ORIGINAL ARTICLES

Programming the Postdigital: Curationof Appropriation Processes in (Collaborative) CreativeCoding Spaces

Judith Ackermann1& Benjamin Egger1 & Rebecca Scharlach2

# Springer Nature Switzerland AG 2019

AbstractCreative coding is a form of postdigital art that uses programming to solve estheticalproblems, subordinating functionality to expression. It often comes with rather uncom-mon usage patterns of coding, going beyond technologies’ affordances and findingways of appropriating them in an individual way and in exchange with others. Thelearning ecologies GitHub, Stack Overflow, and Pouët present digital infrastructuresthat curate and support such appropriation-related activities. The paper presents aqualitative analysis of the structure of these spaces, and the appropriation-relatedcommunication taking place. It shows how crucial the varying designs of the learningecologies and the implemented interaction possibilities are for the appropriation activ-ities taking place and draws a line to the desire for stronger participation in postdigitalcuration.

Keywords Postdigital . Creative coding . Learning ecologies . Digital appropriation .

Curation . Art

Introduction

program the beautifulMax Bense (1960)

The argument that we live in the postdigital age might give an impression that we are in atime after the digital. However, it would be wrong to say that we have left the digital

https://doi.org/10.1007/s42438-019-00088-1

* Judith Ackermannj.ackermann@fh-potsdam.de

1 University of Applied Sciences Potsdam, Kiepennheuerallee 5, 14469 Potsdam, Germany2 The Hebrew University of Jerusalem, Mt Scopus, 91905 Jerusalem, Israel

Published online: 10 December 2019

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behind. When postinternet artist Marisa Olson describes an artwork of hers as art afterthe Internet, she refers to two meanings: after an Internet experience and in the style ofthe Internet (PKKB 2018: 5: 122). Both aspects apply to the concept of the postdigital.We find ourselves in a time marked by the esthetics of the digital and every singlemoment is always one after a digital experience (see Jandrić et al. 2018). In other words,to live in postdigital times means that the ways we live, think, and interact are shaped bydigital configurations. Therefore, postdigital can also be described as a ‘critical attitude(or philosophy) that inquires into the digital world’ (Peters and Besley 2019: 30).

Code enables us to access the digital devices affecting us through their ‘invisible’(Cormier et al. 2019) interfaces. Historically and media-theoretically, the prefix postgrasps a process of digital transformation, in which digital technologies are no longer‘perceived as disruptive’ (Cramer 2015: 20), although they might be. In the field of thearts, the term postdigital is applied analytically and does not describe a concrete genre,but refers to the altered status of media and arts after their digitalization, and thedigitalization of the channels they are communicated through (Cramer 2015: 19). Digitalmedia can no longer be categorized as new, but have their own history that can benegotiated artistically and researched (Grau 2007). Postdigital changes can also be foundin scientific approaches. Practices of computer science merge with other disciplines andarrive in the humanities, provoking a ‘computational turn’ (e.g. Boyd and Crawford2011). Gary Hall has coined the term posthumanities: ‘so that the questions, issues, andapproaches specific to each [discipline] are capable of generating new findings, insights,and realizations in the other—to the point where both of their identities are brought intoquestion’ (2011: 802). In this context, the so-called esthetic turn (Udsen and Jørgensen2005: 213) also needs attention. Both terms describe periods of transition. As theesthetic, as well as the computational are characteristic for the postdigital everyday life,both are vital for the research of postdigital art.

Postdigital artists are often driven by their own as well as society’s disenchantmentassociated with the digital. Hence, they propose new forms of critical examination ofdigital, networked media and their influence on the arts (Berry and Dieter 2015; Kholeif2017). Postdigital artworks are generated via digital methods or at least informed bydigital technology, even if they do not necessarily have to create a digital output(Ackermann et al. 2019: 183). One of the earliest examples of digital art practices inthe history of technology is the demoscene that can be described as the beginning ofcreative coding. In a computer demo, code becomes the central tool or material thatconnects virtual input/output and physical conditions. Demos are programs that generatesound and visualization in real time to be experienced on a certain computer—they arecomposed in a way to meet the requirements of specific (especially retro) technologicaldevices and thereby always combine virtual layers with physical aspects.

The origins of the scene go back to the home computer of the 1980s (see Fig. 1),when cracker groups created elaborate welcome intros (demos) for pirated computergames (Tasajärvi 2004). Since then, demo has emancipated itself from this backgroundand can be regarded as an independent art form that produces esthetically complexarrangements through minimal technical resources (Botz 2011). At demo parties it is atradition to hold competitions, where the competitors code according to certain techni-cal frameworks. This phenomenon matches an instruction to act in an art theoryunderstanding. One of the most important challenges in the demoscene nowadays isto limit oneself technically as much as possible—this anachronistic approach refers to

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the postdigital status of demos, namely, to fall back on past technical conditionscreating a kind of retro style. As Peter Weibel says, the model for the art of instructionis clearly the score, which is an instruction for a performer on how to play a particularpiece of music (Weibel 2002: 15). Ironically, the basis of a demo, the code, alsoresembles a score, with the difference that a computer can only interpret it in oneway—it doesn’t know any nuances, variances, or timbres. In the field of arts, the demohas always been a niche genre which has never been fully accepted as part of fine arts.Nevertheless, it is located at the core of creative coding, a form of programming whichsubordinates the function to the expression (PBS 2013; Dufva 2018: 42).

Creative coding opens up programming from just writing code towards anartistic activity that includes code. It has the potential to involve physical ele-ments, electronics, sensors, and interaction with the physical world (Dufva 2018:43). This hands-on digital production can make the practitioners aware of the deepconnection of body and digitality (Dufva 2018: 43). Therefore, the ‘variety ofhuman-machine assemblages’ (Sierra-Paredes 2017: 27) as well as the hybridity ofdigital and physical spheres referred to by the postdigital can be reflected produc-tively in creative coding—opening a broad field from rather screen oriented works(like the already mentioned demos) to works decidedly staging the connectionsand intersections between physical bodies and digital technologies/code (see Fig.2) and those focusing on the invisibility of digital technology and code and/orpromoting new ways of using it (together) (see Fig. 3).

Appropriation and Postdigital Art

Entering a super innovative art- and tech-scene like postdigital art comes with a verylow level of given and verified information, experience reports and learning resources,

Fig. 1 Screenshot of ‘Demoscene,’ example of the early demo style. See https://youtu.be/Nzltux5yGmE.Accessed 3October 2019

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Fig. 2 Installation view of‘Mother of Machine’, SarahPetkus, US, 2018 (PKKB 2018)

Fig. 3 Installation view of‘Conspiracy,’ Kristin McWharter,US, 2017) (PKKB 2018)

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increasing the need for appropriation activities and for gathering in networks to shareinsights. For example: being seen in the pop-up of numerous creative co-workingspaces and shared artists’ studios in the physical sphere, installing online classesdealing with the topic, as well as establishing specific forums and social networksbringing people with similar and complementary artistic interests together. Whenengaging in activities of creative coding, artists constantly need to overcome newcreative and technological obstacles. Coding languages usually come with easy-to-learn sets of basic rules, but the possibilities of their combination are endless and cannotbe held at one place—neither digital nor physical. Especially the artistic use of coderesults in an experimental approach to coding and keeps on inventing new combinationforms. Gulielmetti describes the process of creative coding as the following: ‘simplelocal rules can create unexpected complex patterns’ (Guglielmetti 2015) which can beused to generate unforseen structures.

In this field—as well as in general—understanding how something works mustbe seen as the basic step of appropriating a certain technology (De la Rosa 2012:16). One needs to know how a tool is intended to be used and by what affordancesit is surrounded before inventing innovative ways of alternative application, likeemploying it to purposes that it was not designed for (Dourish 2003: 467). Ascoined by Gibson in 1977, affordances bundle the properties of something’ssubstance and its surface and evoke in relation to the (human) being interactingwith it (Gibson 1977: 67). They provide ways of typically handling specificobjects or artifacts—translated to the digital sphere this includes the infrastructureof an Internet forum, for example, which promotes certain behaviors by the users,enabling them to immediately participate and gain a first moment of self-effectiveusage. Those ‘basic affordances [...] are usually perceivable directly, without anexcessive amount of learning’ (Gibson 1977: 82).

Norman, who introduced the concept to the sphere of design in 1988, differentiatesbetween perceivable and invisible affordances (Norman 2013: 18). From a designperspective, it makes sense to highlight the visibility of typical usage patterns ratherthan to highlight those research patterns which are important only to a very small groupof people with very specific interests—like the creative coding community in compar-ison to coders in general. In addition, the way affordances are perceived is rooted inculture, social norms, and traditions of handling a certain tool or object (Kress 2010).The community of creative coders uses coding frameworks and languages in a differentmanner than professional coders. They apply code to new fields and employ it forartistic expression, creating specific, rather uncommon usage patterns that rely onexpert knowledge and creative workarounds to be seen, for example, in the p5.jscommunity.1

It is the enactive use of technology or tools (Flint and Turner 2016: 41) that leads tothe emergence of a second form of appropriation denoting ‘processes that take placewhen new uses are invented for tools and when these uses develop into practices andstart spreading within a user community’ (Salovaara 2008: 209). With regard to the

1 P5.js is 'a JavaScript library for creative coding, with a focus on making coding accessible and inclusive forartists, designers, educators, beginners, and anyone else' (McCarthy 2019), which gained great popularity inthe creative coding scene.

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innovative ways of using coding skills to solve (and raise) esthetical questions to befound in creative coding, it becomes clear that relying on the basic affordances is notsufficient, but a lot of appropriation activities are needed. These consist of an interplaybetween usage, perception, evaluation, and processing that allows to make (new) senseof tools and media and is driven by decisive and mental acts in recognizing availablemedia and integrating them into everyday life (Ackermann 2013: 249) or artistic work.

Following Androutsopoulos, (media) appropriation activities especially becomevisible in speech acts dealing with organization, perception, expression, information,evaluation, and interpretation (Androutsopoulos 2008: 247 f.). As shown byAckermann (2011: 326), these are supplemented by media-altering speech acts andmedia-explaining speech acts. In this context, community plays an important role andappropriation turns into a process that is social and collective (Röser and Peil 2010:222; Ackermann 2011: 188). When specifically dealing with the appropriation ofdigital technology, communication tends to be located on digital community platformslike forums and social networks, providing socio-technical infrastructures of coopera-tion (Parks 2014) by connecting media amateurs (Daniels 2002) among each other andwith professional artists, allowing for mutual support—also documented in the publiccollection of threads and answers. They function as so-called learning ecologies(Martin 2016) for the artists—in the sense of Barron’s (2006) concept of interest andself-sustained learning. They document ‘informal and interest-driven learning’ offering‘a place of support, interaction, and resources for finding information to solve aproblem’ (Barron 2006: 51). They differ in the way the information is presented, theforeknowledge required to make use of it and the provided interactivity.

This leads us to the field of curation, which is a very important concept in the artsphere but also bears usefulness for appropriation activities and resources of knowl-edge: how disseminated information can be gathered and enriched with contexts to beperceived as knowledge is one of the most virulent questions in the postdigital age ofnetworked human and artificial entities. In this context, the concept of curating that hasalready undergone a transformation of meaning as a practice in the art field, has gainednew relevance and lost its sharpness. Here, curating can be conceptualized as selectingand prioritizing something within a set of possibilities, but it fails to consider thepractice’s symbolic character. Nevertheless, it is essential to emphasize the meaning-producing aspect of curatorial practices.

Extending to the field of digital technologies, curating is reinterpreted as an expres-sion for ephemeral appearances of algorithmically generated and sorted news feeds ortimelines in social media (Rader and Gray 2015; Eslami et al. 2015). Taking this intoaccount, one must describe the practice as a hybrid ‘anthropotechnical’ (Sloterdijk1999) process in which information and data become significant by oscillating betweenhuman and machine (inter)actions.

Originally, the term curating describes the practices of collecting, arranging, andpreserving artifacts. It constitutes curators as actors remaining invisible in the back-ground of an institution like a museum. This understanding of the practice is literallyreflected by its Latin meaning: curare for caring (von Bismarck 2014: 58). Since the1960s, in the course of the expansion and globalization of the art world, the practicedeveloped into an increasingly exhibition-creating activity that plays an essential role inproducing an artwork’s meaning. In this development, the activity emancipated fromthe need to be embedded in an institution to a broader field of application. In addition to

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practical techniques and skills, in particular organizing exhibitions, the reputation ofcurators today is mainly based on the symbolic power of their activity. Conceptuallyselecting and arranging artifacts that were unconnected before, puts them into commu-nication with each other (PKKB 2018: 3: 98). This describes a meaningful action andthe artifacts’ and the show’s positions in the discourse—be it an exhibition, a talk, orany other expositional medium (von Bismarck 2012: 47ff; Bismarck 2014: 58ff).

Levels of meaning of both preservation and creation apply to processes ofcontextualizing information meaningfully, i.e., to presenting it as knowledge. Theexhibition—to stay within this example—brings an independent, self-organizedknowledge into being (Creischer 2015: 121). The self-organizing element in thisprocess refers to the actors involved in producing the exhibition and the commu-nicative power of the artworks. Especially when spectators get to be involved intoexhibitional decisions, it is often said that they would participate in the curatorialas the sovereignty of interpreting an artwork or an arrangement, as well asproduced knowledge, is shared. In order to analyze spaces that produce knowledgethrough involving diverse entities, learning ecologies like Internet forums areexamined in this article. Questioning their educational benefit, one has to focuson how information is contributed and contextualized meaningfully in a way itconnects with someone’s needs. Thus, we conceptualize forums as self-organizedmedia evoking blank spaces by offering room for inputs and by giving outputsthrough the community and through themselves. The way the involved elementsare put into connection can be described as curatorial processes.

Learning Ecologies Surrounding Postdigital Art

To understand more about the specifics of postdigital artworks and the connectedchallenges of exhibiting and communicating such art, and to analyze how postdigitalartists find their way to the art sphere and gain the required skills in terms of coding,programming, designing, and esthetics, we conducted a series of 14 qualitative in-depthinterviews with international postdigital artists and curators over a period of 6 months.The study aims at understanding the curatorial challenges of integrating postdigitalartworks in physical and/or digital exhibition environments and learning about thebiographical paths artists take in order to become active in the field with an accent onappropriation strategies they pursue. The results are meant to inform new formats ofcultural education, enabling people without artistic and/or professional background tobecome creative in the vibrant field of postdigital arts. It could be shown that artistshaving a focus on digital technologies usually train themselves autodidactically. Inaddition to tutorials, workshops, and communication with experts in the respectivefields, forums represent one diverse option for appropriating technologies and tools.However, with regard to learning ecologies, the study also shows that thematicallycomprehensive forums for digital artists are rather rare. Instead, the appropriation-related communicative exchange of digital artists aiming at finding solutions to tech-nical problems as well as presenting and discussing their own artistic projects isorganized decentrally.

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We decided to take a closer look at the digital learning ecologies connected topostdigital art and creative coding, to understand how and where appropriation activ-ities take place and in which ways information is curated by the actors involved.According to the interview results, the most relevant platform in that field is GitHub.It covers a multitude of topics and technologies relying on an infrastructure, which isexplicitly thematically organized but at the same time complexly differentiated.Dabbish et al. describe it as an ‘iconic example of a knowledge-based workspace’and emphasize its open source structure (Dabbish et al. 2012: 2). Although it is theworld’s largest platform for developers and collaborative work, GitHub has receivedlittle attention from the humanities to date. GitHub describes itself as ‘a communitywhere more than 36 million (July 2019) people learn, share, and work together to buildsoftware’ (GitHub 2019g). Since a few years, it is seen to be the largest source codehost worldwide (Kalliamvakou et al. 2014: 384) and ‘the biggest collection of opensource software’ (Finley 2015).

GitHub identifies as a platform for developers and coders and as an introduction toof front-page states. There is no information given concerning GitHub's application tothe arts, still as the word creative coding implies, the practice cannot be imaginedwithout a connection to coding skills and (at least partially) relies on code. One of theinterviewees working with GitHub for appropriation needs points out that it is the spaceto understand that ‘a lot of other people have already done the [...] work to make itpossible for me to use the stuff that I use’ (PKKB 2018: 3: 300).

Another general learning ecology focusing on coding is Stack Overflow, whichdescribes itself as ‘a question and answer site for professional and enthusiast program-mers’ and follows the plan to ‘build a library of detailed answers to every questionabout programming’ together with the community. To include a learning ecology,related to a specific art practice, we integrated Pouët into the research. The forum isconnected to the already mentioned demoscene and has a history of almost 20 years.

In the following sections, we present a qualitative two-part analysis of the structureof GitHub, Stack Overflow, and Pouët as well as the appropriation-related communi-cation taking place. To identify creative coding-related utterances in the two generalcoding-related spaces (GitHub and Stack Overflow), we narrowed down our research tocommunication and information dealing with the programming language ‘processing’that was especially designed for creative coding. In Pouët, being already connected to aspecific creative coding art practice, we generally focused on code-related activitiesindependent from the used programming language. The Internet forums discussed arefunctionally broad and do not primarily have an educational interest. To identify themas learning ecologies, we analyzed their educational benefit through curatorial process-es taking place. In this case, the respective forums can be regarded as self-organizedmedia in which human actors, such as producers and consumers, as well as artificialentities, such as technical infrastructure, design, and its affordances, are involved indispersed curatorial actions. Thereby, our analysis focuses on the following threequestions: How do the varying designs of the learning ecologies differ in each creativecoding community space? How are the interaction possibilities implemented and howare they used by the participating community?

To answer these questions, we first analyze how the given learning ecologies areconstructed and structured. After that, we focus on the concrete ways on how

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appropriation processes and resources are curated in the presented learning ecologiesand how users are made relevant for these processes.

Overall Structure of the Learning Ecologies

Analyzing the overall structure of the three spaces shows that all of them are publiclyaccessible but offer registration possibilities that are connected to different advantages.For the case of GitHub, the user can decide between the categories ‘free’ (0$/month)and ‘pro’ (7$/month) that both allow them to create an unlimited number of public andprivate repositories, but restrict the number of private collaborations to a maximum ofthree persons for the first case. Also, the professional account comes with ‘advancedtools and insights.’ After registering, GitHub asks the user to rate their programmingskills and define up to three areas of interest that drive their registration. The selectionopportunities convey the impression that the platform especially welcomes program-ming starters: three out of four scale options to evaluate one’s programming skills arerather located at a beginner level and even the highest rating named ‘very experienced’leaves room for improvement, fitting the website’s claim to ‘find endless opportunitiesto learn, code, and create.’ In addition, at least two of the reasons for using GitHub to bechosen are directly connected to learning (‘learning to code,’ ‘learning Git andGitHub’).

Once registered, the platform invites the user to ‘[d]iscover interesting projects andpeople to populate your personal news feed’ and encourages them to create a userprofile, upload a picture, and create a status for other users to see and recognize. Thisresembles creating a user profile in social networking sites like Facebook or Instagram;therefore, it can be assumed that the procedure is quite familiar to most Internet users.Like in the case of typical social networking sites, GitHub encourages users to chooseother people to follow, to get information about their activities as part of their individualdashboard. GitHub also suggests repositories to users based on their activities. How-ever, the words to categorize the possible user interactions at GitHub such as ‘create arepository, start a branch, write comments, and open a pull request’ are—apart fromcommenting—not very similar to social networking vocabulary. In addition, they don’tconnect to learning intuitively, but rather to maintaining projects on the platform. Whenchoosing to start by clicking on the link beneath the information ‘Learn Git and GitHubwithout any code!,’ the user is forwarded to an introduction named ‘Hello World’(GitHub 2019c), referring to the classical first little programs programmers do. As partof this introduction, the description of the platform’s aim shifts from being aboutlearning to being ‘a code hosting platform for version control and collaboration. It letsyou and others work together on projects from anywhere’ (GitHub 2019c). It showsthat the collaborative appropriation of technology and coding is organized aroundspecific projects.

In order to improve one’s knowledge, it is necessary to share one’s own code and askothers to contribute in enhancing it. It is not possible to only ask a question about acertain topic. Thereby GitHub makes sure that the platform is constantly growing,making it a collection of almost any kind of code—(partly) openly searchable. Lookingfor the code repositories via web search can be seen as one of the ways of using GitHubin a more direct manner, liberating the user from the need of pasting original code—a

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procedure that could build a high threshold making it hard for beginners to participate.Taking this into account, GitHub works in two different directions, facilitating an expertexchange as part of the public (and private) repositories on the one hand, and lettingusers curate learning resources for programming to support each other, on the otherhand. In GitHub, users are encouraged to participate and contribute and thus help shapethe content of the platform (see GitHub 2019e).

This especially takes place in the user-generated ‘GitHub awesome lists’, whichstarted around 2014 and are also organized in repositories. The topics are multi-facetted, ranging from recommendations for academic papers to every programminglanguage on the market, big data, and how to speak confidently at conference presen-tations. To make use of the awesome lists, one needs a lot of research activity and/orskill in relation to how specific the question or appropriation need is. This comestogether with the necessity of knowing how to categorize certain information (if notwanting to rely on the luck of having found the right search terms) in order to followthe right path.

In comparison to GitHub, Stack Overflow follows a totally different approach.Being a question-answer-forum, it serves as a place to get information fast and solveproblems quickly. The design supports this usage practice by showing the main andnewest questions on the front page. It addresses developers dealing with creativecoding, among coding in general and presents itself as a very efficient way of solvingappropriation needs, when stating on the main page that it is ‘all about getting answers.It’s not a discussion forum. There is no chit-chat.’ Apart from that, the communicationstyle of the webpage aims to highlight its curatorial function, which becomes visible inclaims like ‘Information is everywhere. Answers are on Stack Overflow.’ (StackOverflow 2019a). It tries to promote a community character like in the homepage titledefining the forum as a place ‘[w]here Developers Learn, Share, & Build Careers’(Stack Overflow 2019c) and the given information of being an ‘open community foranyone that codes’ (Stack Overflow 2019c). Still, it becomes clear at several points thatthe forum is a pretty institutionalized platform, strictly differentiating between a ratherunderdefined we that is ‘helping’ the opposed you in finding answers and ‘build[s]products that empower developers’ (Stack Overflow 2019b) by establishing a clearhierarchy. The assigned competences of the we are described in a lot of superlatives(‘We help you get answers to your toughest coding questions [...] and find your nextdream job,’ Stack Overflow 2019b).

Just like GitHub, Stack Overflow includes a business model offering the categoriesbasic (5$/user/month), business (11$/user/month), and enterprise (17$/user/month)reaching from allowing users to have private questions as a team to including varioussupport activities depending on the chosen category to hosting one’s own cloud serverfor business users. Apart from the paid privileges the platform offers an increase ofinteraction possibilities according to the user’s activity—or more precise their reputa-tion (see Fig. 4). Stack Overflow allows users to upvote questions and answers2 inorder to embrace their quality. For example, if a user’s answer gets upvoted, they gain10 points of reputation while a downvote costs them 2 points (Stack Overflow 2019c).In order to be able to create a new tag for the platform, a user needs at least 1.500

2 This option is only available for users with a reputation of a least 15 points for an upvote or 125 points for adownvote, see: https://stackoverflow.com/help/privileges?tab=all.

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points. The person’s reputation is shown in their profile as well as in the questionoverview next to their profile picture and name. Other than in the case of GitHub, StackOverflow does not allow you to follow other users in order to get in contact, but onlyoffers the possibility of observing tags in the sense of topics. This again reflects theplatform’s intention of not being a forum to bond with each other, but to efficiently findanswers to one’s coding problems.

Fig. 4 Screenshot of Stack Overflow privileges, accessed 27 July 2019

Fig. 5 Screenshot of Pouët. See http://www.pouet.net/comments.php. Accessed 31 May 2019 at 04:31 pm

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Unlike GitHub and Stack Overflow, Pouët is not a place to look for an overallinterest in (creative) coding, but one of the most popular spaces for demosceners tomeet and connect virtually. The fact that there are more than 23,000 users registeredconfirms this. The hosts of the website claim, Pouët is ‘your online demosceneresource’ and it has been online since 2000. The website has a very old-fashionedstyle which becomes apparent in esthetics as well as the structure of the (front) page.You wouldn’t easily know where and what to start with if you were not a scene memberyourself. The clear and classic but static structure might deter younger users who aremore familiar with rhizomatic associatively structured websites or online platforms likein social media (Shifman 2016: 5645). The page gives an easy overview on what itoffers but it is quite complicated to familiarize oneself with the scene’s own terms thatare necessary for the communication and usage of the platform: ‘prod’ for example isshort for Production and means Demo, ‘glöps’ are bonus points users receive for beingactive and ‘BBS’ is short for bulletin board system describing the forum area. The BBSserves as the main platform for communication on Pouët, in which users communicateon the basis of ratings of new demo productions for example (Fig. 5).

Pouët offers a public record of the user activity, comparable to an archive. It providesdetailed insights in the active user behavior—e.g., who liked or commented on whichprod. Users can like (thumbs up emoji), dislike (thumbs down emoji), and in generalreact to prods with different emojis.

There is no explicit welcoming page which would help (new) users to findtheir way around the forum except the FAQs (see Fig. 6) that give a firstimpression of the topic. The aim of Pouët is not to introduce the curious to theworld of the demo, so explanations of the background and history of the sceneand art form are kept short and ironic: ‘What’s a demo? That’s a question akinto “where do babies come from” […]’ (Pouët 2019a). When it comes toappropriation issues and challenges, problems are often closely related to thewebsite as the platform is deeply rooted in the scene. For example, there is a

Fig. 6 Screenshot of Pouët FAQ, 30 July 2019

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thread called ‘fix me beautiful,’ where the main focus is to report problems onthe website. It is one of the longest threads and exists since 2004 (Pouët2019b). Still, the website focuses on distributing demo productions via varioussections such as ‘Groups’ (demo collectives), ‘Parties’ (where the respectivedemos were shown or performed), and ‘Prods,’ which is the explicit area fordemos to be displayed and archived. They can be filtered according to theirtype, i.e., genre, and the platform on which they were encoded. Users having afree account are—other than non registered people—allowed to contributecontent and comment on prods. The same applies to the forum area, which isorganized according to specific topics. Since Pouët regards itself as a non-commercial site, it is not permitted to postprofit-oriented content, with theexception of independent developments that can be discreetly pointed out. Inaddition, it is impossible to register for a professional or team account; usershave to pay for.

Detailed Analysis of Appropriation Processes

To analyze strategies of solving problems or setting topics in the respective userinteractions, we zoomed into the communication practices of the three forums.Since GitHub, Stack Overflow, and Pouët allow and organize communicationflows differently, it was not possible to proceed methodologically the same wayin all three cases. Nevertheless, the spaces were examined for comparable cate-gories, especially in order to strengthen the peculiarities and differences of thethree learning ecologies.

The GitHub Awesome List of Creative Coding

The GitHub awesome lists present an opportunity for users to collect, organize, andshare learning resources and information concerning various topics. The main repos-itory of awesome lists, ‘the awesome list of awesome lists’ (GitHub 2019f), is curatedby Sindre Sorhus who also wrote the awesome manifesto which functions as a guideand gives helpful tips to people who want to make their own awesome list or contributeto an existing one. Users are encouraged to submit a new list, if they follow specificrules to be found in the manifesto. The awesome list of awesome lists is ‘watched’ (=actively followed) by more than 6000 users. It contains multiple single sublists whichall have a similar structure, as they are based on the awesome manifesto: Every list hasa small description/intro to define the topics of this list in the beginning. Furthermore,they refer to the possibilities of editing, giving everyone (beginners as well as advancedusers) the possibility to contribute to the list within a certain scheme.

In general, the lists closely related to programming languages/coding are moreelaborate than non-coding topics. It needs to be stressed that the awesome lists arecompletely curated by the community. The process of co-design of the GitHubawesome lists is discussed in the following using ‘the awesome list of creative coding’(GitHub 2019a) as the example of study. Within the general list of awesome lists, it is

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the only one that deals with this topic and includes all languages and tools that can beused for creative coding. It starts with a definition of creative coding:

Creative coding is a different discipline than programming systems. The goal is tocreate something expressive instead of something functional. Interaction design,information visualization and generative art are all different types of creativecoding – which has become a household term describing artworks articulated ascode (GitHub 2019a)

The software, tools, and languages common for creative coding are introduced in thebeginning of the list, whereas other helpful information is placed afterwards. Thisstructure is typical for all awesome lists. The list is divided into 13 sections and 28subsections that count 377 entries. The categories with the highest load of resources arearticles on shader programming (47 entries) and general information about math in thecontext of coding (33 entries). Another section worth mentioning is ‘communities,’ as itoffers valuable information on how to get in contact with other creative coders fromvarious fields (17 entries across the three subsections).

While the list has been created on 30 October 2016 by a user named terkelg, thereare 37 other users, who also contributed to it. Still, there is a huge imbalance betweenthe creator and regular users, as 215 of the 337 commits (changes) have been made byterkelg himself.

Fig. 7 displays the contribution activity to the master branch of the awesomelist—counting the single lines of code. There is a noticeable development fromhigh activity at the beginning of the list to sporadic changes conducted 2 yearslater. Accordingly, the form of the list was primarily determined at the beginning.

Fig. 7 Screenshot of GitHub creative coding awesome list, Commits Section. See https://github.com/terkelg/awesome-creative-coding/graphs/contributors. Accessed 30 July 2019

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After terkelg created the list in October 2016, until January 2017, he made 916commits and 441 deletions himself (GitHub 2019d), before anyone else contrib-uted to the list. Furthermore, the other contributors only made less than 10commits each, highlighting the fact that the creator of a list functions as its maincurator. This is supported by the given power structure which allows everyone tosuggest changes, but only enables the list creator to approve these before takingeffect. The contributions to the respective master list can be traced by everyone,since it is publicly available. In order to find out how the awesome list of creativecoding is composed, we analyzed the creation of the list and its contributors bymeans of a close reading.

The detailed analysis of the 38 contributors including terkelg illustrates that the vastmajority of users added something to the list rather than submitting changes of thecontent. All these changes are documented in the ‘network graph,’ a timeline of themost recent commits (GitHub 2019d). As already mentioned, the majority of commitswere made by the list creator, whereas the remaining commits can be described as smallchanges like correcting spelling mistakes or outdated links, rather than large changes tothe structure or content. Only the addition of a table of contents in May 2018 is worthmentioning, as most additions (35) and deletions (52) to the list’s code were made here.In general, additions and deletions are not registered as content elements, but as numberof codelines independent of the results they are connected to (see Fig. 7). Taking theexample of the table of contents, the contributor copied the existing structure andreplaced it with additional changes. The person adhered to existing structures and onlymade improvements, modifying the existing structure.

The participation in the list is not synonymous with activity on GitHub ingeneral: 23 of the users contributing to the list present themselves in their profilesas experts that work professionally as developers or coders. Fifteen users do notgive any information about their profession. Still, this does not imply that theyhave less expertise: eight of them are very active, making regular contributions(between 500–35,000 per year). Therefore, they can also be called experts (at leastin regard of the platform). The other seven users are inactive, i.e., they makealmost no contributions (0–86 per year), which is shown in their activity display.In addition, these seven users have only made minor changes such as replacinglinks, or little additions to the existing text.

In general, those who propose changes to the list have a high level of knowledge andare predominantly not beginners. While a contribution to the list is not to be equatedwith a high activity and vice versa, it is still more likely for experts to suggest commitsthan for beginners. Thus, it can be stated that an intervention in the lists is moreaccessible for people who are already highly active on the platform. The overalladditions demonstrate the curatorial power of the creator over the list and highlightthe different roles or levels of participation to be found among the users: othercontributors stick to the creator’s structures and rather suggest small changes toimprove the list. The given structures of the awesome list have general validity forthe curating process of every awesome list covering a specific topic like creativecoding. Furthermore, the structures massively frame the list itself. These clear andtransparent structures give users the opportunity to contribute to a list, understand thestructure, and retrace its history.

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Stack Overflow

Stack Overflow is designed to solve very specific appropriation problems in very shorttime, and communication is not categorized according to fields of application (likecreative coding) but is tagged with specific technologies and/or programming lan-guages. As already mentioned, Processing is a coding language especially created forcreative coding. Our detailed analysis of Stack Overflow is therefore concentrated onquestions marked with this tag. By July 2019, more than 5000 questions dealing withProcessing had been posed by the community and the body of topics rises by one tothree postings per day. For this analysis, we concentrated on the questions occurring inJune 2019. In this period, 54 questions tagged with ‘Processing’ were posted to thenetwork by 46 unique askers. Of these, 42 received at least one answer by thecommunity and 26 were marked as resolved by the initiators. The questions wereviewed 39.14 times on average, ranging from 14 views minimum to 80 views maxi-mum. In average, they were described with 2.09 tags in addition to the tag ‘Processing’.Among these tags, ‘Java’ and ‘Javascript’ were the most common with 29 occurrences.Combinations with ‘p5.js’ (9 occurrences), ‘arduino’ (8 occurrences), and ‘collision’ or‘collision-detection’ (6 occurrences) were next frequent. Apart from that only ‘serial-communication,’ ‘bluetooth,’ ‘Python,’ ‘glsl,’ ‘redraw,’ ‘vertex-shader,’ and ‘array/arraylist’ appeared more than once. Eight questions solely used the tag ‘Processing.’

While it is apparent that most postings apply tags as a way to categorize theirquestions—mainly according to the programming language(s) used—especially thosewith four or five tags tend to use the tag ensemble to condense the question mirroringits headline. In that manner, Q-ID3 9 for example is tagged ‘arduino’ ‘Processing’ ‘wifi’‘esp32’ shortening the headline ‘Send data from ESP32 to Processing via wifi.’ Q-ID24 is tagged ‘Java’ ‘loops’ ‘Processing’ ‘restart’ ‘redraw’ and headlined ‘How toredraw—restart a loop in Processing.’ Q-ID 45 is tagged ‘Java’ ‘eclipse’ ‘console’‘Processing’ including almost all the aspects of the headline ‘Can I run a program onEclipse that opens up the console, and then opens up a Processing window?.’ The list ofquestions, apart from the headline and the tags, also contains the name of the askinguser, their status as well as the first two lines of the question description and someinformation about views, votes, and number of answers are displayed (see Fig. 8).

The overview shows that the headlines are not always formulated as questionsbut also as statements describing a topic. In the corpus of analyzed questions, onlytwelve were generated as a true (complete) question, like the following: ‘Why isthere an error while importing Processing-core to Java?’ (Q-ID 8) or ‘What does_serial_.bufferUntil(byte) do, and how does it synergies with serialEvent?’ (Q-ID17). Sixteen more questions are built beginning with ‘How to,’ seven of themending with a question mark (like ‘How to make one side of the paddle bot, injava ping pong game?’ Q-ID 49) and nine without (like ‘How to properly use avertex shader to morph PShape,’ Q-ID 52). Only in ten of the questions the askerrefers to themselves (I have a randomly falling meteor an I want to make more ofthem,’ Q-ID 44 or ‘My ball doesn’t move smoothly but with stutters. How can Iachieve smoother movement?’ Q-ID 43).

3 Q-ID is the abbreviation for Question-ID.

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This picture totally changes when looking at the first lines of the question descrip-tion displayed in the overview. Only two of the 54 analyzed questions do not refer tothe person asking it as ‘I.’ These are Q-ID 51 using phrases like ‘when you drag’ and‘how to make’ which are at least still referring to a person and Q-ID 38 which reads‘Objective: When the red candles are clicked they should turn green. At the moment,when a candle is clicked, the next candle in the array is changed, instead of the candlethat was clicked’ and by that is formulated in a very neutral way. The other questionsare almost equally divided into askers claiming that they ‘want to’ or ‘would like to’ dosomething (15 questions), that they are ‘trying’ or ‘have tried’ something (15 ques-tions), that they are ‘making,’ ‘creating,’ ‘building’ (or similar) something at themoment (13 questions) and people directly communicating that they ‘need help’ orare ‘having trouble’ or ‘issues’ (9 questions). Only in three of the beginnings, the askerstell their audience that they are not self-driven working on a project (‘I have to make acode for a school project [...],’ Q-ID 1; ‘I am working with a PhD student on a researchinternship. I have been given the task to create a screen [...],’ Q-ID 21; ‘I have receivedan admission assignment for the Computer Science program, where I have to approachPI. [...],’ Q-ID 40). Looking at the reputation of the people posing the questions, onlyfive of them have more than 100 points. The others have a reputation level of 15 pointson average. Eight of them only gained one reputation point, signifying that the posed

Fig. 8 Screenshot of Stack Overflow. See https://stackoverflow.com/questions/tagged/processing?tab=newest&page=2&pagesize=50. Accessed 25 July 2019

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question is the first one a user has put on the forum and by that highlighting the fact thatStack Overflow builds a low threshold for new users.

Looking at the people answering the questions, one finds a totally different picture:concerning the 50 answers given by 27 unique users, the reputation points are 7000 onaverage. Looking only at the people who have given more than one answer, the averageis much higher (19k points). Among these, a user with 55.5k reputation stands out, asbeing the originator of fifteen of the given answers. In addition, it becomes visible thatanswers not seldomly lead to follow-up communication between the asker and theanswerer (1.93 comments on average). Still out of the 42 questions that lead to answers,sixteen didn’t result in comments. Seven were accompanied by one comment—usuallyused to thank the answerer and state that the problem was solved. Thereby, nineteenanswers triggered a conversation of at least two more turns. The longest was composedof ten turns as visible in Fig. 9, still staying appropriation oriented.

The analysis shows that communication on Stack Overflow is very focused on thepresented appropriation needs. The low view numbers of the single questions as well asthe high amount of problems marked as resolved, speak of the speciality of thenegotiated topics and the efficiency of the learning ecology—regardless of the enlistedusers’ coding competences.

Fig. 9 Screenshot of Stack Overflow comments section Q-ID17. See https://stackoverflow.com/questions/56728127/what-does-serial-bufferuntilbyte-do-and-how-does-it-synergies-with-serialev.Accessed 26 July 2019

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Pouët

Presentations of demo productions and conversations about code take place onPouët. Code is the central element that connects it with the other two learningecologies. On Pouët there are often links to GitHub, especially when it comes tofixing bugs noticed by users. There are also references to Stack Overflow, forexample, in cases of thematically similar existing threads. There are in total seventopics to choose from (‘general,’ ‘gfx,’ ‘music,’ ‘parties,’ ‘offtopic,’ ‘residue,’ and‘code’) that structure the BBS. The category ‘general’ is at the time of conductingthis research the largest with more than 8000 threads, while all others range between150 and 880 threads. As the analysis is focused on appropriation, the research of theBBS on Pouët only considers the code topic area, to which users independentlyassign their threads.

Currently, almost 700 threads are dealing with questions concerning code.4 Theoldest is from 2001, the last answer in this communication thread is from 2005. For theanalysis, we decided to take a closer look at the last 2 years of activity and thereforeincluded 110 threads. First, the threads included in the corpus were divided intocategories, according to the name of the thread and the initial post. It is noticeable thattwo especially long threads with more than 1800 replies found in the code section donot deal with problem-oriented topics, but have to be classified in the categoriesentertainment (‘Random line of code thread’) and presentation of demos(‘Raymarching Beginners’ Thread’). There are nine more threads with more than 100replies—among them is one thread that starts with a dedicated question, or rather aproblem to be solved, two more show learning resource users developed themselves orthey found and whose applicability is discussed by the forum members.

Considering the relation between the categories, one would find about 19% threadson non-appropriation-related topics (e.g., ‘Demos using Vulkan,’ ‘The demoscenesourcecode thread,’ ‘A.I. related stuff’), while about 81% of initial posts are devotedto questions of appropriation (e.g., ‘How to render SDF grid volumes?,’ ‘Is anyonewho’s having same problem as this?,’ ‘Any tips on creating this spiral torus effect?’).Non-appropriation-related topics can be threads focusing on presentation (of demos) orentertainment (like the ‘Random line of code thread’). Furthermore, there are threadsinitiated with the purpose to collaborate, connect, and to offer a job. Another significantnon-appropriation-related category is a collection of information, opinions about, andexperiences with a specific topic such as a technology. In the analysis, this category isnot assigned to the field of appropriation, although a collection of information un-doubtedly results in a corpus of knowledge that can initiate educational processes, butwhich, precisely because of the open question, does not serve any specific need forappropriation. On top of that, the unsorted—or rather non-curated—collection makes itdifficult to trace the contributions afterwards.

The analysis of appropriation-related threads constituting more than three-quarters ofthe corpus reveals a differentiation into four types: Open question on a specific need(34), Learning resource to be discussed (23), Specific problem to be solved (18), andTechnology based recommendation (14). Threads in the category ‘Specific problem tobe solved’ mostly start with a concrete code example that shows a bug—here, too,

4 Last accessed: 29 July 2019.

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GitHub is frequently referred to in order to offer solutions (pull requests) that can bediscussed more directly as in the very linear structure of Pouët. Open questions canrange between problem- and improvement-based concerns. In contrast to specificproblems, users wouldn’t fix a certain case. Just like resource-based concerns, technol-ogy recommendations are usually based on an object to be discussed, evaluated, orimproved. Overall, there is no trend of a certain amount of replies in the four categories,but with a few exceptions, the number of responses is in the two-digit range. The vastmajority of threads (82 out of 89) contain less than 50 replies. While in four threads, noone responded to the initial question or resource; on the other side of the spectrum, up to695 answers are possible.

Considering the activity of forum members, it shows that some users start threadsmore often than others - that is 21 out of 110 threads which are distributed among fiveusers who have started them. All other members have not opened more than twothreads. This results in a relatively balanced distribution where no users turn out to beparticularly dominant and influential regarding the topics to be discussed. Assessing theuser influence on the forum’s topics based on their experience is a challenge. Userprofiles can be interpreted, for example, to determine how many prods or posts havebeen created in the BBS as well as how many glöps have been received. However, notendencies in these categories can be seen between users who create threads and thosewho reply. Likewise, there are no discernible differences between the users of therespective analysis categories (non-/appropriation-related). This leads to the cautiousassumption that here, too, a very heterogeneous distribution of user participation andtheir influence on topics can be stated.

Discussion

In this paper we analyze the way code-related knowledge necessary for producingpostdigital art in the field of creative coding is appropriated and how informationresources are curated in the learning ecologies surrounding the field. We show thatappropriation in the sphere of artistically driven coding happens in diverging decentralspaces and is not located in a single digital space. Among these platforms, GitHub servesas a binding element as resources and documentation from all the other appropriationspaces are stored there and hyperlinks exist between them. In analyzing the concreteappropriation activities in the field of creative coding, we looked at the collaborativeinteractions in the different learning ecologies to understand how users communicatewith each other and what resources they use/produce. The analysis revealed that thethree spaces address different appropriation needs: while GitHub serves as an archive ora collection of knowledge—a wikipedia for creative coding, where users contribute tocollect high-ranked learning resources - the communication activities found there aremore connected to improving the material than to discussing actual problems inhandling a technology or similar. Stack Overflow to the contrary is driven by veryconcrete appropriation needs, which become visible in the communication taking place.It is oriented towards an efficient and fast question-answer mode and typically does notlead into elaborated off-topic conversation. Unlike GitHub, Stack Overflow is notencouraging its users to build networks, but rather promotes focused problem-basedinteraction. Pouët on the other hand leaves the most room to enrich appropriation-related

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conversations with activities that strengthen the scene-identity. This for example can beseen in the high load of entertainment-related threads and topics as well as in the longendurance of single threads maintained for several years.

The analysis also asked how open or beginner-friendly the platforms are. Wedocument that all the analyzed learning ecologies create various ways to familiarizenew users with their affordances. Especially for GitHub, we find a wide range ofsupport strategies, from designing the interaction modalities similar to social network-ing platforms, tutorials integrated into the website, through designated coding work-shops, to video information distributed via YouTube. In comparison, Pouët seemspretty reluctant to introduce the functions and structures of the website. Still, it needsto be stated that the forum is composed in a straight forward way with a limited range ofinteraction modalities. Therefore, the familiarizing activities of Pouët concentrate moreon facilitating the entrance to the scene. The three most important questions of what thesite is about, what a demo is, and where to get more information on the subject, areanswered in the FAQs. This shows that the user’s path of interest is quickly steeredfrom the function of the page to the actual topic, which is the demo. With itsinformation material, Pouët stays in the esthetic sphere of a traditional Internet forum,providing its resources like introductions and guidelines as texts spread over threads.Stack Overflow, too, provides text-based information about how the forum is used, butkeeps them short and concise, mirroring the webpage’s aim to promote focused,problem solving–oriented communication. Thereby, all three learning ecologies corre-spond to their overall goals that are gathering lots of (and various) user-generatedcontent for GitHub, fixing appropriation needs in a very fast way for Stack Overflowand creating a sense of community, where appropriation happens among lots of otheractivities for Pouët.

In addition to looking at support opportunities, it is also important toexamine barriers they hold for participation and the curatorial hierarchy theymight establish between media amateurs and professionals. The analysis showedthat Stack Overflow manages to encourage a lot of people new to the forum to askquestions concerning their appropriation needs. In comparison to that, the peopleanswering those questions were highly experienced. Pouët, by contrast, is alreadya place for experts in the field of Demo, the platform does not show much effort inrecruiting and introducing new users and interested people. Being a scene memberis mostly connected to having an account on Pouët and to knowing the commu-nication codes of the site which makes it easier for users to find their way around.The scene, as the analyzed communication dynamics in the space reveal, is opento new platform users, especially when dealing with beginner’s questions. Seriousquestions were answered seriously, regardless of a user’s platform experiencedocumented in their profile. However, Pouët profiles do not reflect users’ techno-logical background, making it difficult to determine if/how inexperienced codersshow initiative in opening or responding to threads or generally getting involvedinto shaping the space. The GitHub awesome lists are also accessible to everyoneand anyone can participate and propose changes and additions to the lists. Theclose reading of the awesome list of creative coding revealed that users whofrequently participate (like the list creator himself) generally have a very highactivity on GitHub and tend to make many public contributions. Furthermore, it isnoticeable that more than half of the contributors are experts in their field. There is

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no restriction to participate, regardless of the level of experience. Nevertheless, thedecision about what is added to the list and what is not is up to the list’s creator,which ultimately reveals a strong curatorial power position and might constitute abarrier for new users at the same time.

We also analyzed the “molding forces” (Hepp 2012) of the different spaces. Ingeneral, a high proportion of user-generated content can be recorded in all threespaces, via that influencing the learning ecologies’ structure. Taking the GitHubawesome lists as an example, which are all curated by their makers, but enableother users to contribute and suggest changes through repos and/or commits,creative coding spaces leave lots of space for creative output. Therefore, GitHubcan be described as an open, shapeable space. Users are creators and so theyparticipate in the curatorial. Furthermore, the platform is the most thematicallyopen and serves various purposes, as it is used by professionals as well asamateurs for different reasons. Pouët users do not have the opportunity to shapethe site’s space by influencing its structure except making suggestions on solvingbugs. But they do have the power to bring in topics and thus contribute to thecontent of the website. Stack Overflow also allows its users to sustainably changethe shape of the forum, i.e., by introducing new tags, but restricts these opportu-nities to those users who are highly active in the forum equipped with a certainreputation. The comparison shows that all three learning ecologies call for user-generated content but allow their users to participate in the curation and presen-tation of this content to different extents. User-generated content is taken to a newlevel within the esthetic turn. Users do not only actively participate in processes,but also determine, shape, and curate them—they constitute these spaces andthereby create learning resources that fit their own needs best.

Conclusion

As the title suggests, we have deliberately chosen to speak of and look for curatingstrategies in appropriation processes. Curation always requires to detect, interpret,evaluate, and select information, to make it available in a way users with a certainneed can access it. In doing so, every curatorial action produces meaning as well as ahierarchical system—constituting a barrier between those who share the informationand those who access it. This also becomes visible in the three discussed learningecologies: each pursue different curating strategies and thereby create different levels ofuser curation. The combination of looking at the learning ecologies’ structures, in termsof design, technical organization, and the way the users are addressed on the one hand,and at the specific appropriation-related communication taking place on the other hand,reveals that the visibility and presentation of interaction modalities, the introduction to acertain appropriation space and the implicit hierarchies trigger certain user behavior.While on the surface all spaces decidedly call for user participation, it becomes clearwhen looking at the concrete interaction taking place that apart from the non-profitspace, Pouët all ecologies use technical mechanisms to control the users’ influence,ensuring that on the one side they increase the amount of user-generated content toestablish their market value but on the other side they hold the power over the generalappearance and the substantive priorities.

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From this point of view, it needs to be questioned if the demand for participation—be it in creative coding forums or in the exhibitional field, which reveals to be anessential characteristic of the postdigital itself—is only an affordance of the overallpostdigital esthetics, fulfilling its own demand, namely, to participate in an estheticrather than in a decisive manner. The mentioned conditions, in which the analyzedprocesses of (creative) participation through appropriation take place, show how eachdesire of shaping the analyzed spaces is constrained by affordances given a priori andthe technical, esthetic, and organizing structures bearing them. Apparently, users areoffered and pushed to actively contribute topics, improve given structures, and access ascene they were not part of. But when it comes to outlasting co-creational interventions,the spaces’ conditions do not show the necessary flexibility—or maybe openness (ofmind). This meets the aims and strategies of curators in the field of postdigital art, whoalso mention that they want to find ways of allowing visitors to participate in thedifferent curatorial processes—but formulate those ideas very vague and frightful(PKKB 2018, 3: 92), imagining user curation with a very limited and predefined scope.

Still, in order to allow for real participation, curators or producers should be willingto see user (co)curated activities diffuse beyond the boundaries of a given frameworkand be open to new topics and structures. This would support the notion of knowledgeproduction as an ongoing collaborative process that needs to be considered as anunfinished set of streams of human and artificial interactions. Ultimately, this leads tothe question of how the different levels of user curation will influence the developmentof postdigital art in terms of curation and appropriation.

The forum analysis revealed different levels of participation—real and pseudoparticipation. Here, the spaces themselves are the decisive factor which determinesthe level of participation. Therefore, further research on the construction of these spacesin the field of postdigital art needs to be done to understand the developments of ourpresent culture. This includes taking a closer look at the role of algorithmic processes.While this topic is very present in other research fields such as social media studies, it isstill largely ignored in the field of arts.

Considering current discourses on the curatorial, however, the practice of curatingmust consider that every curatorial action is embedded into a socio-technical systemincluding multiple human as well as non-human agents who are not necessarily tied toacting subjects (Krysa 2011). However, we would like to stress that artificial entities,that are involved and underlying algorithms, are not necessarily intelligent. Curating,implying processes of meaning production and referring to the self-reflexivity of self-organized knowledge forms, can be an appropriate tool to describe and inscribe thesemechanisms.

Curating in the sense of a postdigital practice can uncover where these structuresbear the potential to open up for lasting creative and intellectual interventions byexceeding the given. This describes a continuous process of mutual negotiation andstruggle for interpretive sovereignty that merges the collaborating anthropotechnicalactors into a unified we. It shows that the request for equal and diverse participation,one of the early ideals of the Internet and one of the virulent demands of contemporaryexhibiting, can only be realized by being aware of the hybrid conditions of thepostdigital era. Besides the intersection of technology and humans or entangledphysical and digital spheres, this also means the pairs of (design) structure/chaos,knowing/not-knowing, sharing/being shared, being an expert/amateur, individuum/

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many. The encountering entities can be fluid and exceeding. In the postdigital, theseseeming paradoxes are no longer binary dichotomies but become dialectic networks,bearing the potential to resolve hierarchies.

Funding Information This paper was created within the framework of the research project ‘Postdigital ArtPractices in Cultural Education. Esthetical Encounters between Appropriation, Production and Education’located at the University of Applied Sciences Potsdam and funded by the Federal Ministry of Education andResearch, Germany (BMBF) since 2017.

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