Approximated and User Steerable tSNE for Progressive Visual Analytics

Progressive Visual Analytics aims at improving the interactivity in existing analytics techniques by means of visualization as well as interaction with intermediate results. One key method for data analysis is dimensionality reduction, for example, to produce 2D embeddings that can be visualized and analyzed efficiently. t-Distributed Stochastic Neighbor Embedding (tSNE) is a well-suited technique for the visualization of several high-dimensional data. tSNE can create meaningful intermediate results but suffers from a slow initialization that constrains its application in Progressive Visual Analytics. We introduce a controllable tSNE approximation (A-tSNE), which trades off speed and accuracy, to enable interactive data exploration. We offer real-time visualization techniques, including a density-based solution and a Magic Lens to inspect the degree of approximation. With this feedback, the user can decide on local refinements and steer the approximation level during the analysis. We demonstrate our technique with several datasets, in a real-world research scenario and for the real-time analysis of high-dimensional streams to illustrate its effectiveness for interactive data analysis

The design-by-adaptation approach to universal access: learning from videogame technology

This paper proposes an alternative approach to the design of universally accessible interfaces to that provided by formal design frameworks applied ab initio to the development of new software. This approach, design-byadaptation, involves the transfer of interface technology and/or design principles from one application domain to another, in situations where the recipient domain is similar to the host domain in terms of modelled systems, tasks and users. Using the example of interaction in 3D virtual environments, the paper explores how principles underlying the design of videogame interfaces may be applied to a broad family of visualization and analysis software which handles geographical data (virtual geographic environments, or VGEs). One of the motivations behind the current study is that VGE technology lags some way behind videogame technology in the modelling of 3D environments, and has a less-developed track record in providing the variety of interaction methods needed to undertake varied tasks in 3D virtual worlds by users with varied levels of experience. The current analysis extracted a set of interaction principles from videogames which were used to devise a set of 3D task interfaces that have been implemented in a prototype VGE for formal evaluation

Interfaces for science: Conceptualizing an interactive graphical interface

6,849.32 new research journal articles are published every day. The exponential growth of Scientific Knowledge Objects (SKOs) on the Web, makes searches time-consuming. Access to the right and relevant SKOs is vital for research, which calls for several topics, including the visualization of science dynamics. We present an interface model aimed to represent of the relations that emerge in the science social space dynamics, namely through the visualization and navigation of the relational structures between researchers, SKOs, knowledge domains, subdomains, and topics. This interface considers the relationship between the researcher who reads and shares the relevant articles and the researcher who wants to find the most relevant SKOs within a subject matter. This article presents the first iteration of the conceptualization process of the interface layout, its interactivity and visualization structures. It is essential to consider the hierarchical and relational structures/algorithms to represent the science social space dynamics. These structures are not being used as analysis tools, because it is not objective to show the linkage properties of these relationships. Instead, they are used as a means of representing, navigating and exploring these relationships. To sum up, this article provides a framework and fundamental guidelines for an interface layout that explores the social science space dynamics between the researcher who seeks relevant SKOs and the researchers who read and share them.This work has been supported by COMPETE: POCI-01-0145-FEDER- 007043 and FCT - Fundação para a Ciência e Tecnologia within the Project Scope: (UID/CEC/00319/2013) and the Project IViSSEM: ref: POCI-010145-FEDER-28284

Exploratory topic modeling with distributional semantics

As we continue to collect and store textual data in a multitude of domains, we are regularly confronted with material whose largely unknown thematic structure we want to uncover. With unsupervised, exploratory analysis, no prior knowledge about the content is required and highly open-ended tasks can be supported. In the past few years, probabilistic topic modeling has emerged as a popular approach to this problem. Nevertheless, the representation of the latent topics as aggregations of semi-coherent terms limits their interpretability and level of detail. This paper presents an alternative approach to topic modeling that maps topics as a network for exploration, based on distributional semantics using learned word vectors. From the granular level of terms and their semantic similarity relations global topic structures emerge as clustered regions and gradients of concepts. Moreover, the paper discusses the visual interactive representation of the topic map, which plays an important role in supporting its exploration.Comment: Conference: The Fourteenth International Symposium on Intelligent Data Analysis (IDA 2015