17,260 research outputs found

    Understanding spatial data usability

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    In recent geographical information science literature, a number of researchers have made passing reference to an apparently new characteristic of spatial data known as 'usability'. While this attribute is well-known to professionals engaged in software engineering and computer interface design and testing, extension of the concept to embrace information would seem to be a new development. Furthermore, while notions such as the use and value of spatial information, and the diffusion of spatial information systems, have been the subject of research since the late-1980s, the current references to usability clearly represent something which extends well beyond that initial research. Accordingly, the purposes of this paper are: (1) to understand what is meant by spatial data usability; (2) to identify the elements that might comprise usability; and (3) to consider what the related research questions might be

    Dynamics of tilt-based browsing on mobile devices

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    A tilt-controlled photo browsing method for small mobile devices is presented. The implementation uses continuous inputs from an accelerometer, and a multimodal (visual, audio and vibrotactile) display coupled with the states of this model. The model is based on a simple physical model, with its characteristics shaped to enhance usability. We show how the dynamics of the physical model can be shaped to make the handling qualities of the mobile device fit the browsing task. We implemented the proposed algorithm on Samsung MITs PDA with tri-axis accelerometer and a vibrotactile motor. The experiment used seven novice users browsing from 100 photos. We compare a tilt-based interaction method with a button-based browser and an iPod wheel. We discuss the usability performance and contrast this with subjective experience from the users. The iPod wheel has significantly poorer performance than button pushing or tilt interaction, despite its commercial popularity

    Neuroimaging study designs, computational analyses and data provenance using the LONI pipeline.

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    Modern computational neuroscience employs diverse software tools and multidisciplinary expertise to analyze heterogeneous brain data. The classical problems of gathering meaningful data, fitting specific models, and discovering appropriate analysis and visualization tools give way to a new class of computational challenges--management of large and incongruous data, integration and interoperability of computational resources, and data provenance. We designed, implemented and validated a new paradigm for addressing these challenges in the neuroimaging field. Our solution is based on the LONI Pipeline environment [3], [4], a graphical workflow environment for constructing and executing complex data processing protocols. We developed study-design, database and visual language programming functionalities within the LONI Pipeline that enable the construction of complete, elaborate and robust graphical workflows for analyzing neuroimaging and other data. These workflows facilitate open sharing and communication of data and metadata, concrete processing protocols, result validation, and study replication among different investigators and research groups. The LONI Pipeline features include distributed grid-enabled infrastructure, virtualized execution environment, efficient integration, data provenance, validation and distribution of new computational tools, automated data format conversion, and an intuitive graphical user interface. We demonstrate the new LONI Pipeline features using large scale neuroimaging studies based on data from the International Consortium for Brain Mapping [5] and the Alzheimer's Disease Neuroimaging Initiative [6]. User guides, forums, instructions and downloads of the LONI Pipeline environment are available at http://pipeline.loni.ucla.edu

    Effects of White Space on Consumer Perceptions of Value in E-Commerce

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    As e-commerce becomes an increasingly large industry, questions remain about how the isolated effects of design elements on websites influence consumer perceptions and purchasing behavior. This study used a quantitative approach to measuring the effect of a ubiquitous element of design, white space, on the perception of the monetary value of individual items. White space is a key component of design and website usability, yet it has been shown to be related to the perception of luxury. Little is known about the direct relationship between manipulation of white space and the outcomes on consumer perceptions of value in an e-commerce context. This study found no significant difference between two levels of total white space area (large vs. small) measured by participants\u27 perceived cost of items (chairs). In contrast, while holding total white space constant, the effect of white space distance between images was significant for males but not for females. Additionally, no significant relationship between gender and frequency of online shopping behavior was found, χ2(1) = 3.19, p = .07, ϕ = .17. Gender and amount of time spent per month online were significantly related, χ2(1) = 6.21, p = .013, ϕ = .24
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