Auke Akkerman - Federica Bardelli - Hilje de Boer - Thom Bovelander - Stef van den Broek - Daniela Diewock - Anne van Egmond - Rik van Eijk - Rosemary Hill - Arla Krikke - Andreea Mironiuc - Michael ten Pas - Daniël van der Poel - Marissa Sieuwerts - Alexandros Valarakis - Giel Veenstra - Kyrsha Verweij
The connotation with the word dashboard is that of a car (or perhaps other vehicles). Nevertheless, the word comes from a dashboard on horse carriages, which prevented the passengers of getting dirty due to the horses trot on the ground (hence dash): an upturned screen of wood or leather placed on the front of a horse-drawn carriage, sleigh or other vehicle that protected the driver from mud, debris, water and snow thrown up by the horse's hooves (Oxford Dictionary). Nevertheless, it is nowadays closely tied to phenomenon of control panels that allow for information retrieval and action. Examples of these dashboards are a car dashboard which provides information relating the car (speed, amount of fuel), or Google Analytics, which let the admins or moderators of a website see into the statistics of a website. Based on this information, dashboards provide a function (both directly and indirectly) to enhance or tweak performance, constructing a power relation between the ones that have direct access to the dashboard, and those that are subject of it.
This research report will approach a "dashboard of dashboards", using methods designed by the Digital Methods Initiative. Approaching dashboard images over a period of time, a lineage is created wherein one can analyze change over time and medium specific changes in Google Images' perception of dashboards. The result will be a cohesive paper contributing in the ongoing debate of dashboard (interfaces); methods and findings relating to the DMI; and a lineage of change over time and power relations between the dashboard user and provided information. Interfaces and dashboards are in constant connection with data. The underlying software structures, algorithms and database governmentalities form the basis on which interfaces and dashboards are created. Both the interface and dashboard provide information to the user, and functions as a mediator between what is on the screen and what the user can collect.
The combination of real-time data, the objective of the dashboard and the 'faith' that is put into the use of a dashboards, provokes the question of dashboard objectivity. There are several key elements relating to dashboards: the interface software structure behind it (what is shown, what is not shown) and the algorithms combined with the power that one accessing a dashboard has over those that do not have access to the dashboard (and hence, the data).
Firstly, the interface that is shown on a dashboard is subject to the subjectivity of the developers. By providing functions or modules build into the (standardized or custom made) dashboard, certain values are enhanced whilst ignoring different information. Because of this, the user of the dashboard is subject to the subjectivity of those that make the dashboard; the user takes part within a "grammar of action" (Agre 745). The grammars of actions are build in, either on request or within a standardized template, to provide the user the best information reaching its objective. Secondly there is the use of algorithms relating to the aggregated data that is shown on dashboards. As Cheney-Lippold suggests, algorithms base their choices on the dividual of ones subject: We no longer find ourselves dealing with the mass/individual pair. Individuals have become dividuals; masses have become samples, data, markets or banks (5). The dividual itself is part of Deleuzes society of control, which elaborates on Foucaults disciplinary societies of closed spaces. Within the society of control, ones dividual is not within an enclosed space, but is in different places at the same time. Though, this explanation is heavily reduced and minimized, it reflects the theories of Foucault and Deleuze. One must know that dividual data is used within a system of algorithms to either place them in or move them between categories, or define new or differentiate existing categories (Cheney-Lippold). At the same time, dividual information may be manipulated by those that provide them, thus creating false data for algorithmically analysis - and thus categorization. Because of this we enter a governmentality Dodge and Kitchin call automated management.
Researching the visual representations of Google Images, one should keep in mind that dashboards themselves are a heavily subjective concept, subject to several discussions related to power, control and software. The approach taken in this study does not reflect any interactive use with the dashboards shown, but keeps the above-mentioned theories in account relating the research question, methodology and results.
The present understanding of the Web opens up the possibility for using online data in order to research society and culture and make online grounded claims (Rogers 4). One could say that we are in an era where the virtual can function as indication of the real. There is no clear boundary between the online and offline anymore; they are intertwined. Therefore, Google is an interesting medium to do research with. An important dualism that should be kept in mind is that of using online media to research the workings of the system and using online media to study societal or cultural developments (Rogers 95-7).
In order to set up a lineage of dashboards and analyze Google Images approach towards the dashboard, a dataset was created for the years 20082014. In general, the dataset consists of images retrieved over the daterange of a year; the year 2008 is an exception because the first images that were saved for the query dashboard on Google Images only date back to the 16th of April 2008. Therefore, the dataset for the year 2008 started from that point on.
Therefore, there had to be a slight change in methodology. The top thirty results were harvested using the Google Image Scraper tool, the larger images were downloaded manually. The Google Image Scraper tool was used to fetch the URls to Google Image results with a specified date range. The top 30 images of these result pages were manually downloaded and sorted in order of Google raning.
As mentioned in relation to the query design, our aim was to have an as neutral as possible starting point. Therefore, there is no preliminary set of categories decided on to allocate different types of dashboards. Instead, we have used an emergent coding scheme to define different categories, by evaluating the dataset per year. We have decided upon categories based on the discernable trends per year, which are demarcated as followed:
External data vs. native online data
Overall, throughout the dataset there is a shift visible from dashboards that use external data that was not produced online towards dashboards that are based on data with an online source, natively online data. There is a decreasing number of dashboards featuring external data whilst there is an increase visible in those featuring native online data throughout the years that were being taken into consideration in the analysis. In general, there are a few shifts that could be identified out of these results: from documenting to monitoring, from archived data to actionable data (as fundament for concrete future steps), from savers of knowledge to producers of knowledge.
Static vs. interactive
All years feature substantial use of icons. there are no big changes in the quantity of icons over most years, except for 2008 that featured about half the amount of use of icons compared to the other years. 43% of the dashboards in 2008 feature the use of icons. 67% up to 87% of dashboards between 2009-2014 feature the use of icons. The analysis provided no clues for an increase or decrease in icon use over time. Differences mostly occurred in relation to design trends as icons become more visually abstract, decreasingly reflecting the real world. An interesting notion is the rise of social icons as well as the appearance of the mechanical cog wheel to indicate settings.
Skeuomorphism (analog metaphors)
Overall, skeuomorphism is limited mostly to old dashboard meters. We can see these kind of meters getting more abstract over the years and less dashboards use meters as a metaphor. From a control standpoint: skeuomorphism are used to give a sense of comfort and familiarity through design which could be seen as a form of control for the user. It can also have direct effect on the usability of the dashboard. The more familiar the dashboard design, the easier it is to understand and the more 'control' the user feels. Interestingly the skeuomorphisms are used less over the years, which could indicate that this idea of familiarity has changed (people have been getting used to digital formats).
First of all we should address that a lot of decisions we made during the process were based on practical considerations. For instance, we chose five categories because it was an easy number to divide between groups. We chose 30 pictures because we had to do it manually and more would be too much work in the set timeframe. The categorization we made relating to the categories are also not objective, and thus we suggest that more research needs to be done in this categorization process, both on a qualitative and quantitative basis.
The results show that there is a decrease in skeuomorphism and external data, and an increase in personalized dashboards, the use of iconography and interactivity. Out of this, we can conclude that the representation of dashboards through the medium of Google Image search, changes over time towards a more personalized, interactive dashboards. Although controversial, this could be linked to the increase in data gathering practices and the introduction of (personalized) tools over the researched years. The images retrieved from Google Images show that dashboards still mediate between the data and user, although we can speculate who is the user: either an organization, government or person.To describe the way we experienced the representation of dashboards, we want to propose to use the cog wheel as a visual metaphor that reminds us of the mechanical age. The cog wheel offers more control to users by customizing and adjusting the dashboard according to their own wishes. However, users do not have real control because there is only a predefined route to follow. Deleuze uses the highway system as metaphor for this situation: drivers think they are able to choose their own route, but are limited to the highway routes that are already determined for them. This metaphor could be adjusted to dashboards as well: we can conclude that users are getting more control in the sense of adjusting settings and customizing layouts, but these possibilities are already pre-defined.
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