Geert

Is Geert cheating? #mask

Is the role you played� different person or more a ‘super self?’

If you would be a super hero, what would be your superpower skill? What would be your weakness?

Eszter

positioning herself as being seen as a� god as a comment� on performance making, addressing us from above as ‘subjects’/
creating a hierarchy

This page includes a series of data models that was produced during a three days work session in a.pass May 2018. (Proposed by Sina Seifee during the Summer research cycle BLOCK 18/II Milieus, associations, sieves and other matters… curated by Pierre Rubio.)

The aim was to create a “filter” for the artistic research projects, each one expressed in a “pad” (textual group feedback using ETHERPAD), to increase/enhance the descriptive power of the languages we use (English, semantics, semblance, information, logic, analogy, abstraction, etc.). To propose a verbal discussion training in making a synthetic meta-linguistic abstractions (and then on a given computer hardware) to construct a “thing” (call it a data model) that enables describing the problem of Building Abstractions (an isolation built with semantics) with Data (a research project presentation performance and its textual feedback).

The list below presents three different digital tropes of data-modeling that was practiced by the participant:

notes and description of the workshop

INTERESTS OF THE WORKSHOP:

computational literacy (including data-collection, librarianship) as part of our diversity-work and our articulation-work (go to #terminology)
differential production of languages (English, computer, non-sign languages, etc.)
the labor of knowledge-work (in research institution and collective everyday, including using computers)
shifts in topology (the ongoing reworking of bodily boundaries of each of our research practices)

PRACTICE:

We want to investigate how each rhetoric of presentation and its digestive techniques can be expressed in terms of data model, or “filter,” and how this filter translates its own politics into metadata.
And what happens in linking the symbolic space of data-model to the (relational, procedural, emotional) qualities of the researches of participants?

We worked on the a.pass 2018 summer’s block’s opening week feedbacks and process them in a diagram like this:

feedback → quasi object → structured knower → data
(or technically:)
semantic in flux → persistence statements → object repository → identifiers

Tuesday, Wednesday, and Thursday were spent on the creation of “quasi objects.”

I proposed some (well-intended but not tested) internal categories: stickiness, zoom, cheat, vulgar

And these categories produce three topologies:
1. ramp
2. nest
3. skew

This is a maneuver to replace the question of ‘strategy’ to ‘topology’, the first act of making quasi-objects.

ramp: sequential, one dimensional, ‘sliders’
nest: fractal, serializable, arborescent, ‘comments’
skew: verb-active, streching, ‘2D field color picker pointer’

Each is “queryable” in different ways and propose different difficulties. Each of them adapted from an existing technologies (range sliders, commenting, color pickers). Each embeds one of: colors, doings, values

slider: marking everything with decimals
comments: hypertextualizing
field picker: spreading

this webpage (https://filters.apass.be/) refers to cleaning up the ‘object repository’ and the work of making ‘identifiers’.

(latest update: 27.Feb 2019)

TERMINOLOGY:

(The following propositions are enabled by the epistemologies and positions in the writings and teachings of Scout Calvert, Katie King, and Geoffrey Bowker.)

articulation-work: the labor necessary to make technologies fit together seamlessly

diversity-work: a kind of work in which we learn about the damage we cause, and of how “causes” are understood as “damage”

librarianship: a work that hooks up people with their technologies

data abstraction: a *technique of isolating* (the parts of your mini-language that deal with) how data/info objects are ‘represented’ from (the parts of your mini-language that deal with) how data/info objects are ‘used’ (—> i addressed this in my fable workshop in a totally different epistemology)

model: your object decomposed into *computational compound objects* (each with their own time-varying local state variables)

(representation of data and control over data:)
modular: localized part of the system that are produced by the perception of the system
objective: viewing a large system as a collection of distinct objects. concerned with how a computational object can change and yet maintain its identity
streamous: information that flow in the system. its evaluation is delayed. infinite list

metadata: machine-readable persistence statements

digital interface: discrete object of your “research problem” that refers to something outside the cri (outside the digital model)

topology: a (proposed) body-plan to investigate questions of *connectivity* and *boundaries*, in order to find out what remains invariant as a result of transformation. this will direct us to propose (well-intended but not tested) *transversal objects*.
to be able to propose: in the culture of each pad+participant+research what connects and joins, what delinks and disconnects.

filters

Maurice

Geert

Caterina

Eszter