[ 0000 ]

Resolution Dispute 0000 : Materiality  “‘Material witness’ is a legal term; it refers to someone who has knowledge pertinent to a criminal act or event that could be significant to the outcome of a trial. In my work, I poach the term ‘material witness’ to express the ways in which matter carries trace evidence of external events. But the material witness also performs a twofold operation; it is a double agent. The material witness does not only refer to the evidence of event but also the event of evidence.”
- Schuppli, Susan. Dark Matters: an interview with Susan Schuppli, in: Living Earth, 2016.

“Materiality is reconceptualized as the interplay between a text's physical characteristics and its signifying strategies, a move that entwines instantiation and signification at the outset. This definition opens the possibility of considering texts as embodied entities while still maintaining a central focus on interpretation. It makes materiality an emergent property, so that it cannot be specified in advance, as if it were a pre-given entity. Rather, materiality is open to debate and interpretation, ensuring that discussions about the text's "meaning" will also take into account its physical specificity as well.”
- Hayles, N. Katherine. "Print is flat, code is deep: The importance of media-specific analysis." Poetics Today 25.1 (2004): 67-90.

A reflexive approach to materiality makes it possible to re-conceptualize materiality itself as ‘the interplay between a text’s physical characteristics and its signifying strategies’. Rather than thinking in the mediums’ material as fixed in physicality, a re-definition of materiality is useful because it opens the possibility of considering any text as embodied entity “while still maintaining a central focus on interpretation. In this view of materiality, it is not merely an inert collection of physical properties but a dynamic quality that emerges from the interplay between the text as a physical artifact, its conceptual content, and the interpretive activities of readers and writers.”

Reflections on materiality should not just happen on a technological level. To fully understand a work, each level of materiality should be studied: the physical and technological artifact, its conceptual content, and the interpretive activities of reader, artist and audience. [the choice of any] digital material is not innocent or meaningless. With enough knowledge of the material, an investigation into digital materialilty can uncover stories about the origin and history of the material, by others.


The slides underneath are from the course ‘Materiality’, which took place over three meetings during the New Media class ‘Beyond Resolution’ I thaught as substitute professor at the KHK (Kassel) in 2018. During these weeks we unpacked the term ‘materiality’ via a research into various file formats. The slides are clickable; they either link to the work reference or zoom. 


[ analogue ]

Beyond Resolution (2015)

Beyond Resolution soundtrack, remix by Ryan Maguire aka moDernisT.
Original: Beyond Resolution [Rosa Menkman, Professional Grin Knalpot remix]

On process, from Ryan Maguires website :

""moDernisT" was created by salvaging the sounds lost in compression via the MP3 and MP4 codecs.

This audio is thus comprised of the audio that would normally be deleted during the mp3 compression of the original file (like an inversed compression).

Beyond Resolution :: Pattern recognition lost its resolution.
15:30 min AV live performance registration that took place during Static Gallery: Syndrome 3.X Loop Systems, Liverpool, January 2015.

Featuring video images by Alexandra Gorczynski and sounds from Professional Grin by Knalpot. Sound mastering by Sandor Caron.

[ ecology ]
An Ecology of Compression Complexities (2017)

A map of the different complexities of compression artifacts featuring the realms of :

⦁ Dots
(pixels, dither, coordinates) 


━ Lines
(interlacing, interleaving, scan line, border, beam)

Collapse of PALTacit:Blue, Beyond Resolution performance, 

▩ Blocks
(macroblocks, cluster) 

⌇ Wavelets

⟗ Vectors
(3D obj, time encoding in MPEG4)



About the Ecology of Compression Complexities / not being able to connect, read and write or the refusal of connection

A modern translation of the 1884 Edwin Abbott Abbott roman "Flatland", explains some of the algorithms at work in digital image compression.
Inspired by Syphon, an open source software by Tom Butterworth and Anton Marini, in DCT:SYPHONING, an anthropomorphised DCT (Senior) narrates its first SYPHON (data transfer) together with DCT Junior, and their interactions as they translate data from one image compression to a next (aka the “realms of complexity”).

As Senior introduces Junior to the different levels of image plane complexity, they move from blocks (the realm in which they normally resonate), to dither, lines and the more complex realms of wavelets and vectors. Junior does not only react to old compressions technologies, but also the newer, more complex ones which ‘scare' Junior, because of their 'illegibility'.  

DCT:SYPHONING at JMAF, Tokyo, Japan, 2017

One screen version.

Production of DCT:SYPHONING
DCT:SYPHONING was first commissioned by the Photographers Gallery in London, for the show Power Point Polemics. This version was on display as a Powerpoint Presentation; a .ppt (Jan - Apr 2016).

A 3 channel video installation was conceived for the 2016 Transfer Gallery's show "Transfer Download", first installed at Minnesota Street Project in San Francisco (July - September, 2016)

DCT:SYPHONING released as VR, commissioned as part of DiMoDA’s Morphe Presence and later as stand alone (2017).

>> Download the VR / standalone app for 

DCT:SYPHONING @the Current museum for contemporary art, NY, USA 

PDF Version 

The full edition of Lune Magazine 3 can be downloaded here:

This edition was guest edited by Nathan Jones

Spanish Translation

[ethnography of DCT]

<href: Cory Arcangel: on Compression, 2007>

A Discrete Cosine Transform or 64 basis functions of the JPEG compression (Joint Photographic Experts Group) 8 x 8 pixel macroblocks.

The .JPEG compression consists of these six subsequent steps
1. Color space transformation. Initially, the image has to be transformed from the RGB colorspace to
Y′CbCr. This colorspace consists of three components that are handled separately; the Y’ (luma or brightness) and the Cb and Cr values; the blue-difference and red-difference Chroma components.
2. Downsampling. Because the human eye doesn’t perceive small differences within the Cb and Cr space very well, these elements are downsampled, a process that reduces its data dramatically.
3. Block splitting. After the colorspace transformation and downsampling steps, the image is split into 8 x 8 pixel tiles or macroblocks, which are transformed and encoded separately.
4. Discrete Cosine Transform. Every Y’CbCr macroblock is compared to all 64 basis functions (base cosines) of a Discreet Cosine Transform. A value of resemblance per macroblock per base function is saved in a matrix, which goes through a process of reordering.
5. Quantization. The JPEG compression employs quantization, a process that discards coefficients with values that are deemed irrelevant (or too detailed) visual information. The process of quantization is optimized for the human eye, tried and tested on the Caucasian Lena color test card.
Effectively, during the quantization step, the JPEG compression discards most of all information within areas of high frequency changes in color (chrominance) and light (luminance), also known as high contrast areas, while it flattens areas with low frequency (low contrasts) to average values, by re-encoding and deleting these parts of the image data. This is how the rendered image stays visually similar to the original – least to human perception. But while the resulting image may look similar to the original, the JPEG image compression is Lossy, which means that the original image can never be reconstructed.
6. Entropy coding. Finally, a special form of lossless compression arranges the macroblocks in a zigzag order. A Run-Length Encoding (RLE) algorithm groups similar frequencies together while Huffman coding organizes what is left.

Revealing the surface and structure of the image *
<href: Ted Davis: ffd8, 2012>

A side effect of the JPEG compression is that the limits of the images’ resolution – which involve not just the images’ number of pixels in length and width, but also the luma and chroma values, stored in the form of 8 x 8 pixel macroblocks – are visible as artifacts when zooming in beyond the resolution of the JPEG.
Because the RGB color values of JPEG images are transcoded into Y’CbCr macroblocks, accidental or random data replacements can result into dramatic discoloration or image displacement. Several types of artifacts can appear; for instance ringing, ghosting, blocking, and staircase artifacts. The relative size of these artifacts demonstrates the limitations of the JPEGs informed data: a highly compressed JPEG will show relatively larger, block-sized artifacts.

▩ [ DCT encryption ] 
<href: Hito Steyerl: How Not to Be Seen, 2013>

The legibility of an encrypted message does not just depend on the complexity of the encryption algorithm, but also on the placement of the data of the message. Here they are closely connected to resolutions: resolutions determine what is read and what is unseen or illegible.

DCT ENCRYPTION (2015) uses the aesthetics of JPEG macroblocks to mask its secret messages on the surface of the image, mimicking error. The encrypted message, hidden on the surface is only legible by the ones in the know; anyone else will ignore it like dust on celluloid.

While the JPEG compession consists of 6 steps, the basis of the compression is DCT, or Discrete Cosine Transform. During the final, 6th step of the JPEG compression, entropy coding, a special form of lossless data compression, takes place. Entropy coding involves the arranging the image components in a "zigzag" order, using run-length encoding (RLE) to group similar frequencies together.
How Not to be Read, a recipe using DCT:

  • Choose a lofi JPEG base image on which macroblocking artifacts are slightly apparent. This JPEG will serve as the image on which your will write your secret message.
  • If necessary, you can scale the image up via nearest neighbour interpolation, to preserve hard macroblock edges of the base image.
  • Download and install the DCT font
  • Position your secret message on top of the JPEG. Make sure the font has the same size as the macroblock artifacts in the image
  • Flatten the layers (image and font) back to a JPEG. This will make the text no longer selectable and readable as copy and paste data.

︎ for the #3D Additivist Cookbook.
︎ DCT won the Crypto Desgin Challenge Award in 2015.

A Discrete Cosine Transform simplified to make a monochrome .ttf font and iRD logo. In the logo RLE 010 000 - 101 1111 signifies the key to the DCT encryption: 010 000 - 101 1111 are the binary values of the 64 most used ASCII glyphs, which are then mapped onto the DCT in a zig zag order (following RLE).
Discrete Cosine Transform (DCT) was first conceived for the Crypto Design Challenge and won a first price. 

A recipe using DCT” was released in the #Additivism cookbook.

Mesmerized by the screen, focusing on the moves of a next superhero, I was conditioned to ignore the dust imprinted on the celluloid or floating around in the theater, touching the light of the projection and mingling itself with the movie.

The dust – micro-universes of plant, human and animal fibers, particles of burnt meteorites, volcanic ashes, and soil from the desert – could have told me stories reaching beyond my imagination, deeper and more complex than what resolved in front of me, reflecting from the movie screen.
… But I never paid attention.

I focused my attention to where I was conditioned to look: to the feature, reflecting from the screen. All I saw were the images. I did not see the physical qualities of the light nor the materials making up its resolution; before, behind, and beyond the screen.

Decennia of conditioning the user to ignore these visual artifacts and to pay attention only to the overall image has changed these artifacts into the ultimate camouflage for secret messaging. Keeping this in mind, I developed DCT.

Premise of DCT is the realisation that the legibility of an encrypted message does not just depend on the complexity of the encryption algorithm, but also on the placement of the message. This encrypted message, hidden on the surface of the image, is only legible by the ones in the know; anyone else will ignore it. Like dust on celluloid, DCT is mimics JPEG error. It appropriates the algorithmic aesthetics of JPEG macroblocks to stenographically mask a secret message, mimicking error. The encrypted message, hidden on the surface of the image, is only legible by the ones in the know.

DCT at MOTI for the Crypto design challenge 
encrypted text:
The legibility of an encrypted message does not just depend on the complexity of the encryption algorithm, but also on the placement of the data of the message.
The Discreet Cosine Transform is a mathematical technique. In the case of the JPEG compression, a DCT is used to describe a finite set of patterns, called macroblocks, that could be described as the 64 character making up the JPEG image, adding lumo and chroma values as ‘intonation’.
If an image is compressed correctly, its macroblocks become ‘invisible’. The incidental trace of the macroblocks is generally ignored as artifact or error.
Keeping this in mind, I developed DCT. DCT uses the esthetics of JPEG macroblocks to mask its secret message as error. The encrypted message, hidden on the surface of the image is only legible by the ones in the know.