Entry and access : how shareability comes about

Shareability is a design principle that refers to how a system, interface, or device engages a group of collocated, co-present users in shared interactions around the same content (or the same object). This is broken down in terms of a set of components that facilitate or constrain the way an interface (or product) is made shareable. Central are the notions of access points and entry points. Entry points invite and entice people into engagement, providing an advance overview, minimal barriers, and a honeypot effect that draws observers into the activity. Access points enable users to join a group's activity, allowing perceptual and manipulative access and fluidity of sharing. We show how these terms can be useful for informing analysis and empirical research

Is the writing on the wall for tabletops?

We describe an ethnographic study that explores how low tech and new tech surfaces support participation and collaboration during a workshop breakout session. The low tech surfaces were post-it notes and large sheets of paper. The new tech surfaces were writeable walls and a multi-touch tabletop. Four groups used the different surfaces during three phases: i) brief presentation of position papers and discussion of themes, ii) the creation of a group presentation and iii) a report back session. Participation and collaboration varied depending on the physical, technological and social factors at play when using the different surfaces. We discuss why this is the case, noting how new shareable surfaces may need to be constrained to invite participation in ways that are simply taken for granted because of their familiarity when using low tech materials

Survey of Concurrent Engineering Environments and the Application of Best Practices towards the Development of a Multiple Industry, Multiple Domain Environment

This thesis investigates the best practices of fifteen existing Concurrent Engineering Environments (CEE). A CEE is defined as any environment, from physical to virtual, designed to facilitate concurrent engineering with multiple domain experts real time. All existing environments surveyed have been focused on the aerospace industry showing significant reductions in design time and cost. I have identified hardware, software, and peopleware as three major classifications as well as sixteen subcategories with which to compare the different CEEs. The success in reducing time and cost of designs seen in the aerospace industry with the introduction of CEEs can and should be leveraged into additional domains and industries. This thesis explores the attributes of existing environments, the needs of additional industries, and the recommended concurrent engineering environment configuration appropriate for a multi-industry/multi-domain focus

A mixed reality telepresence system for collaborative space operation

This paper presents a Mixed Reality system that results from the integration of a telepresence system and an application to improve collaborative space exploration. The system combines free viewpoint video with immersive projection technology to support non-verbal communication, including eye gaze, inter-personal distance and facial expression. Importantly, these can be interpreted together as people move around the simulation, maintaining natural social distance. The application is a simulation of Mars, within which the collaborators must come to agreement over, for example, where the Rover should land and go. The first contribution is the creation of a Mixed Reality system supporting contextualization of non-verbal communication. Tw technological contributions are prototyping a technique to subtract a person from a background that may contain physical objects and/or moving images, and a light weight texturing method for multi-view rendering which provides balance in terms of visual and temporal quality. A practical contribution is the demonstration of pragmatic approaches to sharing space between display systems of distinct levels of immersion. A research tool contribution is a system that allows comparison of conventional authored and video based reconstructed avatars, within an environment that encourages exploration and social interaction. Aspects of system quality, including the communication of facial expression and end-to-end latency are reported

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