Thinking in Practice: Workshop Report
A few thoughts on the interdisciplinary workshop Thinking in Practice, hosted by the Modelling DH project at Schloss Wahn in Cologne, 19-20 January 2017.
 At the end of this gathering that saw a great range of collective wisdom assembled, one might have been tempted to think of Brecht’s closing words to The Good Person of Szechwan (1943):
Wir stehen selbst enttäuscht und sehn betroffen
Den Vorhang zu und alle Fragen offen.
 These two lines crossed my mind at the very least, as I am loath to admit, for they may betray more about my own lack of comprehension than the actual lack of results. Indeed, it would be a gross misrepresentation of the event to take the above quotation (“the curtain closed and all questions open”) literally and pretend that no insight into the matter at hand was gained at all during the proceedings. Questions may not have been answered but questions were asked and added, refining the discourse in a valuable way that doesn’t close the book on Modelling in DH but rather suggests its potential table of contents.
 In the following, I will briefly review some talking points, brushing past most sessions without great detail, focusing rather on the overarching themes:
1. What is a model?
 This question may seem rather obvious but the answer is not, as became clear once more. The participants of the workshop – all renowned experts in their respective fields of study – certainly indicated to know what a model was in the framework of their own research but the attempt to bridge the varied understandings and synthesize a common definition proved elusive. Perhaps that was not the point of the exercise anyway. It stands to reason that it must gain traction in any summarizing effort, however.
 One might argue that the question itself is misleading – that there is not one understanding of “model” but only a multitude of understandings. Well, yes. But does that mean that there cannot be a meta understanding that extracts global features of the concept from its various implementations and classifies them under a supradisciplinary banner?
 While this question was not put to the participants quite so directly (not that I remember, there was a lot to process and note), the intellectually engaging discussions offered several arguments that point to the existence of common inquiries into the concept, at least when it comes to the humanities (though examples of models from the humanities were, as Rens Bod rightfully pointed out, barely used in any of the presentations – lack of confidence or awareness or both?).
 If I were asked which kinds of domain-specific models featured in the discussions, I would not get much farther than: mathematical models (and the distinction between a mathematical model, a numerical model, and a computational model, courtesy of Giorgio Fotia). That is strange because in truth, they did not feature all that much beyond mention and certainly not across the board. Oliver Nakoinz gave a very illuminating overview over different kinds of models used in archaeology (and the scepticism within the discipline towards that practice) but I would struggle to brand them with a similarly self-explanatory description – “archaeological models” would not carry the same meaning as “mathematical models” since archaeological models are not archaeological in nature whereas mathematical models are mathematical in nature and, moreover, clearly defined as “abstractions of reality characterized by mathematical formulas.” Indeed, archaeology does use, for example, computational models in its research so the question should be: Which discipline uses which kinds of models and is there something specific to certain models used in the humanities that has not yet been defined and is the same true for the digital humanities and if so, where are those definitions?
 The composition of the workshop suggests that the organizers see the overarching potential for defining models specific to the (digital) humanities in the field of semiotics. When they speak about modelling, they do not speak about data modelling (as has been the custom in DH) but about a “process of signification.”
 Which brings me to my next point:
2. Space Is Everything
 Iconicity, geography and the spatial dimension of thinking emerged as the most presented and debated topics. While fascinating and providing ample food for thought, in retrospect it is not clear to me how these concepts help us in understanding the role of models in the (digital) humanities. The discussions seemed to oscillate between the visual representation of models (as in the form of graphs) – and why this is necessary for our comprehension of the world – and our visual comprehension of the world and why that is necessary to formulate models. I hope future publications on the matter will investigate that fine line of distinction and whether it’s useful to draw; this is just based on my intuition, as is everything I write here. It might also be that the state of discussion in DH has evolved beyond such basic considerations in which case I would be glad to find it preserved in written form.
 The exercises between the workshop sessions made use of cartography as well. Weaving in and out of the scheduled programme, participants were first asked to position themselves on an imaginary ship, then what direction their compass would be pointing, later whether to explore an island or sail to new destinations. This all proved quite amusing and was a lively application of Willard McCarty’s archipelago metaphor.(1)
 Most importantly, it showcased the breadth of emotions of everyone involved: All starting out in different places but trying to find ways to unite and get the engine running together. Gunnar Olsson described it beautifully when he said that “on the high seas there are no maps because there are no fix points” – that is the quintessential issue in this endeavour but also its potential for substantially shaping modelling as a methodology in DH.
 When it came to the closing session, what had stuck in most participants’ minds were word pairs such as patterns / principles (introduced by Rens Bod in a highly interesting historical review of humanist studies), identity / differences, truth / trust, promise / premise (that Gunnar Olsson judged to be in crisis). Interestingly enough, when asked what should be scrapped from the discourse, the answer was: binary oppositions. Maybe there is a correlation here.
 Patrick Sahle, tasked with summing up the event, self-admittedly struggled to do so, not least of all because it had been a lot to take in. He cited that modelling is seen as a core activity and that modelling and formalization are perceived to go hand in hand, although there’s another discussion to be had about the term “formalization” and what it means in the DH context. He expressed his hope for the development of a meta-model and that one day, he could explain to his son in simple words what it is that he does at work; that he would be able to tell his son what a model is (riffing on Stanley Fish: “how to recognize a model when you see one”) and that he could send him into the world, looking for models, and that a week later his son would return with apt examples.
 There is something to be said for simplicity. Getting entangled in semiotic vocabulary, as this workshop was wont to do, might not serve to illumine anyone but rather obfuscate what it is that we are talking about and what it is we seek to do with it. On the other hand, Patrick Sahle’s tale of his son contained an implicit notion that models are something tangible, something that can be seen or collected or shown off or, at the very least, be readily apparent to a child. What would he say to his son if he asked what a theory was? Would that definition hold across disciplines? Would his son be able to bring home a theory, a theory that is truly a theory and not a hypothesis? Because that is the fundamental level that we are operating on, in my opinion. It does not speak to the desirability of the task, it speaks to its difficulty.
 Models are a way of explanation but, as Øyvind Eide noted, they can also be a way of investigation, of probing an object of study for no other purpose than to understand it. This – together with the many different viewpoints offered at the workshop, from computer science over philosophy to history – hints at the complexity of classifying them. They have different functions. They have different forms of (re)presentation. They involve different work.
 So I must stress that, to not be lost on the high sea of possibility, the questions need to clear: What kinds of models are used in the humanities? What do they share? Can they be used in computing? How would they fit into the concept of computational models? Only on the level of conceptual models? What could a more refined definition offer in that case? Can they be used in computing without being computable? As a stepping stone on the path of making something computable?
 What are we even talking about? Representing knowledge? Information? Data? Or are we talking about our perception of those things and how we rationalize our own perception?
 In summary, I see desiderata in the following areas: definition, explication, differentiation, classification, implementation.
4. Last Thoughts
 As with any interdisciplinary undertaking, the chasm in communication widens, the farther disciplines are removed from each other in language and thought. This presents an especially grievous problem when it comes to the digital humanities, seeing as they unite methods and tools from computer science with the horizon of knowledge (“Erkenntnishorizont”) from the humanities; to put it bluntly. Consequently, the participants covered a lot of ground without quite meeting in the middle, instead circling around the concept of modelling at the centre of attention and sketching out what they could see from their point of view. To get the full picture, someone would have to circumnavigate that globe with their eyes turned inward instead of forward.
 The workshop was a great example of what that would look like: thinking in practice. A bit messy, a bit associative, a bit of everything, but most of all brimming with the scholarly desire to set sail and return home with strange fruit and weathered skin.
 So with that in mind: Full speed ahead!
 (Apply sun screen liberally.)
List of speakers / pairings:
|Willard McCarty: Modelling, ontology and wild thought
digital humanities / philosophy
|Nina Bonderup Dohn: Models, modelling, metaphors and metaphorical thinking
|Barbara Tversky: Visual Communication
|Christina Ljungberg: The role of iconicity in cognition and communication
literary / semiotic studies
|Rens Bod: Notes on Modelling
philosophy of science / history of humanities
|Fotis Jannidis: Modelling in the Digital Humanities
|Oliver Nakoinz: Models and Modelling in Archaeology
|Øyvind Eide [Response]
|Gunnar Olsson: EVERYTHING IS TRANSLATION (including the art of making new boots out of the old ones)
|Claas Lattmann: Iconizing the Digital Humanities. Models and Modeling from a Semiotic Perspective
archaeology / semiotic studies
|Giorgio Fotia: Modelling practices and practices of modelling
mathematics / computer science
|Paul Fishwick: Information Modelling of the Humanities
digital humanities / computer science
|Günther Görz: Some Remarks on Modelling from a Computer Science Perspective
|Francesca Tomasi: Modelling is my favourite job
digital humanities / classics
Bonus: Some Quotes & Notes
“The true nature of the machine is unknown to us [because it’s not natural].”
- question is not whether cognition is computational but rather what cognition is
Nina Bonderup Dohn
- models explicate metaphorical holistic “seeing as”
- metaphorical understanding is primary (not its linguistic expression)
- tools of visual representation can convey meaning directly (empirical semiotics)
“There can be no models without iconicity.”
- iconicity as a mediation between language and thought/mind
“Models link empirical patterns to theoretical principles.”
- contextual assumptions, e.g. in narratology, generative linguistics, harmony theory, structuralism, stemmatology, iconology
- patterns can be found in singular events, models can thus be representations of singular events
- there is no use in substituting model for theory because theory is much better defined and understood
The term “model” comes along as a solution but really, it’s a problem.
- DH needs to develop its own set of vocabulary
- it’s fashionable to use “model” as a buzzword in papers but modelling is met with skepticism in practice
- surprisingly similar trajectory (in archaeology) to anthropology when it comes to the introduction of the term “model”
“Since we are human beings blessed with the gift of imagination, we can see this [something that was verbally described] when we close our eyes.”
- what makes us special is that we can live in the difference between identity and alterity
“Scientific truth is the ability to say that something is something else and being believed.”
“Models are ubiquitous in science.”
- in theory, everything would be a diagrammatical model
“Mathematical models are the abstractions of reality characterized by mathematical formulas […] and represent theories of natural events and engineering systems.”
- quantitative insight is the main objective of mathematical models
“Computing is an instrument metaphor.”
- there is not necessarily a model in data science used in learning from the data (at least not in the mathematical sense)
“The arts & humanities represent a rich area in which to teach modelling.”
- three model categories: knowledge, space, time
- it is essential for modelling to provide a linguistic framework
- modelling starts with the construction of a formal ontology
I think that modelling is mostly a question of language.
- models are a guideline, models are shared inside a community, models are the representation of a domain, models are the practice to translate theory… there doesn’t need to be a universal definition
Featured image: Astroloog, Jan Luyken, 1694, http://hdl.handle.net/10934/RM0001.COLLECT.143908.
All pictures from the event courtesy of Willard McCarty.