Databases & Divination

My initial project concept of exploring glitch between bodies of code (i.e. vocal recognition software) has been postponed to a day when the software gods are smiling upon me.

However the other area which I wished to explore was the concept of juxtaposing practices of divination with the algorithmic action of data mining.

I feel that pattern detection is a massive part of digital culture, especially ubiquitous computing. I am really interested in interrogating the idea of prediction that underpins the faith in data mining as a worthwhile endeavour. I am interested in this movement at all scales (for instance I consider it appropriate to deploy within science but nevertheless find the refiguring of science (it is now figured as a fourth paradigm of scientific enquiry) occurring therein politically interesting (from a science studies point of view). The area which interests me most is the application of data mining to social contexts, the notion that a form of knowledge alchemy can occur through weight of data aggregation and data mining algorithm execution.


So several areas therein interest me. One is the respective distillations of experience that occurs in divination and data mining. Non excitatory (and non substance – induced) divination tends to have an object of focus and there is a communion between diviner and the object. Per an Object Oriented philosophical approach I would be sympathetic to conceiving of a relational agency occurring in divination practice. In divination the distillation of experience is difficult to locate exactly, it is fluid. Data mining is reliant upon fast computers and database structures. But it is at the data entry stage of a data mining process that the distillation of experience occurs. In this regard I am very interested in the processes of classification highlighted by Leigh and Bowker Starr. I am also interested in what categorising an experience in this manner does relative to the intuitive process that characterises other divinatory practices.

I aim to explore this through various means of scrying: initially I drifted towards forms of lecanomancy (water gazing, using oil or ink drops as a focal point). However I have drifted towards focussing on tea reading, or tasseography (or tasseomancy), as the preferred practice.

The concept behind the project works as follows. I want a user to engage in the practice of tea leaf reading. They will follow the procedures of this process, and upon completion will be encouraged to enter their experience into a command line prompt. All the data entered by the user will be stored in a database.

The tasseomancy process will also be observed by the computer via webcam. Upon completion of the task the computer will take a picture of patterns of tea leaves in the tea cup. It will log the data as relevant to it’s processing of the pattern in the same database.

I hope to gradually accrue records in the database wherein the process of human intuition, machinic vision pattern detection and pattern detecting database algorithms will all interact in the one assemblage.

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Digitally Detecting Tea Leaves

IĀ have done some experiments to explore means by which I can explore tasseomancy as a site for critiquing the pattern seekingĀ prerogative of knowledge discovery in database (KDD) algorithms by juxtaposing divination alongside them.

The eventual aim is to explore the distillation of experience that occurs exclusive to each system, as I mentioned in my earlier post. This means some experiments into how a database and appropriate tables can be constructed to capture every aspect of the tea seers process and practice. In some ways I am setting this concept up to fail as I believe that something of this process will escape the intense categorisation which is a prerequisite of relational database architectures and their need for normalisation. In so doing maybe this will prompt reflection on how every database system, irrespective of their predictive prowess, is ultimately a modelling that holds more true to set theory logic than the nuances of our lived experiences (and said nuances being elided is not trivial given the faith and belief placed in the predictive power of data mining).

In order to fully explore KDD algorithms I will need a suitably large amount of data. That is unavailable to me at present so I need another area of interaction between the tea reader and the machine with which they will interface. A visual analysis of the tea leaf pattern left in the cup provides a ready pattern for the computer to interpret.

I have settled upon using a webcam and I’m currently exploring two ways of providing the computer a chance to see the tea leaf pattern. One method comes via a snapshot being taken after the tea pattern has been scrutinised by the tasseomancer.

The above photos are rough webcam snaps, exposure modifications will display pattern but it is important that exposure process can be simply automated by code


Another comes via the whole process of tea drinking being recorded via a webcam positioned at the base of the container from which the tea is drank. Doing this necessitated using a glass, which according to most tasseomancy practice is not ideal. However it does provide an interesting perspective on tea leaf reading. (see the video below, which is quite poor quality due to the fact that I am getting to grips with the exposure functions of Linux UVC webcam software)

Webcam Rig used to capture above video

Capturing the duration of the entire tea drinking process is something I would like to do, and also a period of time I would like to analyse. I am struck by the idea that duration is an important aspect of any of these introspective, gnostic (in the Peter J. Carroll sense) practices. This contrasts markedly with the types of temporality at work in the CPU crunching the numbers which determine the patterns discerned by the image analysis algorithms (silicon flip flops and clock times).

Once the software crimps have been ironed out and I get a clearer idea of the registers by which the machine will pattern analyse the tea leaf patterns I hope to engage with the tasseomancy practice in depth. In essence I will be the entity responsible for determining the data architecture which at some future data KDD algorithms will explore and generate new knowledge (defined within KDD discourse as “novel patterns of information – an epistemic shift in what we deem knowledge).

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