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In this paper, we present our spreadsheet framework, which uses a spreadsheet-like interface for exploring biomedical datasets. The principles and advantages of this class of visualization systems are illustrated, and a case study for the analysis of hip joint congruity is presented. Throughout this use case, we see how end users can compare different datasets, apply parallel operations on data, create analysis templates, and how this helps them in the exploration process.

This article addresses 2-dimensional layout of high-dimensional biomedical datasets, which is useful for browsing them efficiently. We employ the Isomap technique, which is based on classical MDS (multi-dimensional scaling) but seeks to preserve the intrinsic geometry of the data, as captured in the geodesic manifold distances between all pairs of data points while classical approaches can see just the Euclidean structure. According to first two of Isomap's coordinates, the high-dimensional data points are arranged in a plane. Experimental results with images of marine creatures' shapes and 3D bone renderings are presented.

As the Sensor Internet starts to become reality, increasingly heterogeneous sensor networks are becoming interconnected into federated sensor networks and provide huge volumes of sensor data for a variety of applications to large user communities, such as in science and engineering. Effective metadata management plays a crucial role in processing and properly interpreting raw sensor measurement data, and needs to be performed in a collaborative fashion. Previous work on metadata management for experimental and measurement data has not provided specific support for joint real-time processing of metadata and sensor data. In this paper we propose a framework that allows effective sensor metadata management based on realtime metadata creation and processing over federated sensor networks. The framework is based on three key mechanisms: (i) Distributed metadata joins to allow streaming sensor data to be efficiently processed with associated metadata, regardless of their location in the network. (ii) Automated metadata generation to permit users to define monitoring conditions or operations for extracting and storing metadata from streaming sensor data. (iii) Advanced metadata search utilizing various techniques specifically designed for sensor metadata querying and visualization. The framework is currently deployed and used as the backbone of a concrete application in environmental science and engineering, the Swiss Experiment, which runs a wide variety of measurements and experiments for environmental hazard forecasting and warning.

This paper addresses evaluation and visualization of stress and strain on soft biological tissues in contact given three-dimensional models of reconstructed organs from magnetic resonance images (MRI), we use an anatomy-based kinematical model combined with a soft tissues model to represent their shape and behavior. Then, we compute resulting distribution of stress and strain on deforming surface when motion is simulated. The computed stress and strain are then effectively visualized using an interactive animation framework. Experimental results are illustrated in the case of the hip joint cartilage.

This article addresses visualization of deformation or shape differences between bones while conventional visualization techniques are often about a single bone such as its 3D reconstruction. Given a pair of bones with a set of corresponding anatomical landmarks, we compute displacement vectors describing the deformation from one bone to the other at the landmark points on one of the bones. Out of these prescribed ones, a displacement vector at each vertex on the bone surface is derived using a multi-level approximation technique of scattered data. Based on the value of inner product between a displacement vector and a surface normal at each vertex, color is mapped. Considering error-prone estimation of the landmark location in real applications, approximations at different levels are realized instead of exact interpolation as usually done in elastic image registration. Experimental results on a pair of femoral bones are presented.

The Open Support Platform for Environmental Research (OSPER) has been launched to take forward key data management components developed under the Swiss Experiment platform project to achieve improved usability and a wider scope. With this project, we aim to connect users to data and their context, an area identified during SwissEx as having the greatest potential impact on the research community. OSPER has a clear focus on providing the technology for data storage, management and exploitation with a special focus on data interoperability and documentation. In this presentation, we will demonstrate the key aims of OSPER for the period 2012 – 2015. Inheriting the basic SwissEx functionality, OSPER provides an excellent method of making data accessible via their metadata. One of the biggest differences between the OSPER infrastructure and other data platforms is the level of interaction that one can have with the data and the level of integration with the analysis tools used in science. We wish to capitalise on this advantage by increasing this integration and working with environmental research projects to develop the tools that make a difference to their daily research. The new data infrastructure will serve the following purposes: — Open documentation, archiving and discovery of datasets. — Facilitation of data sharing and collaboration (especially inter-disciplinary) with data owner controlled access rights, particularly concentrating on providing as much contextual information as possible. — Improvements in ease of data access and combination of data sources. — Tools for data visualisation and statistical and numerical data analysis with a focus on spatial data and trends. Key areas identified for development during OSPER are: — New infrastructure and content for current WebGIS-based data visualisation system to create a publicly available platform. — Provision of data in standard formats using standard methods as well as the consumption of such data by the processing/visualisation tools. — Provision of connected tools to provide commonly used functionality. — Cloud compatibility. — Greater integration of metadata and data. — Integration of publications using advances made in the ScienceWise project. — Advanced queries of 3- and 4-Dimensional data sources. — Documented examples of spatio-temporal statistical tools. Each of the components of the infrastructure (database middleware, WebGIS, model interfaces and processing/visualization tools) will be designed for usage both within the OSPER system and standalone. They will provide standardized interfaces, such that they can be adapted for use with data from any compatible infrastructure, and such that the data held within OSPER can be visualized or processed using any compatible tools. www.swiss-experiment.ch