available at: https://coolhunting.com/design/giorgia-lupi-joining-pentagram-interview/ [Accessed 9 Jan. 2023].
Onuoha, M. (2018). Nichons-Nous Dans L’Internet “What is Missing Is Still There” [online] Available at: https://static1.squarespace.com/static/5147c437e4b096a97cf3defd/t/5af0698e8a922ddd8dd4cd87/1525705104023/nichons-nous-onuoha1.pdf [Accessed 12 Dec. 2022].
Posavec, S. (n.d.). Stefanie Posavec. [online] Stefanie Posavec. Available at: https://www.stefanieposavec.com/ [Accessed 7 Jun. 2023].
PrintMag (2017). Data Humanism: The Revolutionary Future of Data Visualization. [online] PrintMag. Available at: https://www.printmag.com/article/data-humanism-future-of-data-visualization/ [Accessed 22 Oct. 2002].
Reas, C. (2001). REAS.com is a database for Casey REAS. [online] reas.com. Available at: https://reas.com/ [Accessed 7 Jun. 2023].
Thorp, J (2021). Living in Data. New York: MCD Farrar, Straus & Giroux.
Tufte, E.R. (2001). The Visual Display of Quantitative Information. Connecticut: Graphics Press.