Mandy Keck

Towards a formalization of multi-touch gestures

Multi-touch is a technology which offers new styles of interaction compared to traditional input devices like keyboard and mouse. Users can quickly manipulate objects or execute commands by means of their fingers and hands. Current multi-touch frameworks offer a set of standard gestures that are easy to use when developing an application. In contrast, defining new gestures requires a lot of work involving low-level recognition of touch data. To address this problem, we contribute a discussion of strategies towards a formalization of gestural interaction on multi-touch surfaces. A test environment is presented, showing the applicability and benefit within multi-touch frameworks.

DepthTouch: an elastic surface for tangible computing

In this paper we describe DepthTouch, an installation which explores future interactive surfaces and features elastic feedback, allowing the user to go deeper than with regular multi-touch surfaces. DepthTouchs elastic display allows the user to create valleys and ascending slopes by depressing or grabbing its textile surface. We describe the experimental approach for eliciting appropriate interaction metaphors from interaction with real materials and the resulting digital prototype.

Immersive data grasping using the e x plore table

Accustomed to traditional user experiences with mouse and keyboard, designers are challenged to break free and find new and compelling approaches to interaction design for natural user interfaces. Tangible and embodied interaction works in parallel, is quick, and allows cooperative work. This exploration serves to inspire and provoke critical reflection on interaction design for natural user interfaces based on physical substances that are used in everyday life -- like eggs, soap bubbles, and magnets.

Exploring Similarity

Faceted browsing is an established and well-known paradigm for product search. However, if the user is unfamiliar with the topic and the provided facets, he may not be able to sufficiently reduce the amount of results. In order to increase the understanding of the bidirectional relation between facets and result set, we present an interface concept that allows manifold approaches for product search, analysis and comparison starting with a single product or a summarizing visualization of the entire data set. Moreover, various product features can be analyzed in order to support decision-making. Even without detailed knowledge of a specific topic, the user is able to estimate the range and distribution of characteristics in relation to known or desired features. Conventional list-based search forms do not provide such a quick overview. Our concept is based on two visualization techniques that allow the representation of multi-dimensional data across a set of parallel axes: parallel coordinates and parallel sets.

Revisiting Graspable User Interfaces

The use of metaphors can support the understanding of novel interfaces approaches and increase the ease of use. But the design of novel holistic and adaptable metaphors is still challenging for interface designers. While most literature provides no systematic instruction for metaphor design or recommend to use a repertoire of known metaphors, we present a method that focuses on the generation of new metaphors based on the analysis and abstraction of everyday objects and the separate analysis of the given problem domain. Several methods of the field of human-computer interaction and traditional design support these analyzes. The methods presented in this paper are suitable especially for graspable user interfaces and illustrated by examples from several workshops.

TagStar: a glyph-based interface for indexing and visual analysis

TagStar is designed to support users during the classification of data items based on a multidimensional classification scheme. We also intend to support experts when analyzing the database. Analytic features of the presented visual indexing system allow experts to discover insufficiently described resources with little effort. The resulting interface concept is based on star glyphs to visualize the multivariate data.

Natural interface exploration

Finding new and compelling approaches to interaction design for natural user interfaces, is challenging. The Natural Interface Exploration studio will offer participants the opportunity to explore interaction design for natural user interfaces based on physical substances that are used in everyday life. Studio organizers will present an overview of their methodology, providing examples of their experience [1, 2] and comparing it to other approaches. They will demonstrate how they analyze natural substances regarding the aspects of visualization and interaction and what kind of interfaces resulted [3, 4, 5] from these findings in initial workshops (see Figure 3 and 4). Following the demonstration, participants will form teams and collaboratively decide which substances or materials they would like to analyze. After examining and charting relevant aspects, the teams will chose a certain task to be solved with a new kind of interface. Example tasks will be provided by the studio organizers. The next step will be to decompose the tasks into required interaction and information needs. Finally participants will develop their own interface mock-up using stop motion or paper prototyping. Finally, studio organizers will facilitate a group critique session and offer closing thoughts on employing this methodology in ones creative TEI practice.

Improving Motive-Based Search

In complex search scenarios like planning a vacation or finding a suitable gift for a friend, the user usually does not know exactly what he is looking for at the beginning. However, this is the question that most search interfaces present as first step. In this paper, we discuss approaches for supporting the user in expressing a search query based on vague feelings and ideas. We therefore consider search interfaces on the syntactic, semantic and pragmatic level and discuss different mechanisms of these levels to support the first stages of the information seeking process.

Towards Glyph-based visualizations for big data clustering

Data Analysts have to deal with an ever-growing amount of data resources. One way to make sense of this data is to extract features and use clustering algorithms to group items according to a similarity measure. Algorithm developers are challenged when evaluating the performance of the algorithm since it is hard to identify features that influence the clustering. Moreover, many algorithms can be trained using a semi-supervised approach, where human users provide ground truth samples by manually grouping single items. Hence, visualization techniques are needed that help data analysts achieve their goal in evaluating Big data clustering algorithms. In this context, Multidimensional Scaling (MDS) has become a prominent visualization tool. In this paper, we propose a combination with glyphs that can provide a detailed view of specific features involved in MDS. In consequence, human users can understand, adjust, and ultimately improve clustering algorithms. We present a thorough glyph design, which is founded in a comprehensive survey of related work and report the results of a controlled experiments, where participants solved data analysis tasks with both glyphs and a traditional textual display of data values.

Visualizing uncertainty in flow diagrams: a case study in product costing

Business Intelligence applications often handle data sets that contain uncertain values. In this work we focus on product costing, which deals with the average costs of product components - that vary significantly based on many factors such as inflation, exchange rates, and commodity prices. After experts provide the uncertainty information for single items, decision makers need to quickly understand the cost uncertainties within the hierarchical data structure of the complete product. To provide this kind of quick overview, we propose a holistic visualization that contains both data and uncertainty. Since Flow diagrams are suitable to visualize tree data structures associated with value attributes, we focus on incorporating uncertainty information directly into these diagrams. Interviews with product costing experts led us to base our solution on Sankey diagrams. We chose three visualization techniques that are able to convey uncertainty information to the user: Color-code, Gradient, and Margin. We contribute a user study, which involved solving different product costing tasks using these three different visualizations. From the recorded error rates and subjective feedback, we designed an integrated approach that combines elements from all three distinct techniques.