Improving Big Data Visual Analytics with Interactive Virtual Reality

For decades, the growth and volume of digital data collection has made it challenging to digest large volumes of information and extract underlying structure. Coined 'Big Data', massive amounts of information has quite often been gathered inconsistently (e.g from many sources, of various forms, at different rates, etc.). These factors impede the practices of not only processing data, but also analyzing and displaying it in an efficient manner to the user. Many efforts have been completed in the data mining and visual analytics community to create effective ways to further improve analysis and achieve the knowledge desired for better understanding. Our approach for improved big data visual analytics is two-fold, focusing on both visualization and interaction. Given geo-tagged information, we are exploring the benefits of visualizing datasets in the original geospatial domain by utilizing a virtual reality platform. After running proven analytics on the data, we intend to represent the information in a more realistic 3D setting, where analysts can achieve an enhanced situational awareness and rely on familiar perceptions to draw in-depth conclusions on the dataset. In addition, developing a human-computer interface that responds to natural user actions and inputs creates a more intuitive environment. Tasks can be performed to manipulate the dataset and allow users to dive deeper upon request, adhering to desired demands and intentions. Due to the volume and popularity of social media, we developed a 3D tool visualizing Twitter on MIT's campus for analysis. Utilizing emerging technologies of today to create a fully immersive tool that promotes visualization and interaction can help ease the process of understanding and representing big data.Comment: 6 pages, 8 figures, 2015 IEEE High Performance Extreme Computing Conference (HPEC '15); corrected typo

3D-Stereoscopic Immersive Analytics Projects at Monash University and University of Konstanz

Immersive Analytics investigates how novel interaction and display technologies may support analytical reasoning and decision making. The Immersive Analytics initiative of Monash University started early 2014. Over the last few years, a number of projects have been developed or extended in this context to meet the requirements of semi- or full-immersive stereoscopic environments. Different technologies are used for this purpose: CAVE2™ (a 330 degree large-scale visualization environment which can be used for educative and scientific group presentations, analyses and discussions), stereoscopic Powerwalls (miniCAVEs, representing a segment of the CAVE2 and used for development and communication), Fishtanks, and/or HMDs (such as Oculus, VIVE, and mobile HMD approaches). Apart from CAVE2™ all systems are or will be employed on both the Monash University and the University of Konstanz side, especially to investigate collaborative Immersive Analytics. In addition, sensiLab extends most of the previous approaches by involving all senses, 3D visualization is combined with multi-sensory feedback, 3D printing, robotics in a scientific-artistic-creative environment

Multiple Coordinated Views for Searching and Navigating Web Content Repositories

The advantages and positive effects of multiple coordinated views on search performance have been documented in several studies. This paper describes the implementation of multiple coordinated views within the Media Watch on Climate Change, a domain-specific news aggregation portal available at www.ecoresearch.net/climate that combines a portfolio of semantic services with a visual information exploration and retrieval interface. The system builds contextualized information spaces by enriching the content repository with geospatial, semantic and temporal annotations, and by applying semi-automated ontology learning to create a controlled vocabulary for structuring the stored information. Portlets visualize the different dimensions of the contextualized information spaces, providing the user with multiple views on the latest news media coverage. Context information facilitates access to complex datasets and helps users navigate large repositories of Web documents. Currently, the system synchronizes information landscapes, domain ontologies, geographic maps, tag clouds and just-in-time information retrieval agents that suggest similar topics and nearby locations

A Simulation Environment with Reduced Reality Gap for Testing Autonomous Vehicles

In order to facilitate acceptance and ensure safety, autonomous vehicles must be tested not only in typical and relatively safe scenarios but also in dangerous and less frequent scenarios. Recent pedestrian fatalities caused by test vehicles of the front-running giants like Google and Tesla suffice the fact that Autonomous Vehicle technology is not yet mature enough and still needs rigorous exposure to a wide range of traffic, landscape, and natural conditions on which the Autonomous Vehicles can be trained on to perform as expected in real traffic conditions. Simulation Environments have been considered as an efficient, safe, flexible and cost-effective option for the training, testing, and validation of Autonomous Vehicle technology. While ad-hoc task-specific use of simulation in Autonomous Driving research is widespread, simulation platforms that bridge the gap between simulation and reality are limited. This research proposes to set up a highly realistic simulation environment (using CARLA driving simulator) to generate realistic data to be used for Autonomous Driving research. Our system is able to recreate the original traffic scenarios based on prior information about the traffic scene. Furthermore, the system will allow to make changes to the original scenarios and create various desired testing scenarios by varying the parameters of traffic actors, such as location, trajectory, speed, motion states, etc. and hence collect more data with ease

Métodos de representação virtual e visualização para informação arquitetónica e contextual em sítios arqueológicos

This work seeks to outline some guidelines in order to improve the use of 3D visualization applied to archaeological data of diverse nature and at different scales. One difficulty found in this process is related to the still frequent two-dimensional representation of the three-dimensional archaeological reality. Aware that the existence of data of two-dimensional nature is fundamental in the archaeological process and that they result, on the one hand, from the manual archaeological recording processes and, on the other hand, from the intense analysis and interpretation activity of the archaeological investigation team, we seek to ensure an adequate 3D representation based on 3D acquisition methods mostly available to the archaeology teams. Archaeological visualization in three-dimensional support is an increasingly frequent and necessary practice, but it continues to show some difficulties. These are substantiated in the reduced number of visualization techniques used, the use of visualization tools that are not very customized for the archaeological needs and the privileged use of visual features of the models during the archaeological process phases. Thus, the main objective of this work is to design and evaluate appropriate methods for visualizing archaeological data. To determine which visualization methods are most used during the phases of the archaeological process, an online user-survey was carried out, which allowed consolidating the 3D representation methodologies used, as well as to propose a visualization model that also categorizes the appropriate visualization techniques which increase the visual perception and understanding of the archaeological elements. Three prototypes are defined according to the different 3D data acquisition methodologies presented and visualization methodologies are designed in order to, on the one hand, take into account the scale and diversity of the archaeological elements and, on the other hand, to account for the need to ensure visualization methods which are easily assimilated by archaeologists. Each prototype was evaluated by two archaeologists with different professional background. They were proposed, through a set of previously determined tasks, to assess the interaction with 3D models and with the visualization methods and the satisfaction of the visualization results regarding the archaeological needs. The evaluation of the prototypes allowed to conclude that the presented visualization methods increase the perception of 3D models which represent archaeological elements. In addition, it was also possible to produce new objects that reveal elements of archaeological interest. It is suggested to make these methodologies available on a web-based application and on mobile platforms.Este trabalho procura esboçar algumas diretrizes no sentido de melhorar a utilização da visualização 3D aplicada aos dados arqueológicos de natureza diversa e a escalas distintas. Uma dificuldade encontrada neste processo prende-se com a, ainda frequente, representação bidimensional da realidade arqueológica tridimensional. Ciente de que a existência de dados de natureza bidimensional são fundamentais no processo arqueológico e que resultam, por um lado, dos processos manuais de registo arqueológicos e, por outro, da intensa atividade de análise e interpretação da equipa de investigação arqueológica, procuramos assegurar uma representação 3D adequada, com base em metodologias de aquisição de dados 3D geralmente disponíveis às equipas de arqueologia. A visualização arqueológica em suporte tridimensional é uma prática cada vez mais frequente e necessária, mas que continua a evidenciar algumas dificuldades. Estas substanciam-se no reduzido número de técnicas de visualização usadas, na utilização de ferramentas de visualização pouco adaptadas às necessidades arqueológicas e na utilização preferencial de características visuais dos modelos durante as fases do processo arqueológico. Assim, o objetivo primordial deste trabalho é desenhar e avaliar métodos adequados à visualização de dados arqueológicos. Para determinar que métodos de visualização são mais utilizados durante as fases do processo arqueológico realizou-se um questionário online que permitiu consolidar as metodologias de representação 3D usadas, bem como propor um modelo de visualização que também categoriza as técnicas de visualização adequadas para aumentar a perceção e a compreensão visual dos elementos arqueológicos. Definem-se três protótipos de acordo com as distintas metodologias de aquisição de dados 3D apresentados e são desenhadas metodologias de visualização que, por um lado, têm em conta a escala e a diversidade dos elementos arqueológicos e, por outro, a necessidade de assegurar métodos de visualização facilmente assimilados pelos arqueólogos. Cada protótipo foi avaliado por dois arqueólogos com experiências profissionais distintas. O que lhes foi proposto, através de um conjunto de tarefas previamente estabelecidas, foi aferir da facilidade de interação com os modelos 3D e com os métodos de visualização e adequação dos resultados de visualização às necessidades dos arqueólogos. A avaliação dos protótipos permitiu concluir que os métodos de visualização apresentados aumentam a perceção dos modelos 3D que representam elementos arqueológicos. Para além disso foi possível produzir também novos objetos que revelam elementos com interesse arqueológico. É sugerida a disponibilização destas metodologias em ambiente web e plataformas móveis.Programa Doutoral em Informátic

MxTasks: a novel processing model to support data processing on modern hardware

The hardware landscape has changed rapidly in recent years. Modern hardware in today's servers is characterized by many CPU cores, multiple sockets, and vast amounts of main memory structured in NUMA hierarchies. In order to benefit from these highly parallel systems, the software has to adapt and actively engage with newly available features. However, the processing models forming the foundation for many performance-oriented applications have remained essentially unchanged. Threads, which serve as the central processing abstractions, can be considered a "black box" that hardly allows any transparency between the application and the system underneath. On the one hand, applications are aware of the knowledge that could assist the system in optimizing the execution, such as accessed data objects and access patterns. On the other hand, the limited opportunities for information exchange cause operating systems to make assumptions about the applications' intentions to optimize their execution, e.g., for local data access. Applications, on the contrary, implement optimizations tailored to specific situations, such as sophisticated synchronization mechanisms and hardware-conscious data structures. This work presents MxTasking, a task-based runtime environment that assists the design of data structures and applications for contemporary hardware. MxTasking rethinks the interfaces between performance-oriented applications and the execution substrate, streamlining the information exchange between both layers. By breaking patterns of processing models designed with past generations of hardware in mind, MxTasking creates novel opportunities to manage resources in a hardware- and application-conscious way. Accordingly, we question the granularity of "conventional" threads and show that fine-granular MxTasks are a viable abstraction unit for characterizing and optimizing the execution in a general way. Using various demonstrators in the context of database management systems, we illustrate the practical benefits and explore how challenges like memory access latencies and error-prone synchronization of concurrency can be addressed straightforwardly and effectively

LOCATIVE MEDIA, AUGMENTED REALITIES AND THE ORDINARY AMERICAN LANDSCAPE

This dissertation investigates the role of annotative locative media in mediating experiences of place. The overarching impetus motivating this research is the need to bring to bear the theoretical and substantive concerns of cultural landscape studies on the development of a methodological framework for interrogating the ways in which annotative locative media reconfigure experiences of urban landscapes. I take as my empirical cases i) Google Maps with its associated Street View and locational placemark interface, and ii) Layar, an augmented reality platform combining digital mapping and real-time locational augmentation. In the spirit of landscape studies’ longstanding and renewed interest in what may be termed “ordinary” residential landscapes, and reflecting the increasing imbrication of locative media technologies in everyday lives, the empirical research is based in Kenwick, a middleclass, urban residential neighborhood in Lexington, Kentucky. Overall, I present an argument about the need to consider the digital, code (i.e. software), and specifically locative media, in the intellectual context of critical geographies in general and cultural landscape studies in particular

From Unstructured 3D Point Clouds to Structured Knowledge - A Semantics Approach

International audienc