Understanding Quality in Conceptual Modeling
IEEE Software
IBM computer usability satisfaction questionnaires: psychometric evaluation and instructions for use
International Journal of Human-Computer Interaction
Writing Effective Use Cases
Usability Engineering
Information Retrieval
A Practical Guide to Usability Testing
A Practical Guide to Usability Testing
Current practice in measuring usability: Challenges to usability studies and research
International Journal of Human-Computer Studies
Future Generation Computer Systems
Content-based organisation of virtual repositories of DICOM objects
Future Generation Computer Systems
Enhancing privacy and authorization control scalability in the grid through ontologies
IEEE Transactions on Information Technology in Biomedicine
Methodological Review: Cloud computing: A new business paradigm for biomedical information sharing
Journal of Biomedical Informatics
From infrastructure delivery to service management in clouds
Future Generation Computer Systems
Perspectives on grid computing
Future Generation Computer Systems
Architectural Requirements for Cloud Computing Systems: An Enterprise Cloud Approach
Journal of Grid Computing
e-Infrastructures for e-Science: A Global View
Journal of Grid Computing
Practical Considerations in Cloud Utilization for the Science Gateway nanoHUB.org
UCC '11 Proceedings of the 2011 Fourth IEEE International Conference on Utility and Cloud Computing
Discovering Mammography-based Machine Learning Classifiers for Breast Cancer Diagnosis
Journal of Medical Systems
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Biomedical applications are often built on top of knowledge bases that contain medical images and clinical reports. Currently, these bases are being used to improve diagnosis, research and teaching, but in many cases, the infrastructure required has a prohibitive cost for many medical centres. However, resources can be attached from existing e-Science infrastructures. Therefore, many efforts have been made to establish best practices that allow the use of such infrastructures. However, e-Science relies on open, distributed, collaborative environments, built on top of very specialized technologies, such as Grid and Cloud computing, which require reasonable technical skills for their usage. Therefore, science gateways have become essential tools that assist users in interacting with e-Science applications. This paper describes TRENCADIS, a technology that supports the creation and operation of virtual knowledge bases. To this end, it provides developers with components and APIs for building secure data services that can be annotated and queried through ontology templates, based on DICOM and DICOM-SR. This technology was used in this paper to build a gateway for assisting diagnosis and research in breast cancer. We also present here the results of a study conducted to evaluate the gateway, from the point of view of the usability perceived by a group of physicians and radiologists.