Complexity And Uncertainty In DH Projects: A Co-design Approach Around Data Visualization

workshop / tutorial
Authorship
  1. 1. Eveline Wandl-Vogt

    Austrian Centre for Digital Humanities (ACDH) - OEAW Österreichische Akademie der Wissenschaften / Austrian Academy of Sciences

  2. 2. Enric Senabre Hidalgo

    Internet Interdisciplinary Institute - Open University of Catalonia

  3. 3. Roberto Theron

    VisUsal - University of Salamanca / Universidad de Salamanca

Work text
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Introduction
In the recent years, with the pervasiveness of computers and a great variety of electronic devices connected to the Internet, Digital Humanities (DH) as a research field has experienced a great transformation that has permitted the completion of very ambitious projects with large impact in the society beyond the academia. This has resulted in a major economic impact in the cultural and creative industry. A number of new and powerful ICT have made possible the exploitation of a wealth of data (either digitized or digitally born) that have, on the other hand, changed enormously the practice in DH, and exposed novel challenges that must be faced in order to complete any of the said projects. From the creation to the consumption of digital resources, there are new stakeholders, contexts and tasks to consider. The amount of digital resources produced (or digitized), stored, explored, and analysed in any DH project is immensely vast (specially if we take into account the introduction of linked-data), so the traditional humanities tools have to be either substituted or aided with ancillary tools in the form of interactive visualisations or novel user interfaces (Therón et al., 2018). Furthermore, during the whole lifecycle of any DH project -from the data preparation to the actual analysis or exploration phase-, many decisions have to be made in order to yield the desired results that depend on the uncertainty pertaining to both the datasets and the models behind them (Edmond, 2018).
The PROVIDEDH project (PROgressive VIsual DEcision-Making in Digital Humanities) aims to provide visual interactive tools that convey the degree of uncertainty of the datasets and computational models used behind, designed to progressively adapt the visualizations to incorporate the new, more complete or more accurate data (Therón and Wandl-vogt, 2018). The project not only takes into account scholars, since it is most relevant in DH the fact that the role of citizens has changed enormously (Finke and Lazlo, 2014). We live in a society that has democratized science, and the number of projects in which the contribution of citizens, either producing or using digital resources, has exploded. The experience gained in other areas of science in which the intervention of computing has been much deeper and constant can be analysed and adapted to the case of humanities (Edmond, 2013). Specially, regarding infrastructures, frameworks, models and tools that can be standardized for the different disciplines in the humanities.
Taking into account these key issues of complexity in data visualization for DH, the workshop will develop through knowledge design methods (Nelson and Stolterman, 2003; Zimmerman et al., 2007) and Open Innovation (Chesbrough, 2006) a hands-on sequence around specific software needs and features. More specifically, via participatory design (or “co-design”) with participants as ’domain experts’ of their own needs and experience (Visser et al., 2005). Design thinking, and co-design as it’s more participative dimension (Manzini and Coad, 2015), represents a set of practical approaches for the creative definition and solving of problems (Cross, 2011), as well as for generating different types and forms of design knowledge (Thoring and Müller, 2011). It offers a great variety of visual methods, procedures and techniques for designing new projects in complex and uncertain circumstances, as well as the simultaneous exploration of scenarios, user-centered and participatory approaches and the integration of many possible points of view (Blizzard and Klotz, 2012).

Workshop phases
Each stage of the workshop focuses on specific ways to generate and discuss visual information, in accordance with participatory design practices (Kensing and Blomberg, 1998). The different co-design and discussion phases will be based on research toolkit materials adapted expressly for the session and the DH2019 conference theme.

Phase 1 - “DIY” accreditation and general introduction: We begin by offering participants a series of ways to think about research perspectives and backgrounds in DH, customizing a session badge to identify approaches from a set of investigator roles and profiles. This way, we facilitate personal introductions and sharing of motivations for the session, followed by an introduction to the PROVIDEDH project goals, around data visualization and decision making in DH, as well as the rationale of the workshop phases.

Phase 2 - Presentation and discussion about exemplary visualizations in DH projects: Eliciting from participants’ experience and awareness about relevant DH projects, via rounds of short presentations this phase will focus on relevant aspects related to complexity in DH datasets and data visualization, following a convergence sequence (Brown and Katz, 2011). That is, in order to generate a discussion about visualization and complexities in DH in a participatory way (a sequence of divergence, by forming sub-groups) and a later coming-together to select options (convergence sequence) through idea-sharing and decision taking mechanisms.

Phase 3 - Comparison of complexity-related issues and matrix of uncertainty: Based on results from the previous phase, at this stage participants will discuss guided by a visual canvas (Senabre Hidalgo et al., 2018) the different criteria for assessing complexity and uncertainty in DH projects in relation to data sharing and visualization (among them, issues of openness / accessibility, public interest, potential social impact, reuse for transdisciplinary approaches, etc). The technique will allow for discussions oriented to software features and also set a shared understanding for the next iterations.

Phase 4 - Identification of user personas for prototype evaluation: Adapting the User Experience (UX) technique of personas from the field of user-centred systems design (Gulliksen et al., 2003), this part of the workshop will allow participants to generate and discuss different perspectives around potential end-users of the PROVIDEDH platform, as well as for other technological systems related to DH visualizations.

Phase 5 - PROVIDEDH prototype and DH-related user stories: Based on a selection of personas generated in the previous phase, this final part of the workshop will be twofold. On the one hand, it will allow participants to provide and discuss feedback on data visualizations features of the PROVIDEDH prototype. On the other hand, we will formulate in a series of new potential user stories (Ralph, 2015) in relation to DH complexity challenges around data visualization.

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