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Title: Oak Ridge Graph Analytics for Medical Innovation (ORiGAMI)

Abstract

In this era of data-driven decisions and discovery where Big Data is producing Bigger Data, data scientists at the Oak Ridge National Laboratory are leveraging unique leadership infrastructure (e.g., Urika XA and Urika GD appliances) to develop scalable algorithms for semantic, logical and statistical reasoning with Big Data (i.e., data stored in databases as well as unstructured data in documents). ORiGAMI is a next-generation knowledge-discovery framework that is: (a) knowledge nurturing (i.e., evolves seamlessly with newer knowledge and data), (b) smart and curious (i.e. using information-foraging and reasoning algorithms to digest content) and (c) synergistic (i.e., interfaces computers with what they do best to help subject-matter-experts do their best. ORiGAMI has been demonstrated using the National Library of Medicine's SEMANTIC MEDLINE (archive of medical knowledge since 1994).

Authors:
;
Publication Date:
Research Org.:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
Contributing Org.:
Larry W. Roberts, Sreenivas R. Sukumar, Sangkeun (Matt) Lee, Aleksandra Zakrzewska, Katherine Senter, and Jeffrey Graves. I do not have the email addresses for anyone other than Larry Roberts and Sangkeun Lee.
OSTI Identifier:
1340289
Report Number(s):
ORiGAMI; 005124WKSTN00
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Software
Software Revision:
00
Software Package Number:
005124
Software CPU:
WKSTN
Open Source:
Yes
Source Code Available:
Yes
Related Software:
Python libraries (Flask, SPARQLWrapper, solrpy); Apache Jena; ORNL's EAGLE open source code.
Country of Publication:
United States

Citation Formats

Roberts, Larry W., and Lee, Sangkeun. Oak Ridge Graph Analytics for Medical Innovation (ORiGAMI). Computer software. https://www.osti.gov//servlets/purl/1340289. Vers. 00. USDOE. 1 Jan. 2016. Web.
Roberts, Larry W., & Lee, Sangkeun. (2016, January 1). Oak Ridge Graph Analytics for Medical Innovation (ORiGAMI) (Version 00) [Computer software]. https://www.osti.gov//servlets/purl/1340289.
Roberts, Larry W., and Lee, Sangkeun. Oak Ridge Graph Analytics for Medical Innovation (ORiGAMI). Computer software. Version 00. January 1, 2016. https://www.osti.gov//servlets/purl/1340289.
@misc{osti_1340289,
title = {Oak Ridge Graph Analytics for Medical Innovation (ORiGAMI), Version 00},
author = {Roberts, Larry W. and Lee, Sangkeun},
abstractNote = {In this era of data-driven decisions and discovery where Big Data is producing Bigger Data, data scientists at the Oak Ridge National Laboratory are leveraging unique leadership infrastructure (e.g., Urika XA and Urika GD appliances) to develop scalable algorithms for semantic, logical and statistical reasoning with Big Data (i.e., data stored in databases as well as unstructured data in documents). ORiGAMI is a next-generation knowledge-discovery framework that is: (a) knowledge nurturing (i.e., evolves seamlessly with newer knowledge and data), (b) smart and curious (i.e. using information-foraging and reasoning algorithms to digest content) and (c) synergistic (i.e., interfaces computers with what they do best to help subject-matter-experts do their best. ORiGAMI has been demonstrated using the National Library of Medicine's SEMANTIC MEDLINE (archive of medical knowledge since 1994).},
url = {https://www.osti.gov//servlets/purl/1340289},
doi = {},
url = {https://www.osti.gov/biblio/1340289}, year = {Fri Jan 01 00:00:00 EST 2016},
month = {Fri Jan 01 00:00:00 EST 2016},
note =
}