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Big Data To Knowledge
Big Data to Knowledge (BD2K) is a project of the National Institutes of Health for knowledge extraction from big data Though used sometimes loosely partly because of a lack of formal definition, the interpretation that seems to best describe Big data is the one associated with large body of information that we could not comprehend when used only in smaller am .... BD2K was founded in 2013 in response to a report from the Working Group on Data and Informatics for the Advisory Committee to the Director of the National Institutes of Health. A significant part of BD2K's plans is to have organizations make plans to share their research data when they make a proposal in response to a funding opportunity announcement. Philip Bourne was the lead in managing the project until early 2017. References External links *{{official website, http://datascience.nih.gov/bd2k National Institutes of Health Big data ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
National Institutes Of Health
The National Institutes of Health, commonly referred to as NIH (with each letter pronounced individually), is the primary agency of the United States government responsible for biomedical and public health research. It was founded in the late 1880s and is now part of the United States Department of Health and Human Services. The majority of NIH facilities are located in Bethesda, Maryland, and other nearby suburbs of the Washington metropolitan area, with other primary facilities in the Research Triangle Park in North Carolina and smaller satellite facilities located around the United States. The NIH conducts its own scientific research through the NIH Intramural Research Program (IRP) and provides major biomedical research funding to non-NIH research facilities through its Extramural Research Program. , the IRP had 1,200 principal investigators and more than 4,000 postdoctoral fellows in basic, translational, and clinical research, being the largest biomedical research instit ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Knowledge Extraction
Knowledge extraction is the creation of knowledge from structured (relational databases, XML) and unstructured (text, documents, images) sources. The resulting knowledge needs to be in a machine-readable and machine-interpretable format and must represent knowledge in a manner that facilitates inferencing. Although it is methodically similar to information extraction ( NLP) and ETL (data warehouse), the main criterion is that the extraction result goes beyond the creation of structured information or the transformation into a relational schema. It requires either the reuse of existing formal knowledge (reusing identifiers or ontologies) or the generation of a schema based on the source data. The RDB2RDF W3C group is currently standardizing a language for extraction of resource description frameworks (RDF) from relational databases. Another popular example for knowledge extraction is the transformation of Wikipedia into structured data and also the mapping to existing knowledge ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Big Data
Though used sometimes loosely partly because of a lack of formal definition, the interpretation that seems to best describe Big data is the one associated with large body of information that we could not comprehend when used only in smaller amounts. In it primary definition though, Big data refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many fields (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Big data analysis challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy, and data source. Big data was originally associated with three key concepts: ''volume'', ''variety'', and ''velocity''. The analysis of big data presents challenges in sampling, and thus previously allowing for only observations and sampling. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Philip Bourne
Philip Eric Bourne (born 1953) is an Australian bioinformatician, non-fiction writer, and businessman. He is currently Stephenson Chair of Data Science and Director of the School of Data Science and Professor of Biomedical Engineering and was the first associate director for Data Science at the National Institutes of Health, where his projects include managing the Big Data to Knowledge initiative, and formerly Associate Vice Chancellor at UCSD. He has contributed to textbooks and is a strong supporter of open-access literature and software. His diverse interests have spanned structural biology, medical informatics, information technology, structural bioinformatics, scholarly communication and pharmaceutical sciences. His papers are highly cited, and he has an h-index above 50. Education Bourne was trained as a physical chemist in the mid to late 1970s and obtained his PhD in 1979 at the Flinders University. Career and research After his PhD, Bourne moved to the University of Shef ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
