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The EAV/CR framework, designed for database support of rapidly evolving scientific domains, utilizes metadata to facilitate schema maintenance and automatic generation of Web-enabled browsing interfaces to the data.
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The approach taken to build a business rules engine relies heavily on utilizing metadata that exist for application databases.
Our experimental results show promising performance of vision applications with GIFT in terms of lower communication load, improved efficiency, accuracy, and scalability when compared with baseline approaches which do not fully utilize geospatial metadata.
The external programs can utilize the metadata database as follows: (1) make a URL that has a query including the search parameters, (2) search data by GET method in the HTTP protocol, (3) get the search result in the XML format, (4) parse the XML file to obtain the necessary information, and (5) use the information for visualizing and analyzing data.
The technique does not perform decoding, utilize any coding metadata, or assume information about the structure describing the bit stream format of a codec.
The optimizations performed on a complete case study, utilizing the extracted software metadata, achieve overall improvements of up to 42% in the number of cycles spent accessing memory when compared to code optimized only with the static techniques applied by GNU G++.
This is an example of Twitter utilizing the "invisible" carriage of metadata contained in each tweet to truck along extra information.
Our proactive approach to collecting descriptive information seems to be successful, although only time will tell if the community will utilize the full extent of metadata collected.
NCBI offers several different methods to access GEO records, which we utilize to capture all GEO metadata for different GEO data types accordingly.
Our system has been tested on a manually annotated corpus of journal articles related to phylogeography using integrated heuristics for location disambiguation including a distance heuristic, a population heuristic and a novel heuristic utilizing knowledge obtained from GenBank metadata (i.e. a 'metadata heuristic').
For metadata analysis we utilized age groups 20 20-400), 50 (41-60), 80 (61 and older), presence of vascular or heart problems, diabetes, systemic antibiotic use, number of days with wounds at time of evaluation (arbitrarily grouped into <100 days, 100-900, and 901+ days), presence or absence of any type of immobility (e.g. paraplegia or quadriplegia), race, and gender.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com