"A Project Review Under The Focus Of Complexities On The Example Of ExploreAT!"

In recent years cross-disciplinary, cross-organisational and cross-sectoral research has been widely practised, linking across digital tools, research fields and actor groups. As our world is becoming increasingly more complex, this phenomenon is also particularly visible in academic fields, where complexities have arisen at several levels. In the field of Digital Humanities (DH) the benefit of bringing together different disciplines and research areas is the opportunity to work with complex data structures, thus providing a springboard for further scientific work. In this context, digital humanists not only have on an important role in the Humanities themselves, but also in relation to society. The processing of complex data provides increased opportunities to access Humanities knowledge across actor groups, and also enables more interested citizens to engage with it. As a result, DH have the opportunity to prove their importance to society, but at the same time participation of further actors groups yet again increases the complexity regarding the interaction with the society.
In this paper, we provide insights into the Digital Humanities project
exploreAT! - exploring austria’s culture through the language glass (Wandl-Vogt et al., 2015), against the complexities it has addressed and for which we introduce our solutions (cultural, semantic, visual, societal) by drawing on cross-disciplinary efforts in an international framework.

The project has addressed complexities on several levels and from several perspectives. To exemplify our approach, we here report on three complex aspects that were tackled: the focal topic food, the interaction with society within a open innovation framework and the use of existing and new technologies. These three aspects are met within a cultural analysis framework, in line with one of the definitions of culture in the literature (cf. Longhurst et al., 2008).
As a general background, the project has been based on a digitised German non-standard language collection from the time of the former Austro-Hungarian monarchy (Database of Bavarian Dialects in Austria, DBÖ) (Wandl-Vogt, 2008), counting around 3.5 million digitised entries. The project has aimed to rethink dialect lexicography, by connecting a language resource to real-world objects for cultural exploitation, bring it into European networks and infrastructures and open it for sustainable use and re-use for various actor groups such as scholars and citizens (cf. Dorn et al., 2018). Through the setup of complex data models (cf. Abgaz et al., 2018a; Abgaz et al., 2018b), the linking to and enrichment with other datasets and frameworks (LOD) was enabled and visualisation of this multi-modal content and underlying complex system has been achieved by different prototypes (cf. Benito et al., 2016; Benito et al., 2018). Through participatory methods, e.g. design thinking and agile research, community groups have been connected to these scientific efforts by looking into links to cultural and societal challenges. In addition, it has also given rise to exploration space
, an experimental Open Innovation Research Infrastructure (OI-RI) for the Humanities, which has been listed as a best practice example by the Austrian Federal Ministry of Science, Research and Economy, and is also as an example in the citizen science policy report.

Citizen science has provided the project the possibility to engage non-experts in the scientific process, to raise e.g. their understanding of scientific work, but also to raise the understanding of social needs of the involved scientists (Silvertown 2009). With the widespread availability and use of the internet and especially smartphones, the past decade has seen a remarkable increase in successful web-based citizen science projects (e.g. FoldIt, GalaxyZoo, PatientsLikeMe) and showed the potential of these approaches. While these have highlighted the advantages of citizen involvement in science, they have also triggered debate (Riesch and Potter 2014). Legal and ethical questions have been raised regarding data security (Kaye et al., 2012), the risk of harming participating citizens (Vayena and Tasioulas 2013) or using them only as a free labour for scientific research projects. Our project aimed to tackle these issues by implementing citizen science within an Open Innovation framework, giving participating citizens the possibility to engage with the project from the beginning and to deliver their inputs and ideas with low barriers.
Learning to understand each other is a complex undertaking that requires time and, above all, physical space. For this reason, the exploration space was established, which in addition to the digital aspects of the project also provided physical space for interaction with citizens. In this room, among other things, workshops were held in which where a crucial part to interact with interested citizens. This physical space offered the opportunity to interact directly, to jointly answer sensitive and difficult questions and to develop concrete ideas for solutions.
In this context, citizens and researchers engaged through participatory formats such as co-creation and co-design workshops in different scenarios around the cultural topic of food, which provides a wide field with numerous perspectives of engagement across actor groups and also with different community groups (cf. Palfinger et al., 2018). With food being treated as either a service, a product or an emotion, the complexity of the subject offered also several possibilities for new cultural research questions with insights for lexicographic analysis. By applying different technological tools and methods, combining state-of-the art (i.e. thesauri) and novel technologies (Artificial Intelligence), the processing of these complex data was enabled to access, structure and analyse the derived cultural content.
Finally, we aim to share our learnings from this project with communities and future projects with similar interests and challenges. On the one hand, we share our processes and learnings in face-to-face workshops (brainfood lectures, etc.), but also the applied methodologies are made available online and can thus be readily applied to datasets or projects who wish to follow a similar approach. In our endeavours we follow the FAIR data principles and aim to make our data and insights better findable, useable and reusable for the benefit of scholars and actor groups beyond.

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