Perceptual user interface framework for immersive information retrieval environments (An experimental framework for testing and rapid iteration)

The use of perceptual inputs is an emerging area within HCI that suggests a developing Perceptual User Interface (PUI) that may prove advantageous for those involved in mobile serious games and immersive social network environments. Since there are a large variety of input devices, software platforms, possible interactions, and myriad ways to combine all of the above elements in pursuit of a PUI, we propose in this paper a basic experimental framework that will be able to standardize study of the wide range of interactive applications for testing efficacy in learning or information retrieval and also suggest improvements to emerging PUIs by enabling quick iteration. This rapid iteration will start to define a targeted range of interactions that will be intuitive and comfortable as perceptual inputs, and enhance learning and information retention in comparison to traditional GUI systems. The work focuses on the planning of the technical development of two scenarios, and the first steps in developing a framework to evaluate these and other PUIs for efficacy and pedagogy.

Enabling Scientific Workflow Sharing through Coarse-Grained Interoperability

E-scientists want to run their scientific experiments on Distributed Computing Infrastructures (DCI) to be able to access large pools of resources and services. To run experiments on these infrastructures requires specific expertise that e-scientists may not have. Workflows can hide resources and services as a virtualization layer providing a user interface that e-scientists can use. There are many workflow systems used by research communities but they are not interoperable. To learn a workflow system and create workflows in this workflow system may require significant efforts from e-scientists. Considering these efforts it is not reasonable to expect that research communities will learn new workflow systems if they want to run workflows developed in other workflow systems. The solution is to create workflow interoperability solutions to allow workflow sharing. The FP7 Sharing Interoperable Workflow for Large-Scale Scientific Simulation on Available DCIs (SHIWA) project developed two interoperability solutions to support workflow sharing: Coarse-Grained Interoperability (CGI) and Fine-Grained Interoperability (FGI). The project created the SHIWA Simulation Platform (SSP) to implement the Coarse-Grained Interoperability approach as a production-level service for research communities. The paper describes the CGI approach and how it enables sharing and combining existing workflows into complex applications and run them on Distributed Computing Infrastructures. The paper also outlines the architecture, components and usage scenarios of the simulation platform.

Extending Science Gateway Frameworks to Support Big Data Applications in the Cloud

Cloud computing offers massive scalability and elasticity required by many scien-tific and commercial applications. Combining the computational and data handling capabilities of clouds with parallel processing also has the potential to tackle Big Data problems efficiently. Science gateway frameworks and workflow systems enable application developers to implement complex applications and make these available for end-users via simple graphical user interfaces. The integration of such frameworks with Big Data processing tools on the cloud opens new oppor-tunities for application developers. This paper investigates how workflow sys-tems and science gateways can be extended with Big Data processing capabilities. A generic approach based on infrastructure aware workflows is suggested and a proof of concept is implemented based on the WS-PGRADE/gUSE science gateway framework and its integration with the Hadoop parallel data processing solution based on the MapReduce paradigm in the cloud. The provided analysis demonstrates that the methods described to integrate Big Data processing with workflows and science gateways work well in different cloud infrastructures and application scenarios, and can be used to create massively parallel applications for scientific analysis of Big Data.

The user's view level of the GOQL graphical query language

The paper addresses issues related to the design of a graphical query mechanism that can act as an interface to any object-oriented database system (OODBS), in general, and the object model of ODMG 2.0, in particular. In the paper a brief literature survey of related work is given, and an analysis methodology that allows the evaluation of such languages is proposed. Moreover, the user's view level of a new graphical query language, namely GOQL (Graphical Object Query Language), for ODMG 2.0 is presented. The user's view level provides a graphical schema that does not contain any of the perplexing details of an object-oriented database schema, and it also provides a foundation for a graphical interface that can support ad-hoc queries for object-oriented database applications. We illustrate, using an example, the user's view level of GOQL