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Federal Big Data Working Group Meetup:The Yosemite Project: A Roadmap for
Healthcare Information Interoperability and The New Book: Building Ontologies
with Basic Formal OntologyDr. Brand Niemann
Director and Senior Data Scientist/Data JournalistSemantic CommunitySemantic Community
Federal Big Data Working Group MeetupData Science
August 31, 2015
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Agenda
• 6:30 p.m. Welcome and Background (New Tutorial and Mentoring) Slides Data Science for EHRs• 6:40 p.m. David Booth, PhD. HRG and Rancho BioSciences, Slides• 7:30 pm. Brief Member Introductions• 7:40 p.m. Professor Barry Smith, Department of Philosophy - University
at Buffalo New Book: Building Ontologies with Basic Formal Ontology Slides• 8:30 p.m. Open Discussion• 8:45 p.m. Networking• 9:00 p.m. Depart
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Schedule
• August 25th, Introduction to the American Community Survey Webinar (2-3 PM EST). http://www.census.gov/mso/www/training/ (See October 5th Meetup Below)
• September 1st, Data Science for EPA Hydraulic Fracturing Webinar.• September 14th, Big Data Science for Precision Farming Business Online Course.• September 16-17th, Building Ontologies with Basic Formal Ontology, Barry Smith• September 28th, Climate Change Data - Data Science Meetup of Meetups.• October 5th, Data Science for Census American Community Survey.• October 19th, Sensing Our Air: The Quest for Big Data About Our Air Quality.• November 2nd, Data Science for Random Forests• November 5-6th, OSTP/NSF Data Science Meetup of Meetups, Ballston, VA.• November 16th, Data Science for the DataAct Datathon• December 7th, TBA
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Background
• David Booth, PhD. HRG and Rancho BioSciences, The Yosemite Project. Slides 5-6.• Barry Smith, Professor of Philosophy and Co-Author of New Book on Ontology, Meeting
with Intelligence Community. Slides 7-11.• Jonathan Hines, ORNL science writer, doing a story on Semantic Medline and the ORNL
CADES – Compute and Data Environment for Science. Slides 12-15.• Joan Aron and Brand Niemann, Data Mining - Science - Questions - Publication Process.
Slides 16-28.• Weifeng Li (Lexie) and Brand Niemann, FDA Precision Medicine, Slides 29-32.• Chris Crawford and Jay Patkar, TIBCO Software Federal, Random Forests for Kaggle
Competitions and Spotfire TERR. November 2nd.• Steve Hanmer, Mission Source, Allyson Ugarte, Treasury, co-planning Data Science for Data
Act Datathon Meetup. He attended the Data Act Datathon and Forum this week and will report. November 16th.
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About the Yosemite Project
• The Yosemite Project is a collaborative effort to achieve semantic interoperability of all structured healthcare information, using RDF as a universal information representation. It is a follow-up to the Yosemite Manifesto -- a position statement issued by participants of the 2013 workshop on RDF as a Universal Healthcare Exchange Language, held at the Semantic Technology and Business Conference, in response to the 2010 PCAST report's call for a universal exchange language for healthcare information. The Yosemite Manifesto identifies RDF as the "best available candidate" to meet this need, and has been signed by over 100 healthcare and technology experts since it was issued. Add your name!
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https://mitpress.mit.edu/index.php?q=books/building-ontologies-basic-formal-ontology
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Building Ontologies with Basic Formal Ontology:Table of Contents
• Introduction• 1 What Is an Ontology?• 2 Kinds of Ontologies and the Role of Taxonomies• 3 Principles of Best Practice I: Domain Ontology Design• 4 Principles of Best Practice II: Terms, Definitions, and Classification• 5 Introduction to Basic Formal Ontology I: Continuants• 6 Introduction to Basic Formal Ontology II: Occurrents• 7 The Ontology of Relations• 8 Basic Formal Ontology at Work• Appendix on Implementation: Languages, Editors, Reasoners, Browsers, Tools for Reuse• Glossary• Web Links Mentioned in the Text• Notes• Bibliography
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Building Ontologies with Basic Formal OntologyBy Robert Arp, Barry Smith and Andrew D. Spear
• In the era of “big data,” science is increasingly information driven, and the potential for computers to store, manage, and integrate massive amounts of data has given rise to such new disciplinary fields as biomedical informatics. Applied ontology offers a strategy for the organization of scientific information in computer-tractable form, drawing on concepts not only from computer and information science but also from linguistics, logic, and philosophy. This book provides an introduction to the field of applied ontology that is of particular relevance to biomedicine, covering theoretical components of ontologies, best practices for ontology design, and examples of biomedical ontologies in use.
• After defining an ontology as a representation of the types of entities in a given domain, the book distinguishes between different kinds of ontologies and taxonomies, and shows how applied ontology draws on more traditional ideas from metaphysics. It presents the core features of the Basic Formal Ontology (BFO), now used by over one hundred ontology projects around the world, and offers examples of domain ontologies that utilize BFO. The book also describes Web Ontology Language (OWL), a common framework for Semantic Web technologies. Throughout, the book provides concrete recommendations for the design and construction of domain ontologies.
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http://skr3.nlm.nih.gov/SemMed2/
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NIH Data Commons
• FAIR Principles:• Findable• Accessible• Interoperable• Reusable
• Cloud:• Data• Software• Results
• Federal Science Policy:• OSTP Public Access to Scientific Data
Memo (February 2013)• New Program: Big-Data-to-
Knowledge (2013)• New Position: Associate Director of
Data Science (2014)• Digital Enterprise (2015): Data
Commons• Metadata• Open APIs• Digital Objects• Containers
A NIH – Semantic Medline Data Science Data Publication Commons
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OSTP/NSF Data Science Meetup of Meetups
• Week of November 2nd:• NSF Data Science/Big Data
Principal Investigators (About 300)• NSF Data Hubs (4)• Organizers of Largest Data
Science/Big Data Meetups (About 65)
• Pipeline for Return on Investment:• PIs put their data, tools and
research results in the Data Hubs• Data Hubs provide those data,
tools, and research results to the world, but especially to the Data Science/Big Data Meetups• Data Science/Big Data Meetups
collaborate with PIs and Data Hubs to increase usage and feedback
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We Already Do This!
• Semantic Community:• Provides a Community Sandbox that is
like a GitHub, Data Hub, Data Commons, etc.• Metadata (MindTouch)• Open APIs (MIndTouch)• Digital Objects (MindTouch)• Containers (Spotfire)
• Organize the Federal Big Data Working Group Meetup
• Support Agencies and Programs in Crowdsourcing Their Data Sets
• Mentor Data Scientists (Tutorials and MOOCs) and Entrepreneurs (Eastern Foundry)
• Federal Big Data Working Group Meetup:• Federal: Supports the Federal Big Data
Initiative, but not endorsed by the Federal Government or its Agencies;
• Big Data: Supports the Federal Digital Government Strategy which is "treating all content as data", so big data = all your content;
• Working Group: Data Science Teams composed of Federal Government and Non-Federal Government experts producing big data products; and
• Meetup: The world's largest network of local groups to revitalize local community and help people around the world self-organize like MOOCs (Massive Open On-line Classes) now embraced by the White House.
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Data Mining - Science - Questions - Publication Process
• Data Mining Process:• Business Understanding• Data Understanding• Data Preparation• Modeling• Evaluation• Deployment
• Data Science Process:• Data Preparation• Data Ecosystem• Data Story
• Data Science Questions:• How was the data collected?• Where is the data stored?• What are the data results? and• Why should we believe the data results?
• Data Science Data Publication:• Knowledge Base• Spreadsheet Index• Web & PDF Tables to Spreadsheet• Data Browser• Dynamically Linked Adjacent
Visualizations
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Data Science Data Curation for Sustainable Data Science Meetups
of Meetups• I just finished four data science ecosystems:• RDA Climate Data Challenge (July 15):
• http://semanticommunity.info/Data_Science/Data_Science_for_RDA_Climate_Change_Data_Challenge
• RDA Information Week 2016 (Ebola Response and Nepal Earthquake) (July 17):• http
://semanticommunity.info/Data_Science/Data_Science_for_Global_Ebola_Response_Data
• USDA Microsoft Innovation Challenge (July 27):• http://semanticommunity.info/Data_Science/Big_Data_Science_for_Precision_Farming_
Business#Story• US Data Act (July 28):
• http://semanticommunity.info/Data_Science/Data_Science_for_the_DataAct_Datathon
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Collaboration for Data Science Win-Wins
• USDA Open Government Data Training, Innovation Competition, and Online Course in Data-Driven Farming:• http
://semanticommunity.info/Data_Science/Big_Data_Science_for_Precision_Farming_Business#Story
• Many Curated Government Data Sets and Data Science Products:• http://semanticommunity.info
• Pick an Agency and/or a Data Set and Look for a Meetup on That:• http://www.meetup.com/Federal-Big-Data-Working-Group/
• Mentor Startups Partnership with Eastern Foundry:• http://www.meetup.com/Federal-Big-Data-Working-Group/events/223140032/
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USDA Collaboration Chronology
• March 16th: USDA CIO and ACDO on Open Data Plan and Roundtable Meetup• March 25th: Government Technology & Innovation Incubator for Big Data Analytics II Meetup at
Eastern Foundry• May 18th: USDA Data Science MOOC Meetup• May 21st, USDA Open Data Quarterly Submission to OMB on USDA Data Usage provided (USDA Data
Science MOOC)• July 21st, Data-Driven Farming Online Course Announced by HeatSpring and Semantic Community• July 27th: USDA Microsoft Innovation Challenge Submission on Farm Data Dashboards• July 29th, Partnerships Sought for Data-Driven Farming Online Course• August 19, 2015, Data Science for USDA Big Data, Briefing and Demo• September 17th: Big Data Science for Precision Farming Business Online Course Meetup and
Commercial Examples: Farmers Business Network, FarmLogs, etc.• October 26-December 18th, Data-Driven Farming Online Course with Partners
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http://www.opendataenterprise.org/map/viz/index.html
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http://www.opendataenterprise.org/map/viz/index.html
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Agriculture:Data Type: 8 PagesIndustry Category: 3 Pages
http://www.opendataenterprise.org/map/viz/index.html
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FDA Mission
• FDA plays an integral role in President Obama’s Precision Medicine Initiative, which foresees the day when an individual’s medical care will be tailored in part based on their unique characteristics and genetic make-up. Yet while more than 80 million genetic variants have been found in the human genome, we don’t understand the role that most of these variants play in health or disease.• The FDA, an agency within the U.S. Department of Health and Human Services,
protects the public health by assuring the safety, effectiveness, and security of human and veterinary drugs, vaccines and other biological products for human use, and medical devices. The agency also is responsible for the safety and security of our nation’s food supply, cosmetics, dietary supplements, products that give off electronic radiation, and for regulating tobacco products.
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precisionFDA
• Planned for beta release (work in progress) in December 2015, precisionFDA will offer community members access to secure and independent work areas where, at their discretion, their software code or data can either be kept private, or shared with the owner’s choice of collaborators, FDA, or the public. Initially, precisionFDA’s public space will offer a wiki and a set of open source or open access reference genomic data models and analysis tools developed and vetted by standards bodies, such as the National Institute of Standards and Technology (e.g., Genome in a Bottle). We believe precisionFDA will help us advance the science around the accuracy and reproducibility of NGS-based tests, and in doing so, will advance consumer safety. We look forward to continuing to update the community on the development of these new tools.http://blogs.fda.gov/fdavoice/index.php/2015/08/advancing-precision-medicine-by-enabling-a-collaborative-informatics-community/
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Previous FDA-Related Meetups
• July 7, 2014: Data Science of White House Big Data Review and Brooke Aker: Big Data Lens on OpenFDA• http://www.meetup.com/Federal-Big-Data-Working-Group/events/192336492/
• October 6, 2014: FDA Data Innovation Lab and Predictive Analytics• http://www.meetup.com/Federal-Big-Data-Working-Group/events/209068792/
• December 1, 2014: Data Science for NIH/FDA SEMOSS Data Federation and Analytics• http://www.meetup.com/Federal-Big-Data-Working-Group/events/210542792/
• April 6, 2015: Data Science for the FDA RFI• http://www.meetup.com/Federal-Big-Data-Working-Group/events/219374810/
