Interactive access and management for four-dimensional environmental data sets using McIDAS

Significant accomplishments in the past year are presented and include the following: (1) enhancements to VIS-5D; (2) Implementation of the VIS AD System; and (3) numerical modeling applications. Focus of current research and plans for next year in the following areas are briefly discussed: (1) continued development and application of the VIS-AD system; (2) further enhancements to VIS-5D; and (3) plans for modeling applications

Ewé: a web-based ethnobotanical database for storing and analysing data

Ethnobotanical databases serve as repositories of traditional knowledge (TK), either at international or local scales. By documenting plant species with traditional use, and most importantly, the applications and modes of use of such species, ethnobotanical databases play a role in the conservation of TK and also provide access to information that could improve hypothesis generation and testing in ethnobotanical studies. Brazil has a rich medicinal flora and a rich cultural landscape. Nevertheless, cultural change and ecological degradation can lead to loss of TK. Here, we present an online database developed with open-source tools with a capacity to include all medicinal flora of Brazil. We present test data for the Leguminosae comprising a total of 2078 records, referred to here as use reports, including data compiled from literature and herbarium sources. Unlike existing databases, Ewé provides tools for the visualization of large datasets, facilitating hypothesis generation and meta-analyses. The Ewé database is currently available at www.ewedb.com

SenseCluster for exploring large data repositories

Exploring and making sense of large data repositories has become a daunting task. This is especially the case for end users who often have limited access to the data due to the complexity of the retrieval process and limited availability of IT support for developing custom queries and reports based on the data. Consequently, traditional interfaces are no longer meeting these requirements. Instead, novel interfaces are required to fully support the sense making process. In this paper, we followed a design science approach and introduced a query clustering system (Sense Cluster) that could serve as a quick exploration tool for making better sense of large data repositories. We also present an evaluation of the effectiveness of our artifact using cognitive walkthroughs

Supporting Information Visualization Through Topic Maps

We are living a phenomenon of accelerated information production with different accessing sources. Hence users are faced with a growing problem: accessing (navigation) and filtering specific information contained in large datasets, which are increasing in size. Procedures such as data filtering and gathering are now simplified through a new concept known as Topic Maps. The application of Virtual Reality technologies enables to present and interact with multidimensional information in a 3D space. In this paper we present INSPHERE, a new visual metaphor for information visualization, based on both, Virtual Reality techniques, and “geographical information maps” provided by Topic Maps

Information visualization approach in marine fisheries landing data

This paper studied the landings statistical data in marine fisheries by the state of Terengganu for the period of time 2000 until 2009 and to discuss some of the main features on how information visualization technique can be used as a keystone technology for represent these fisheries data. Information visualization (InfoVis) represents an abstract data in graphical representation concepts in such a way that is more natural or easier for human to comprehend. InfoVis is recognized as one of the important way to help users to study, explore, and present information in fisheries data. Today, this emerging technology is important in fisheries and plays a vital role in developing integrated approaches to fishery management and assessment. It helps to convey relatively complex technical information to scientists, managers and decision makers. Since visualization technology provide a high degree of functionality in sampling design, data assimilation, exploratory data analysis and model development, they will continue to play an increasing significant strategic role in fishery management and assessment

Creating and understanding email communication networks to aid digital forensic investigations

Digital forensic analysts depend on the ability to understand the social networks of the individuals they investigate. We develop a novel method for automatically constructing these networks from collected hard drives. We accomplish this by scanning the raw storage media for email addresses, constructing co-reference networks based on the proximity of email addresses to each other, then selecting connected components that correspond to real communication networks. We validate our analysis against a tagged data-set of networks for which we determined ground truth through interviews with the drive owners. In the resulting social networks, we find that classical measures of centrality and community detection algorithms are effective for identifying important nodes and close associates

VisualDecisionLinc: A visual analytics approach for comparative effectiveness-based clinical decision support in psychiatry

Comparative Effectiveness Research (CER) is designed to provide research evidence on the effectiveness and risks of different therapeutic options on the basis of data compiled from subpopulations of patients with similar medical conditions. Electronic Health Record (EHR) system contain large volumes of patient data that could be used for CER, but the data contained in EHR system are typically accessible only in formats that are not conducive to rapid synthesis and interpretation of therapeutic outcomes. In the time-pressured clinical setting, clinicians faced with large amounts of patient data in formats that are not readily interpretable often feel 'information overload'. Decision support tools that enable rapid access at the point of care to aggregate data on the most effective therapeutic outcomes derived from CER would greatly aid the clinical decision-making process and individualize patient care. In this manuscript, we highlight the role that visual analytics can play in CER-based clinical decision support. We developed a 'VisualDecisionLinc' (VDL) tool prototype that uses visual analytics to provide summarized CER-derived data views to facilitate rapid interpretation of large amounts of data. We highlight the flexibility that visual analytics offers to gain an overview of therapeutic options and outcomes and if needed, to instantly customize the evidence to the needs of the patient or clinician. The VDL tool uses visual analytics to help the clinician evaluate and understand the effectiveness and risk of different therapeutic options for different subpopulations of patients

Analysis of biomedical data with multilevel glyphs

BACKGROUND: This paper presents multilevel data glyphs optimized for the interactive knowledge discovery and visualization of large biomedical data sets. Data glyphs are three- dimensional objects defined by multiple levels of geometric descriptions (levels of detail) combined with a mapping of data attributes to graphical elements and methods, which specify their spatial position. METHODS: In the data mapping phase, which is done by a biomedical expert, meta information about the data attributes (scale, number of distinct values) are compared with the visual capabilities of the graphical elements in order to give a feedback to the user about the correctness of the variable mapping. The spatial arrangement of glyphs is done in a dimetric view, which leads to high data density, a simplified 3D navigation and avoids perspective distortion. RESULTS: We show the usage of data glyphs in the disease analyser a visual analytics application for personalized medicine and provide an outlook to a biomedical web visualization scenario. CONCLUSIONS: Data glyphs can be successfully applied in the disease analyser for the analysis of big medical data sets. Especially the automatic validation of the data mapping, selection of subgroups within histograms and the visual comparison of the value distributions were seen by experts as an important functionality