The slides present the context of a workshop on using card games to interpret datasets as well as defamiliarize and reassess the role of tools in data practices and the computational humanities. An abstract with more information and literature can be found here: https://www.dropbox.com/s/rsb1zilzzisqfja/RMA%20Workshop_%20Making%20Data%20Playable%20-%20announcement.pdf?dl=0.

1. Slide No. 1“Playing with Datasets?”, December 10th, 2019
Making Datasets Playable…?
Dr. Karin van Es
Dr. Stefan Werning
(Utrecht University)

2. Slide No. 2“Playing with Datasets?”, December 10th, 2019
11.15 Intro ‘Playful Datasets’
11.30 Play sample card game & plenary discussion
12.15 Lunch
13.00 Explain card creation with Nandeck
13.20 Redesign sample game (incl. creating new cards)
14.30 Team pitches
15.00 Redesign card game made by other team
16.00 Team pitches and prototype comparison
16.30 Closing remarks/theoretical embedding
(incl. Galey/Ruecker)
Program today

3. Slide No. 3“Playing with Datasets?”, December 10th, 2019
Premise
• As games become a ‚reference medium‘,
more people interpret their lives
through the ‚lens‘ of games and game
co-creation
• NRC article on changing Hasbro‘s Game
of Life to reflect real-world lived
experience
– “Spelkaart 1: Je besluit dat tijd meer waard
is dan geld. Verkoop je bezittingen en trek je
terug in het groen”
– “Spelkaart 2: Je wil géén standaardgezin.
Geef je buggy weg en start een ander soort
familie”
– “Spelkaart 3: Je hebt geen huis nodig. Leen
een tent of camper en zwerf een tijdje rond”

4. Slide No. 4“Playing with Datasets?”, December 10th, 2019
Playfulness in
Engaging with Data • Playfulness (Lieberman)
– Cognitive Spontaneity
– Physical Spontaneity
– Social Spontaneity
– Humor
– Manifest Joy
• Dear Data
• “Playing With Real(ish) Data:
Visualizing the Books I Read Last
Year”
• Play can but need not be critical!
Lieberman, J. Nina. 2014. Playfulness: Its Relationship to Imagination and Creativity.
Brooklyn, NY: Academic Press.

5. Slide No. 5“Playing with Datasets?”, December 10th, 2019
• How can games and play make data
‘experienceable’ while simultaneously
contributing to a more nuanced
understanding of tools in data analysis?
• Primacy of visual evidence vs. multimodality
– Making Data Matter ⇔ Music by Oceans
• Defamiliarization
– Making both familiar data and techniques ‘strange’
• Foregrounding play, performativity and participation
– Often excluded from “scientific method” and rhetoric
– Cf. e.g. (Roberts-Smith 2017)
Question
Roberts-Smith, J. (2017) ‘Théâtre et humanités numériques. Du développement des outils aux
design experimental’, Revue d’Historiographie du Théâtre, 4(Special Issue: Études théâtrales et
humanités numériques).

6. Slide No. 6“Playing with Datasets?”, December 10th, 2019
Game Co-Creation
⇔
Critical Making

7. Slide No. 7“Playing with Datasets?”, December 10th, 2019
Epistemologies of
‘Making’ • Stephen Ramsay, “On Building”
– “All the technai of digital humanities – data
mining, xml encoding, text analysis, gIs, Web
design, visualization, programming, tool
design, database design, etc. – involve
building”
• Galey/Ruecker
– Prototypes can constitute scholarly
arguments
– Exhibit a rhetoric of their own
• Ratto, “Critical Making”
• Dunne & Raby, “Critical Design”, Feminist Data
Set
• Tharp & Tharp, “Discursive Design”
– Focus on “alternative things”
– Commonalities and differences

8. Slide No. 8“Playing with Datasets?”, December 10th, 2019
Analytical Game
Design • Some existing perspectives on critical
(board/card) game-making
– Critical board game design (Zavala/Odendaal
2018)
– Indigenous board game design
(LaPensée 2016)
– Critical Modification (Loring-Albright 2015)
– “Executable thought experiments” (Schulzke
2014)
– All focus on one games as ‘product’
• Analytical Game Design
• a) Game co-creation as an ongoing discourse
• b) Game prototypes as epistemic objects
(cf. Humanities Today, objects)
• c) Unfinishedness affords ‘productive
Irritations’
• d) Playgiarism (Raymond Federman)
LaPensée, E. (2016) ‘Indigenous Board Game Design in The Gift of
Food’, Analogue Game Studies, 3(2). Available at:
http://analoggamestudies.org/2016/03/indigenous-board-game-
design-in-the-gift-of-food/.
Loring-Albright, G. (2015) ‘The First Nations of Catan: Practices in
Critical Modification’, Analogue Game Studies, 2(7). Available at:
http://analoggamestudies.org/2015/11/the-first-nations-of-catan-
practices-in-critical-modification/.
Schulzke, M. (2014) ‘Simulating philosophy: Interpreting video
games as executable thought experiments’, Philosophy and
Technology. Springer Netherlands, 27(2), pp. 251–265.
Zavala, K. and Odendaal, A. (2018) ‘Black Boxes out of Cardboard:
Algorithmic Literacy through Critical Board Game Design’,
Analogue Game Studies, 5(4). Available at:
http://analoggamestudies.org/2018/12/black-boxes-out-of-
cardboard-algorithmic-literacy-through-critical-board-game-
design/.

9. Slide No. 9“Playing with Datasets?”, December 10th, 2019
Defamiliarization in
Critical Practice and
Games
• “Scholars in various fields have argued that
one of the great merits of digital tools is
their capacity for ostranenie: for ‘making
strange’, or defamiliarizing us from, our
objects of study – and by the same token,
for calling into question our most profound
assumptions about them”
(Masson 2017, 31)
• Defamiliarization in/through games
– E.g. games devised to reinvigorate
artistic practice and unsettle routines
(Dadaism, Surrealism, OuLiPo)
Knight’s tour diagram used in creating
Georges Perec’s Life: A User's Manual
Masson, E. (2017) ‘Humanistic Data Research. An Encounter between
Epistemic Traditions’, in Schäfer, M. and Van Es, K. (eds) The Datafied Society.
Studying Culture through Data. Amsterdam: Amsterdam University Press, pp.
25–38.

10. Slide No. 10“Playing with Datasets?”, December 10th, 2019
Card Games as
‘Tools’ for Thought

11. Slide No. 11“Playing with Datasets?”, December 10th, 2019
Card Games as
Data Storage Devices • The playing card as “platform” (Altice
2014)
• Material affordances
– “Planar, uniform, ordinal, spatial, and
textural”
– Tapping, turning, stacking, shuffling
(cf. e.g. Magic: The Gathering)
• Specific ‘data type’ qua layout
– Selection and position of values, ‘flavor text’
• “Programmable” (Bogost/Montfort 2009)
– “A ‘platform’ is a system that can be programmed and
therefore customized by outside developers -- users -- and
in that way, adapted to countless needs and niches”
Altice, Nathan. 2014. “The Playing Card Platform.” Analogue Game Studies 4
(2). http://analoggamestudies.org/2014/11/the-playing-card-platform/.
Bogost, I., & Montfort, N. 2009. “Platform Studies: Frequently Questioned
Answers.” UC Irvine: Digital Arts and Culture 2009. Retrieved from
https://escholarship.org/uc/item/01r0k9br

12. Slide No. 12“Playing with Datasets?”, December 10th, 2019
Playing with Data:
The ‘Language’
of Card Games
• Top-down vs. Bottom-up
– Modify mechanics and basic parameters
(players, goals, rules, external tokens/board etc.)
• Sequence/set-making (incl. hand management)
– Open (e.g. Domino and derivatives)
– Hidden (e.g. Vroeger of Later)
• Collectible cards (asymmetrical)
• Deck building
• Worker/engine placement
• Asymmetrical goals
• Trick taking
• Distributed information (e.g. Hanabi)
• Trading/auction (e.g. You’re Bluffing!/Koehandel)
• Memorization
• Self-modifying rules (e.g. Fluxx)
• Narrative/scripts

13. Slide No. 13“Playing with Datasets?”, December 10th, 2019
Playing with Data:
Mechanics • New gameplay mechanics (like
layout algorithms) enable new ways
of looking at data
• Randomly extended sequences
– All players choose a result that fits their
role
– Random results are added to the
sequence, which is shuffled
– Players need to guess who selected
which result
(=> identify bias of examination work,
e.g. reliance on SD etc.)

14. Slide No. 14“Playing with Datasets?”, December 10th, 2019
A Sample Game

15. Slide No. 15“Playing with Datasets?”, December 10th, 2019
Our Sample Dataset
• Scraped from the Google Play Store
– Imported from Google Sheet
– Can be extended (collaboratively)
• Adaptable to other datasets
– Kickstarter projects
– Trending videos on YouTube
• Yet: Playing the same game with different
datasets/metrics produces different
‘meanings’

16. Slide No. 16“Playing with Datasets?”, December 10th, 2019
Sample Game
• Players ‘launch’ apps to
compete with each other in
four categories
– Install size, installs, review score,
number of reviews (buzz)
• ‘Gaps’ in the rules as
productive irritations
– E.g. can you compete with your
own apps?
• ⇔ Leaves room for co-creation
– E.g. what role do rating and
category play?
• Maybe extend using set-
making or event cards
(limiting points earned for
apps rated T and above?)

17. Slide No. 17“Playing with Datasets?”, December 10th, 2019
Playtesting

18. Slide No. 18“Playing with Datasets?”, December 10th, 2019
Redesign
• Co-creating games requires a bit
of practice and getting used to
a. Start by modifying individual
parameters
b. Use Caillois’ taxonomy as a
heuristic
c. Try out different rule
variations and determine
whether they fit one
prototype or should be split
into multiple
• Template
– Setup phase
• Setup action 1
• Setup action 2
– Play phase(s) (per player)
• (Potential) Action 1
• (Potential) Action 2
• Check win/lose conditions
• Game response before player switching
– Wrap-up phase
• Determine win/lose state
• Consequences for next play session?

19. Slide No. 19“Playing with Datasets?”, December 10th, 2019
Connections to the three concepts established earlier in class?
• How could Caillois’ taxonomy of games be of use here?
• How can Sutton-Smith’s emphasis on the ambiguity of play be made
productive in working with data (even if it contradicts the traditional
‘scientific method’)
• How can data games facilitate performative engagement with data?
• What are the “terms of participation” (Jenkins) in this case and what role
do tools and “DIY cultures” play?
• (How) Can this approach contribute to the notion of cultural citizenship?
“Play, Perform,
Participate” Questions

20. Slide No. 20“Playing with Datasets?”, December 10th, 2019
• What classifications and standards are employed? What is made visible (and
invisible) in this system? To what end and at what consequences?
• What are the material affordances of the tools (i.e. the cards) employed? How do
they impact the game(play)?
• What interpretive acts have been made in the construction of the interface (i.e.
the cards)? How is this partial?
• What are underlying values and norms? (the basic logics or principles of the game)
Tool Criticism questions
in Playable Datasets

21. Slide No. 21“Playing with Datasets?”, December 10th, 2019
• Duration presentation: 20-30 minutes
• Make use of visuals that support the rationale
• Address the following elements in your presentation:
– Main results of your project
– Reflection on cycle and position of your question
– Role of digital tools and the concept of tool criticism
– Connect to wider debates and theories in Data-driven research as addressed
in literature and seminars
– Position in relation to Tools Criticism symposium in Leiden
Presentation:
Playful Datasets workshop from a
tool criticism perspective

22. Slide No. 22“Playing with Datasets?”, December 10th, 2019