The MatSeek system is an ontology-based federated search interface to key materials science databases and analytical tools. By combining semantic Web and Web 2.0 technologies, MatSeek provides materials scientists wit...
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The MatSeek system is an ontology-based federated search interface to key materials science databases and analytical tools. By combining semantic Web and Web 2.0 technologies, MatSeek provides materials scientists with a single Web interface that enables them to search across disparate databases containing crystal-structure data, ionic-conductivity data, and phase stability data; render 3D crystal-structure images; calculate bond lengths and angles; retrieve relevant scholarly references; and identify potential new materials with the structure and properties required to satisfy specific applications. The MatOnto ontology underlying MatSeek enables integration of data across disparate databases, and Web 2.0 technologies enable iterative searching across the databases. The results retrieved from searching the previous database are used as input to the query on the next database. By providing materials scientists with a single, integrated Web interface to the critical materials science databases and analytical tools, MatSeek represents a significant advance toward a full-fledged materials-informatics workbench.
Health registries from multiple jurisdictions often include terms that are assumed to be semantically equivalent (e.g. fetal death and stillbirth). Closer examination reveals that such attributes have near - but non-e...
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The ecoinformatics community recognizes that ecological synthesis across studies, space, and time will require new informatics tools and infrastructure. Recent advances have been encouraging, but many problems still f...
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The ecoinformatics community recognizes that ecological synthesis across studies, space, and time will require new informatics tools and infrastructure. Recent advances have been encouraging, but many problems still face ecologists who manage their own datasets, prepare data for archiving, and search data stores for synthetic research. In this paper, we describe how work by the Canopy database Project (CDP) might enable use of database technology by field ecologists: increasing the quality of database design, improving data validation, and providing structural and semantic metadata - all of which might improve the quality of data archives and thereby help drive ecological synthesis. The CDP has experimented with conceptual components for database design, templates, to address information technology issues facing ecologists. Templates represent forest structures and observational measurements on these structures. using our software, researchers select templates to represent their study's data and can generate normalized relational databases. information hidden in those databases is used by ancillary tools, including data intake forms and simple data validation, data visualization, and metadata export. The primary question we address in this paper is, which templates are the right templates. We argue for defining simple templates (with relatively few attributes) that describe the domain's major entities, and for coupling those with focused and flexible observation templates. We present a conceptual model for the observation data type, and show how we have implemented the model as an observation entity in the dataBank database designer and generator. We show how our visualization tool CanopyView exploits metadata made explicit by dataBank to help scientists with analysis and synthesis. We conclude by presenting future plans for tools to conduct statistical calculations common to forest ecology and to enhance data mining with dataBank databases. dataBank could be extend
data analysis in modern biomedical research has to integrate data from different sources, like microarray, clinical and categorical data, so called multi-modal data. The reef SOM, a metaphoric display, is applied and ...
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ISBN:
(纸本)3540388710
data analysis in modern biomedical research has to integrate data from different sources, like microarray, clinical and categorical data, so called multi-modal data. The reef SOM, a metaphoric display, is applied and further improved such that it allows the simultaneous display of biomedical multi-modal data for an exploratory analysis. Visualizations of microarray, clinical, and category data are combined in one informative and entertaining image. The U-matrix of the SOM trained on microarray data is visualized as an underwater sea bed using color and texture. The clinical data and category data are integrated in the form of fish shaped glyphs. The resulting images are intuitive, entertaining and can easily be interpreted by the biomedical collaborator, since specific knowledge about the SOM algorithm is not required. Visual inspection enables the detection of interesting structural patterns in the multi-modal data when browsing through and zooming into the image. Results of such an analysis are presented for the van't Veer data set.
Current trends in the global economy are leading to inter-enterprise interactions and to new business models that depend on the timely notification of events and the reaction to them. In this paper we present a distri...
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The structure of a closely integrated data warehouse is described that is designed to link different types and varying numbers of biological networks, sequence analysis methods and experimental results such as those c...
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Heterogeneous relational databases being integrated vary widely in how the same data is represented. We propose the notion of an ontology extended relation (OER). An OER contains an ordinary relation as well as an ass...
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ISBN:
(纸本)0780382420
Heterogeneous relational databases being integrated vary widely in how the same data is represented. We propose the notion of an ontology extended relation (OER). An OER contains an ordinary relation as well as an associated ontology that conveys semantic meaning about the terms being used. We extend the relational algebra to query OERs. The advantage of this is that the OER model can be directly built on top of commercial relational DBMSs. We describe an implementation of the OER model and show (via experiments) that the system scales to handle large data sets.
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