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As more research literature in the biological sciences is made available in electronic format, text mining systems are increasingly being used to improve the ability of investigators to retrieve relevant information. Through the use of advanced indexing techniques that utilize biological ontologies, semantic databases, and other formal representations of biological concepts text mining systems have been able to effectively parse biological literature. While text mining systems are increasingly effective at creating the linkages required to provide context--specific search results, the systems themselves are difficult to set up and use by novice computer users due to the highly technical nature of the applications. Because most researchers in the biological sciences do not have a strong computer science background we have focused on improving the quality of existing, proven text mining systems by implementing a web--based GUI that greatly improves the workflow of these systems. Textpresso in particular has an excellent web--based interface for searching literature but does not have an easy to use administrative interface. We developed the Apellicon interface to enable a wide range of users to build and manage a Textpresso database. An important feature of Apellicon is that it can enable groups to collaborate in building a Textpresso database.

The amount of data that floods toda y 's networks is well be y ond what securit y anal y sts can manage b y textual means alone. In an effort to solve this problem, researchers have explored different methods of visualizing network securit y threats. There is little debate that humans can perceive more information visuall y than textuall y . The problem is that the majorit y of visualization tools in practice or proposed do not take efficient visualization techniques into consideration. As a result, it is difficult to get a high-level view of the network that facilitates rapid isolation of network attacks. We propose the Converged Securit y Visualization Tool (Cover-VT) to solve the efficient visualization problem. Cover-VT was designed to provide anal y sts with a high-level view of network threats using geographic information s y stems. The tool allows for rapid identification of threats b y minimizing the cognitive obstacles to efficient threat location. Cover-VT includes the capabilit y to drill-down on a node of interest for additional details and even filter out unwanted data. Cover-VT was designed with usabilit y in mind, making it eas y to comprehend while assisting the anal y st in rapid threat identification. Man y different securit y tools make up a securit y anal y st'S tool kit. Cover-VT was developed as an effective securit y visualization s y stem that integrates existing securit y tools and network securit y s y stems.

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