Data Manifestation

Jose Gutierrez Professor Zahra Zafaverdi ARCH 3314 : Materiality in Formation

Data Manifestations: A Typological Investigaton into Data as Media and its Applications

Abstract Data Sculpting, Data Art, Data Analytics, Data Visualization, Data Simulation, Data physicalization.

These are all terms that one comes across when attempting to assemble an understanding of data represented as media. Whether it be physical, sonified, or purely visual; Data can be processed into many forms. These manifestations of data open the door to an intriguing conversation between matter and the immaterial. They force us to bridge the gap between the irrational, loose grip of perception and the objective truth of information.

The synthesis of the two microcosms within which our reality stands is revelatory. This research paper aims to further understand the processing of raw data into media as well as its possibilities and applications. Additionally we will critically examine vocabulary and terminology and find where it is lacking. In order to do so the paper will take place in three parts. The parts will proceed as follows:

A.) Typologies of Data representation

This section of the paper will analyze productions from several artists and studios in order to create a typology of data represented as media. The predetermined typologies are:

I.) Transformation

The transformation typology is one that is represented as an abstraction of the data. Less focused on analysis, this typology seeks to challenge how we perceive data. It manipulates as well as discriminates in order to produce a desired aesthetic effect. This typology mingles with the others and its categorization is fluid.

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II.) Representation

The truest form of data processing is representation. This typology prioritizes communication and legibility of the data over artistic representation. Being the most common, within this typology we find more industrious applica-tions. This however does not make it exempt from artistic and aesthetic opportunity.

III.) Materialization

The final typology is materialization. This typology is (for the most part) a physical, tangible, and interactive form of Data. It has visually stimulating properties as well as tangible ones. While being somewhat restrictive, it has promising potential in its application in materiality.

B.) Case Study This section will be worked in with out typologies select two projects that invite discourse, contradiction, and compromise. It will serve to test our new categorization standards and help us develop our vocabulary and understanding of the subject . The projects selected will be architectural, sculptural, and immaterial.

As of now one of our case studies will be the works from the book Monsoon as Method, Refik Anadol, Midjourney Studies, Center for spatial Research, The Mu-seum of Tomorrow, Seattle public Library.

C.) Conclusion The third installment will take the research and thoughts that were generated from our case study as well as typo-logical research and combine them into a cohesive argument. While it is unknown whether we will find clarity or further distort our perceptions of materiality and reality we can surely count on the discovery of the potential that data holds.

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Introduction As humanity further dives into the digital age, it becomes evident how all-encompassing this revolution has become. In almost every aspect, our lives are consumed through the medium of the machine and the data operations they perform. This data is collected, collated, and consumed on a daily basis and understanding this process and how it manifests is essential to the field of architecture. It is this process and how machines attempt to render reality using data, that we can refine and train ourselves to be more receptive to this change. As per John May, Images are the outputs of energetic processes defined by signalization, and these signals are what we mean when we say data.”

(2019). Through this definition we come to understand how machines attempt to exchange information in order to model reality using data. To further breakdown the output of this process we will need to define three typologies: Transformation, Representation, and Materialization.

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Transformation Transformation of data can be defined as the abstraction of the data. Less focused on analysis, this typology seeks to challenge how we perceive data. It mingles with the boundary of reality vs. representation. It manipulates as well as discriminates in order to produce a desired aesthetic effect.

It makes you doubt what you are looking at. Thus, by initiating the position of doubt in your mind, you begin to evaluate when and where and in what ways you believe in things (Young 2021). The sensory overload created by this manifestation is best exemplified by the work of Refik Anadol. In Machine Hallucinations: ISS dreams, snapshots of satellite imaging are processed and curated into a dynamic and swirling hive of particles attempting to create a multisensory experience. The original data sample is subverted and manipulated into a new surface image. This is the essence of transformation. It provides us with the decontextualized fragments of data in a system detached from reality. Attention thus becomes diffused into the background and we are left in a cognitive state of immersion.

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Representation

The next typology will be classified as representation. As discussed previously it can be seen as the truest form of data manifestations. It is the exchange of information between machine and human perception in order to achieve an image that represents the data as it was intended. While it may seem limiting, an interesting negotiation between expression and information needs to take place in the mind of the author. That same interaction is then transferred to the viewer who will ultimately judge the success of the production. The issue the author runs into with representation is the risk of separating too much from reality. This results in an unbalanced relationship between the image and the information. It is once this threshold is crossed, that representation becomes transformation. In order to further understand the implications of this, we will look at two selected works of representational data. The first will be taken from Monsoon as Method and Features John Cook’s rendering of winter moonsonal information over south east asia. The Second work features Serjan Burlak’s representation of Saturn’s moon orbits. By comparing these two images we can more easily discern the point at which representation becomes transformation.

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Representation Case Study

When observing these two images it is evident that data becomes a form of manipulation of the viewer’s attention. In Fig. 8 we can make assumptions about what we are observing with little context. If we are offered more information, we learn that it is a map of winter monsoon over India overlaid by the observational instruments that produce the climatic data used in drawing (Breemer 2022). There is a clear relation between method and production, and it results in a successful representation of data. On the other hand, Fig. 9 is much more vague and betrays the data by attempting to make an aesthetic argument. There is a contradiction in the way color, texture, and scale is used to portray the data. It is when the image subverts the data in this way that we inch closer to a transformation. In order for a data manifestation to remain representational it is important that our image does not betray the human senses.

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Materialization

The final typology is materialization. This typology is (for the most part) a physical, tangible, and interactive form of Data. It has visually stimulating properties as well as tangible ones. Materialization is best defined as a physical articulation of the surface (Young 2022). Further, it is the transmutation of data from the digital space into the physical, material space. It becomes a physical response to data, a glitch in haptic reality. This typology has the unique ability to bridge the gap between the optic, haptic, and algorithm. Data becomes a form and is distributed across a surface culminating in a material manifestation. Even when the production does not result in a physical entity, the materialization of data elicits a physical reaction/projection from the viewer when interacted with.

Confusion may arise when the result is not physical. In those cases, the other typologies take precedence and materialization becomes a facet . For example, when looking at Anadol’s work, a tactile force is present through the illusion of volume and texture. However, this is a feature of the production, not the ultimate manifestation of the data. A better example of materialization would be Projectors I by Millions. A conscious effort is made to sustain the exchange between image and the tectonic. According to Millions, the priority remains a perfect symmetry between the digital model and its fabricated object. Haptics becomes the priority even though a balanced transition from representation to materialization and vice versa occurs. In addition, we can also understand parametric architecture as a form of data materialization.

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Conclusion In conclusion, data as a medium and manifestation has opened up new possibilities in understanding the complex relationship between matter and the immaterial. The different typologies of data representation, including transformation, representation, and materialization, offer unique ways of engaging with data, challenging both our perception of reality and how we engage the data to produce a desired aesthetic or industrial effect.

Through our typological classifications,, it is clear that data representation can take on a multitude of forms, and each typology has its own strengths and weaknesses. Transformation can be incredibly powerful in challenging our perceptions and creating an immersive experience, but it also runs the risk of dissociating itself. This results in a separation between method and intent. Ultimately sacrificing material for impact. Representation, on the other hand, is the truest form of data manifestation, but must balance the exchange of information and artistic expression to avoid becoming too detached from reality. Lastly, materialization can provide a physical, tangible form of data across a surface, but is somewhat restricted in its manifestation by the laws of our physical reality. The case studies selected for this research paper have also helped us to understand how these typologies can be applied in different fields, including architecture, sculpture, and consumable media. However, as we continue to explore data representation, we must also critically examine the vocabulary and terminology used in this field to ensure that it accurately reflects the multifaceted nature of data.

Further investigations into the subject call for clarification and separation of how data is processed.

The implications of these different typologies within the context of our reality provide new insights and discoveries that will inspire further exploration into the potential of data as a material. It is of utmost importance that we refine our intent as we engage with data in order to maximize the potential of its manifestations.

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This is because we are entering the deep expanse that is the mind of the machine. It models reality in ways inaccessible to humans (Young 2021). By doing so we can successfully achieve a materialism that displays the multiple orders of materiality or the order of materialities between a phenomenological account of the interface between user and technology, an archaeological account of the physical infrastructure of the medium, and a sociological account of the cultural and economic forces that continue to shape both the technology itself and our interactions with it (Mitchell, Hansen 2010).

As we move further into the digital age, it is essential that we continue to refine and train ourselves to be more receptive to the advancements in media manifestations taking place, in order to fully understand the impact that data and its manifestations will have on materiality, media, and any other consumable form of production.

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Index

• Figure 1: Herwig Scherabon, Income Inequality (2016) • Figure 2: Adam Wes, Nebula of Knowledge (2022) • Figure 3: Refik Anadol Machine Halluciations (2018, Ongoing) • Figure 4: Michael Young, Photogrammetry scan of G i o v a n n i B a t t i s t a P i ra n e s i ’s a l t a r i n S a n t a M a r i a d e l P r i orato (1765), (Scans and Images by the Michael Young, 2019) • Figure 5-6: Ahmed Elgammal, Faceless Por traits Transcending Time (2019) • Figure 7: John Cook, map of winter monsoon over India overlaid by the observational instruments that produce the climatic data used in drawing (2021) • Figure 8: Serjan Burlak, Mathematics of Satrun (2018) • Figure 9-12: Millions, Projectors I (2018) • Figure 13: Zaha Hadid, Pleated Shell Structures, Sci-Arc Exhibition (2012) • Figure 14: JL Design and KORB, Human Movement and the Digital Arts (2013 • Figure 15: BairBailliet, The Corner - The Next Port of Call (2016)

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Bibliography

1. Young, Michael. Reality Modeled After Images. New York, NY: Routledge, 2023 2. Bremner, Lindsay, Beth Cullen, Christina Leigh Geros, John Cook, Harshavardhan Bhat, Anthony Powis, and Tom Benson. Monsoon as Method: Assembling Monsoonal Multiplicities. New York, NY: Actar Publishing, 2022.

3. May, John. Signal. Image. Architecture.: (Everything Is Already an Image). Columbia Books on Architecture and the City, 2019.

4. Mitchell, W. J. T., and Mark B. N. Hansen. Critical Terms for Media Studies. University of Chicago Press, 2010.

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