# Performing Data

## session 01: Intro Lecture :performing_arts: :desktop_computer:
:hourglass_flowing_sand: 60 min

Joana Chicau is a graphic designer, coder, researcher — with a background in dance. She researches the intersection of the body with the constructed, designed, programmed environment, aiming at widening the ways in which digital sciences is presented and made accessible to the public. The latter has been informing a practice and exploration of various forms and formats — interweaving web programming with choreography — from the making of online platforms to performances or workshops. In parallel Chicau has been actively participating and organizing events involving multi-location collaborative coding, algorithmic improvisation, open discussions on digital equity and activism.


* [website;](https://joanachicau.com/)
* [list of live coding projects;](https://jobcb.github.io/)
* [screenshots archive;](https://www.are.na/joana-chicau/web-choreographies-other-stories)
* [staging errors videos list;](https://www.youtube.com/playlist?list=PLkRYCVc1KXTU1S47T_0GlUpKtz3MQkthA)

### ::: Task 01 :::
:hourglass_flowing_sand: 60 min

#### Creating a 'hand-made' dataset;

In groups:
1. choose a specific theme for your dataset collection:
1.1. choose either _text_ or _image_ ;
1.2. make sure it is part of everyone's routine and easy to collect;
2. reflect on: _audience_ and _context_; consider what could the dataset be used for? and for whom?
3. discuss if alongside the data itself you will be collecting any metadata.
4. start collecting some examples so the group builds a common understanding of your dataset.

**Next class each group member will bring 7-10 data pieces printed out in paper.**

_References:_


> Myriad (Tulips) is an installation of thousands of hand-labeled photographs of tulips; these photographs were later used as the dataset for Mosaic Virus 2018 and Mosaic Virus 2019. By choosing to make the dataset an artwork it draws attention to the skill, labour and time that goes into constructing it, whilst also helping to expose the human element in machine learning, usually hidden by algorithmic processes.

* [by Anna Ridler](https://annaridler.com/)
* [Data Inventory Excercise by Kit Kuksenok](https://criticalcode.recipes/contributions/critical-data-practice-at-home-and-with-friends)
* [Anatomies of Intelligence by Joana Chicau and Jonathan Reus](https://anatomiesofintelligence.github.io/)
* [Other projects by Joana Moll](https://www.janavirgin.com);
* [Tega Brain](http://tegabrain.com/)

## session 02: Rehearsal;

> “To dramatize data, you must first understand it. You analyse it, play with it, try to find relationships, try to infer the events that took place, and extract stories and meaning.
> And then you throw it all away. Chuck it in the bin, and wipe your hands clean. All that’s left is your understanding of the processes that gave rise to the data and the events and relationships within.” - [Memo Akten and Liam Young](https://www.memo.tv/works/#performance)

### ::: Task 02 :::
:hourglass_flowing_sand: 15 min

In groups:
1. present to each other the data you have collected:
2. think of words to categorize your data;
2.1. what vocabularies emerge from the categorization and analysis of the dataset? what can be 'put into words' and what is left unspoken?
3. map your dataset: arrange the data in space according to similarities and differences;

### ::: Task 03 :::
:hourglass_flowing_sand: 15 min

In groups:

1. return to the data you collected as group, and look again it with choreographic lenses 👓 . Re-organize the data according to some of the principles below:


* Schema from [12 choreographic principles — Wayne Mcgregor](https://waynemcgregor.com/learning/resources/)

What are the differences you see when looking at it from different viewpoints?

__{BREAK}__

### ::: Task 04 :::
:hourglass_flowing_sand: 30 min

1. Think of ways how to 'perform' or 'embody' your dataset.
1.1 Let the viewpoints from before inform how you will re—present your data.
1.2 Consider what are elements you want to emphasise from your data.
1.3 Try applying different rhythms, using voice, silence, other sounds, gestures to re—>_present_ your datasets.

__{BREAK}__

### ::: Task 05 :::
:hourglass_flowing_sand: 20 min

1. WIP SHOW TIME! Each group takes approx. 5minutes to present.

:hourglass_flowing_sand: 10 min

Wrap-up discussion round.

## session 03: Recap;

*Friday 13th of May (13-14h) — research and grouping;*

**Brief:** we will further discuss how to create 'situations' around data that embrace audience participation. We will cover various methodologies and documentation strategies which can be challenging when creative 'performative' work.

At the end of the these workshop series each group will have realised and documented their projects.

---

We will be starting from the datasets created in the past session. Group may choose to use a different dataset if readily available.

**::: Task :::** bring news articles that relate to your datasets. Aim at:

* * finding as recent news as possible (*for eg.: from the last 5 years*);
* * finding news from contexts and realities you are close to (*for eg.: familiar places; products you regularly consume; industries or communities you are knowledgeable about*);
* * complement the news with historical facts that can provide further context;

## session 04: Workshop;

*Wed 18th of May (14h-16h) — practical workshop;*

### ::: Task ::: Newspaper Theatre by Boal

:hourglass_flowing_sand: 30 min + 15 min

[The Newspaper Theatre](https://en.wikipedia.org/wiki/Theatre_of_the_Oppressed) is a system of techniques devised to give the audience a way to transform daily news articles or any non-dramatic pieces to theatrical scene. The strategies are as follows:

* **Simple Reading**: news item read, detached from the context of the newspaper (which makes it false or controversial).
* **Crossed Reading**: two news item are read in alternating form, complementing or contrasting each other in a new dimension.
* **Complementary Reading**: information generally omitted by the ruling class are added to the news.
* **Rhythmical Reading**: article is read to a rhythm (musical), so it acts as a critical "filter" of the news, revealing the true content initially concealed in the newspaper.
* **Parallel Action**: actors mimic the actions as the news is being read. One hears the news and watches its visual complement.
* **Improvisation**: news is improvised on stage to exploit all its variants and possibilities.

Choose one of the techniques above and practice with your news items (choose news items that may fit best the chosen technique).

Groups will be reading out loud their news to each other.

### ::: Task ::: Intro to ML5

:hourglass_flowing_sand: 60 min

We will look into [ml5js — image classification](https://learn.ml5js.org/#/reference/image-classifier)!

[Download the code files](https://artslondon-my.sharepoint.com/:f:/g/personal/j_chicau_arts_ac_uk/Ep71g7QSmw5Jt6BYTQlYx6cBw0UVUzuptSiRDBELOK5srQ?e=cmP3eq);

* 0. Install [npmjs http-server](https://www.npmjs.com/package/http-server)) alternatively [install via this link](https://nodejs.org/zh-cn/):
> sudo npm -g install http-server
* 1. Open the terminal and 'cd' into the same folder location as the previous code files.
* 1.2. type in the terminal
> http-server
* 1.3. now you can visit the index.html file inside the folder by opening this URL http://localhost:8080 in your browser;
* 1.4. to quit the program press in the keys 'control' + 'C' in the terminal;

🌈 🖥 **tools** 🖥 🌈

_Image Dataset (MobileNet) + ML5_

* [Beginner's Guide to Machine Learning in JavaScript with ml5.js](https://www.youtube.com/watch?v=26uABexmOX4&list=PLRqwX-V7Uu6YPSwT06y_AEYTqIwbeam3y)
* [Intro ml5js image-classifier](https://learn.ml5js.org/#/reference/image-classifier)
* [ml5.js: Image Classification with MobileNet](https://youtu.be/yNkAuWz5lnY?t=231)
* [hello-ml5](https://learn.ml5js.org/#/tutorials/hello-ml5)
* [ml5js — ImageClassification](https://editor.p5js.org/ml5/sketches/ImageClassification)
* [MIMIC: mobilenet](https://mimicproject.com/code/45e317ca-2edb-f7a0-141c-a6e462f9243d)

### ::: Take Away Task :::

**Create your Stories**

WHERE * WHEN * WHO * WHY

⇨ **Aims**: What are possible questions you want yout dataset to provoque? What would like your players to be confronted or engage with?

⇨ **Scenario**: Departing from your dataset and the context in which it operates, create a scenario or situation that helps facilitated the 'aims' above.

Describe it in one or two paragraphs, considering: how will this scenario invite players to engage and participate?

⇨ **Players**: What roles are necessary in order to bring different perspectives around the data?

Describe each role including: what roles can members from your team take in order to help facilitate the experience? what roles can the audience take?

## session 05: Group Tutorials;

*Thurs 19th (14h-17h00)*

:hourglass_flowing_sand: groups schedule:

* 14.00–14.25 –
*
*Meanwhile other groups go through:*

### ::: Task ::: Storyboard

:hourglass_flowing_sand: 30 min

[Storyboard](https://toolkits.dss.cloud/design/method-card/storyboard-2/) is a narrative tool derived from cinema. It’s a form of prototyping which communicates each step of an activity, experience, interaction or event.

Transfer your ideas from the above task into a storyboard and consider:

⇨ What other elements might be relevant to use to compose the scene? You can use ‘props’ (aka theatrical property) or objects that carry a specific meaning and may help setting / engaging with the scene (eg.: clothing; specific technology, news articles, print out of datasets..).

Example of templates:

* [TEMPLATE_MAIN_SCENE](https://toolkits.dss.cloud/wp-content/uploads/sites/2/2016/06/STORYBOARD_TEMPLATE_MAIN_SCENE.pdf)
* [STORYBOARD_TEMPLATE](https://toolkits.dss.cloud/wp-content/uploads/sites/2/2016/06/STORYBOARD_TEMPLATE.pdf)

### ::: Task ::: Planning

:hourglass_flowing_sand: 30 min

In your groups plan your next steps and what you need to create your scenario and invite participants;

### ::: Notes on Documentation :::
_important:_ ask permission to participants about recording and agree to which extent you will be publishing the documentation; make sure the act of documenting does not interfere with the situation or leave participants unconfortable;

* photography: close-up and general set up;
* video: close-up and wide lens;
* audio recording;
* other material: skecthes; scripts; storyboards...

## session 06: Final SHOW

> "data visualization art is concerned with the anti-sublime. If Romantic artists thought of certain phenomena and effects as un-representable, as something whuch goes beyond the limits of human sense and reason, data visualization artists aim at precisely the opposite: to map such phenomena into a representation whose scale is comparable to the scales of human perception and cognition" *in Data Visualization as New Abstraction and Anti-sublime" by Lev Manovitch, 2002.*

Wed 25th of May (14h-17h00): sharing / crits;

:hourglass_flowing_sand: 15 min per group;

---

_References:_


> What will be the role of humans in a future AI driven world? As algorithms begin to optimize nearly every interaction and aspect of our lives, the last remaining role for people may be performing the emotional labor to act as human interface to AI. The 24h HOST performance is a small party that lasts for 24 hours, driven by software that automates the event, embodied in human HOST.

* [by Lauren McCarthy](https://lauren-mccarthy.com/24h-HOST)

---


> "Through these participatory processes of roleplay, rehearsal and speculation, the pre-enactment is a tool for understanding prediction and reclaiming contested futures.""

* [by Lily McCraith](https://lilymccraith.net/Pre-Enacting-Predictions)

---


> Hello Hi There uses the famous television debate between the philosopher Michel Foucault and linguist/activist Noam Chomsky from the Seventies as inspiration and material for a dialogue between two custom-designed chatbots: every evening, these computer programs, designed to mimic human conversations, perform a new – as it were, improvised – live text.

* [Hello, Hi There by Annie Dorsen](https://anniedorsen.com/projects/hello-hi-there/)
* [Hello, Hi There. (video)](https://vimeo.com/194697514?embedded=true&source=video_title&owner=9302488)

---


* ['Project 'Anatomies of Intelligence' by Joana Chicau and Jonathan Reus](https://anatomiesofintelligence.github.io/)

---


* [Body of Matter: Orion Maxted - HUMAN SIMULATION](https://vimeo.com/154972235)

Orion Maxted's systemic, algorithmic theatre reveals how a group of people thinking together can form a computer, and in so doing arrive at new forms of thought and presentation.
In stark contrast to the vast complexity of the world we live in, as individual humans, we can consciously handle only a few elements at once. How are we then to think and write about this then, when we are inextricably woven into these systems? And yet, simple patterns appear to repeat at every level of reality.

---


* [Dora Garcia: Instant Narrative](http://doragarcia.org/segundavez/live/)

Instant Narrative is a performance involving an observer in an exhibition space typing on a laptop computer, writing everything she sees and hears, mostly the appearance and behaviour of the visitors to that exhibition. This text is projected on a screen somewhere in the exhibition room, with no obvious connection to the writer. When the public is confronted with the projected text, they realise that someone has been/is looking at them, and they see themselves through the eyes of that other person, which is sometimes comic and often unpleasant for the reader. From that moment on, the visitor knows that her behaviour will influence the text, and a complex feedback is generated.

---


* [Guy de Cointet](https://guydecointet.org/)

Guy de Cointet was fascinated with language, which he explored primarily through performance and drawing. His practice involved collecting random phrases, words, and even single letters from popular culture and literary sources —and working these elements into non-linear narratives, which were presented as plays to his audience.​

* [Example performance "Going to the Market"](https://vimeo.com/175809560)

---


"...each and every work articulates a particular stance, attitude, and point of view: it addresses the world as a whole from the limits of that world, that is, from the point where a world begins and ends, where α and Ω coincide. In each work Filko projects a view of the world as a whole by formulating conditions—and formalizing terms—under which the world could be viewed as a whole."

(...)

"HAPPSOC 1, for example, was announced by a simple invitation card to the city-wide artwork, listing among other things the materials used in the work: “138036 women, 128727 men, 49991 dogs, 18009 houses, 165236 balconies, 40070 water pipes in homes, 35060 washing machines, 1 castle, 1 Danube in Bratislava, 22 theatres, 6 cemeteries, 1000801 tulips (...) etc.” The grand gesture of seizing a whole city with the sublime force of one thought is thus offset by the modest form of its announcement (a small card) and the laconic enumeration of the mundane parts of the whole."

* [source: World as Medium: On the Work of Stano Filko](https://www.e-flux.com/journal/28/68020/world-as-medium-on-the-work-of-stano-filko/)

---


“The Transborder Immigrant Tool ... is a last mile safety device designed to aid the disoriented of any nationality in a desert environment.” – Electronic Disturbance Theater 2.0/b.a.n.g. lab

* [Source Net Art Anthology](https://anthology.rhizome.org/transborder-immigrant-tool)
---


* [100% City](https://www.rimini-protokoll.de/website/en/projects/100-stadt-7-1)

100 citizens that represent their city in 5 criteria, a sample, a cross-section of the society, always assembled into ever changing new group pictures on a big revolving stage. Sorted according to age or address, gender, political leanings, preferred local pub, means of transport, sandwich spread, playwright and then, bit by bit, as a sea of voices, as a geometric body on 100 square metres of stage..

---


* [Transcultural Data Pact](https://decal.furtherfield.org/2019/11/22/transcultural-data-pact-larp/) explores how personal and collective data practices and devices shape the attitudes and fortunes of societies.
* [Trailler: The Transcultural Data Pact - A Live Art Action Research Role Play](https://vimeo.com/470585528)
* [Talk: How live action role play could fix real-world social problems:](https://theodi.org/event/odi-fridays-how-live-action-role-play-could-fix-real-world-social-problems/) Artistic Director Ruth Catlow talks about how participation in scenarios in live action role play (LARP) leads to powerful group-driven discovery, rich research data, and potential real-world answers.
* [Lecture: Deliberating Data-Driven Societies Through Live Action Role Play](https://www.youtube.com/watch?v=xTM0ukm8HS4)

---
✨ **References** ✨ 👀

* [Data Dramatization by Memo Atken](https://memoakten.medium.com/data-dramatization-fe04a57530e4)
* [Data Meditation by Salvatore Iaconesi & Oriana Persico](https://chatty-pub.hackersanddesigners.nl/Network_Imaginaries#ch-18datameditation)
* [Data Visceralization by Catherine D'Ignazio and Lauren Klein](https://data-feminism.mitpress.mit.edu/pub/5evfe9yd/release/5)
* [Visualizing Energy Data or Visceralizing Energy Transitions by J Wernimont](https://jwernimont.com/visualizing-energy-data-or-visceralizing-energy-transitions/)
* [Blast Theory](https://www.blasttheory.co.uk)
* [Improbotics - An Improvised Theatre Experiment](https://improbotics.org/)
* [Data Physicalization Projects](http://dataphys.org/wiki/Data_Physicalization)
* [Open Data Playground by Stefanie Posavec](https://www.stefanieposavec.com/open-data-playground)
* [Livebook Staging tool](https://github.com/inkandswitch/livebook#readme)

✨ **Further References on DataViz** ✨ 👀

* [Fundamental DataViz](https://clauswilke.com/dataviz/)
* [Introduction to Data Science](https://rafalab.github.io/dsbook/)
* [Visualising Data](https://www.visualisingdata.com/resources/)
* [Making with Data](http://makingwithdata.org/)
* [Data Stories](https://datastori.es/)
* [DataViz Books](https://informationisbeautiful.net/visualizations/dataviz-books/)
* [Open Access Vis](http://oavis.org/)
* [DataViz Libraries JavaScript](https://github.com/javierluraschi/awesome-dataviz)

✨ **ML project References** ✨ 👀

* [Normalizing — by Mushon Zer-Aviv](https://normalizi.ng/)
* [On scene net datasets — HOMESCHOOL by Simone C Niquille /Technoflesh](https://www.technofle.sh/hs/homeschool.php)
* [3D objects](https://www.technofle.sh/hs/homeschool.php)
* [Coco Dataset](http://plottingd.at/a/introduction.html#dataset-for-4-year-olds-coco)
* [Facing the Future, Kate Crawford ](https://soundcloud.com/the-observatory-1/episode-113-facing-the-future)
* [Face Swap](https://github.com/deepfakes/faceswap#faceswap-has-ethical-uses)
* [15 min fame](http://www.marnixdenijs.nl/15-minutes-of-biometric-fame.htm)
* [Surveillance Paparazzi](https://driesdepoorter.be/surveillance-paparazzi/)