Subjunctive interfaces

Lunzer, Aran; Hornbæk, Kasper

doi:10.1145/1314683.1314685

Cited by 45 publications

(8 citation statements)

References 46 publications

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“…Dynamic clustering of information. This requires efforts for new and better data summarisation and visualisation, and user interfaces for parallel exploration [37] such as subjunctive interfaces [40].…”

Section: Data Visualisationmentioning

confidence: 99%

The societal impact of big data: A research roadmap for Europe

Cuquet¹,

Fensel²

2018

Technology in Society

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With its rapid growth and increasing adoption, big data is producing a substantial impact in society. Its usage is opening both opportunities such as new business models and economic gains and risks such as privacy violations and discrimination. Europe is in need of a comprehensive strategy to optimise the use of data for a societal benefit and increase the innovation and competitiveness of its productive activities. In this paper, we contribute to the definition of this strategy with a research roadmap to capture the economic, social and ethical, legal and political benefits associated with the use of big data in Europe. The present roadmap considers the positive and negative externalities associated with big data, maps research and innovation topics in the areas of data management, processing, analytics, protection, visualisation, as well as non-technical topics, to the externalities they can tackle, and provides a time frame to address these topics in order to deliver social impact, skills development and standardisation. Finally, it also identifies what sectors will be most benefited by each of the research efforts. The goal of the roadmap is to guide European research efforts to develop a socially responsible big data economy, and to allow stakeholders to identify and meet big data challenges and proceed with a shared understanding of the societal impact, positive and negative externalities and concrete problems worth investigating in future programmes. IntroductionThe volume of data is growing exponentially, and is expected to reach the tens of zettabytes in 2020, of which a third is expected to be valuable if analysed, and about 40% will require protection [1]. The acquisition, analysis, curation, storage and usage of such big data may result in effects experienced by third parties that had no direct involvement in the activity itself. These externalities-positive if the action causes a positive effect or benefit to the third party, negative if it causes cost or harm-arise from decisions, activities or products by stakeholders such as industry, researchers and policy-makers.The present document contributes to the formulation of a strategy to define research and innovation efforts necessary for the realisation of a European big data economy by capturing and addressing the positive and negative societal externalities associated with the use of big data. It complements the technical challenges already identified [2] by taking a special focus on societal impacts, skills development and standardisation, and has been developed in parallel with a policy roadmap in the context of a multi-disciplinary study of the societal impacts of big data in seven European sectors aimed to define a roadmap and create a community that address and optimise these impacts [3].The term big data has received numerous definitions [4,5]. To develop the roadmap, we considered as a working definition that big data is that which uses big volume, big velocity, big variety data assets to extract value (insight and knowledge), and furthermor...

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Section: Data Visualisationmentioning

confidence: 99%

The societal impact of big data: A research roadmap for Europe

Cuquet¹,

Fensel²

2018

Technology in Society

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“…Moreover, while real-world analyses tend to be messy and complex, today's tools still largely rely on single-state models involving one user at a time [39]. This disconnect contributes to making analytic practices cumbersome and increases cognitive load [24,28]. Worse still, a lack of support for exploring alternatives, explicit management of uncertainty in analysis, and support for collaboration in sense-making can lead to poor problem solving and decision-making [29].…”

Section: Introductionmentioning

confidence: 99%

Understanding the Role of Alternatives in Data Analysis Practices

Liu

Boukhelifa

Eagan

2019

IEEE Trans. Visual. Comput. Graphics

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Data workers are people who perform data analysis activities as a part of their daily work but do not formally identify as data scientists. They come from various domains and often need to explore diverse sets of hypotheses and theories, a variety of data sources, algorithms, methods, tools, and visual designs. Taken together, we call these alternatives. To better understand and characterize the role of alternatives in their analyses, we conducted semi-structured interviews with 12 data workers with different types of expertise. We conducted four types of analyses to understand 1) why data workers explore alternatives; 2) the different notions of alternatives and how they fit into the sensemaking process; 3) the high-level processes around alternatives; and 4) their strategies to generate, explore, and manage those alternatives. We find that participants' diverse levels of domain and computational expertise, experience with different tools, and collaboration within their broader context play an important role in how they explore these alternatives. These findings call out the need for more attention towards a deeper understanding of alternatives and the need for better tools to facilitate the exploration, interpretation, and management of alternatives. Drawing upon these analyses and findings, we present a framework based on participants' 1) degree of attention, 2) abstraction level, and 3) analytic processes. We show how this framework can help understand how data workers consider such alternatives in their analyses and how tool designers might create tools to better support them.

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“…In 2008, Lunzer coined the term Subjunctive Interfaces to describe interfaces that support the exploration of multiple scenarios [12]. For example, Side Views [20] is an interesting example of an early feedback technique that gave previews of the results of different choices a user may make (e.g., making text bold vs. italic).…”

Section: Single Document Model and Subjunctive Interfacesmentioning

confidence: 99%

“…This paper focuses on fusing and presenting multiple alternatives, one of which is eventually selected to disambiguate input. In contrast, both Parallel Paths and the RecipeSheet [12] provide facilities for manipulating alternatives interpretations directly. The ideas presented in subjunctive interfaces contain a wide range of possibilities for future work.…”

Section: Single Document Model and Subjunctive Interfacesmentioning

confidence: 99%

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An Architecture for Generating Interactive Feedback in Probabilistic User Interfaces

Schwarz

Mankoff

Hudson

2015

Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems

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Increasingly natural, sensed, and touch-based input is being integrated into devices. Along the way, both custom and more general solutions have been developed for dealing with the uncertainty that is associated with these forms of input. However, it is difficult to provide dynamic, flexible, and continuous feedback about uncertainty using traditional interactive infrastructure. Our contribution is a general architecture with the goal of providing support for continual feedback about uncertainty.Our architecture is based on prior work in modeling uncertainty using Monte Carlo sampling, and tracks multiple interfaces -one for each plausible and differentiable sequence of input that the user may have intended. Importantly, it considers how the presentation of uncertainty can be organized and implemented in a general way. Our primary contribution is a method for reducing the number of alternative interfaces and fusing possible interfaces into a single interface that both communicates uncertainty and allows for disambiguation. We demonstrate the value of this result through a collection of 11 new and existing feedback techniques along with two applications demonstrating the use of the feedback architecture.

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Subjunctive interfaces

Cited by 45 publications

References 46 publications

The societal impact of big data: A research roadmap for Europe

The societal impact of big data: A research roadmap for Europe

Understanding the Role of Alternatives in Data Analysis Practices

An Architecture for Generating Interactive Feedback in Probabilistic User Interfaces

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