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eScience

eScience. Jim Gray Microsoft Research presented @ 21st Century Computing Conference October 2006. eScience: What is it?. Synthesis of information technology and science. Science methods are changing.

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eScience

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  1. eScience Jim Gray Microsoft Research presented @ 21st Century Computing Conference October 2006

  2. eScience: What is it? • Synthesis of information technology and science. • Science methods are changing. • Science is being codified/objectified.How represent scientific knowledge in computers? • Science faces a data deluge.How to manage and analyze information? • Scientific communication changing;integrate online literature and data.

  3. Science Paradigms • Thousand years ago: science was empirical describing natural phenomena • Last few hundred years: theoretical branch using models, generalizations • Last few decades: a computational branch simulating complex phenomena • Today:data exploration (eScience) unify theory, experiment, and simulation • Data captured by instrumentsOr generated by simulator • Processed by software • Information/Knowledge stored in computer • Scientist analyzes datausing data management and statistics

  4. Data Mining Algorithms Miners Scientists Science Data & Questions What X-info Needs from us (cs)(not drawn to scale) Database To Store Data Execute Queries Systems Question & AnswerVisualization Tools

  5. How Engage With An Area • eScience is inter-disciplinary • We bring informatics expertise • Process: • Long-term and deep collaborations • Find someone who is desperate. • Start with requirements: 20 questions • Help build systems to: • Answer those questions much faster • Answer new questions.

  6. Astronomy • Help build world-wide telescope • All astronomy data and literature online and cross indexed • Tools to analyze the data • Built SkyServer.SDSS.org • Built Analysis system • MyDB • CasJobs (batch job) • OpenSkyQueryFederation of ~20 observatories. • Results: • It works and is used every day • Spatial extensions in SQL 2005 • A good example of Data Grid • Good examples of Web Services.

  7. Ecosystem Sensor NetLifeUnderYourFeet.Org • Small sensor net monitoring soil • Sensors feed to a database • Helping build system to collect & organize data. • Working on data analysis tools • Prototype for other LIMSLaboratory Information Management Systems

  8. RNA Structural Genomics • Goal: Predict secondary and tertiary structure from sequence.Deduce tree of life. • Technique: Analyze sequence variations sharing a common structure across tree of life • Representing structurally aligned sequences is a key challenge • Creating a database-driven alignment workbench accessing public and private sequence data

  9. VHA: largest standardized electronic medical records system in US. Design, populate and tune a ~20 TB Data Warehouse and Analytics environment Evaluate population health and treatment outcomes, Support epidemiological studies 7 million enrollees 5 million patients Example Milestones: 1 Billionth Vital Sign loaded in April ‘06 30-minutes to population-wide obesity analysis (next slide) Discovered seasonality in blood pressure -- NEJM fall ‘06 VHA Health Informatics

  10. HDR Vitals Based Body Mass Index Calculation on VHA FY04 Population Source: VHA Corporate Data Warehouse Total Patients 23,876 (0.7%) 701,089 (21.6%) 1,177,093 (36.2%) 1,347,098 (41.5%) 3,249,156 (100%)

  11. Other Projects • Carbon Cycle Portal • Hydrology Portal • Oceanography Workbench

  12. Common Themes • Each science is codifying & objectifying their data and knowledge • What is a galaxy? • What is a molecule? • So that they can • Ask questions of the data • Exchange data with one another • Result will be a Data Grid • Datasets published as “objects” • Service Oriented Architecture

  13. All Scientific Data Online • Many disciplines overlap and use data from other sciences. • Internet can unify all literature and data • Go from literature to computation to data back to literature. • Information at your fingertipsFor everyone-everywhere • Increase Scientific Information Velocity • Huge increase in Science Productivity

  14. Unlocking Peer-Reviewed Literature • Agencies and Foundations mandating research be public domain. • NIH (30 B$/y, 40k PIs,…)(see http://www.taxpayeraccess.org/) • Welcome Trust • Japan, China, Italy, South Africa,.… • Public Library of Science.. • Other agencies will follow NIH

  15. How Does the New Library Work? • Who pays for storage access (unfunded mandate)? • Its cheap: 1 milli-dollar per access • But… curation is not cheap: • Author/Title/Subject/Citation/….. • Dublin Core is great but… • NLM has a 6,000-line XSD for documents http://dtd.nlm.nih.gov/publishing • Need to capture document structure from author • Sections, figures, equations, citations,… • Automate curation • NCBI-PubMedCentral is doing this • Preparing for 1M articles/year • Automate it!

  16. Portable PubMedCentral • “Information at your fingertips” • Helping build PortablePubMedCentral • Deployed US, China, England, Italy, South Africa, (Japan soon). • Each site can accept documents • Archives replicated • Federate thru web services • Working to integrate Word/Excel/…with PubmedCentral – e.g. WordML, XSD, • To be clear: NCBI is doing 99% of the work.

  17. articles Data Sets Overlay Journals • Articles and Data in public archives • Journal title page in public archive. • All covered by Creative Commons License • permits: copy/distribute • requires: attribution http://creativecommons.org/ Data Archives

  18. title page articles Data Sets Overlay Journals • Articles and Data in public archives • Journal title page in public archive. • All covered by Creative Commons License • permits: copy/distribute • requires: attribution http://creativecommons.org/ JournalManagement System Data Archives

  19. title page comments articles Data Sets Overlay Journals • Articles and Data in public archives • Journal title page in public archive. • All covered by Creative Commons License • permits: copy/distribute • requires: attribution http://creativecommons.org/ JournalCollaboration System JournalManagement System Data Archives

  20. Better Authoring Tools • Extend Office tools to • capture document metadata (NLM DTD) • represent documents in standard format • WordML (ECMA standard) • capture references • Make active documents (words and data). • Easier for authors • Easier for archives

  21. Conference Management Tool • Currently a conference peer-review system (~300 conferences) • Form committee • Accept Manuscripts • Declare interest/recuse • Review • Decide • Form program • Notify • Revise

  22. eJournal Management Tool • Connect to Archives • Manage archive document versions • Capture Workshop • presentations • proceedings • Capture classroom ConferenceXP • Moderated discussions of published articles • Connect literature and data archives • Add publishing steps • Form committee • Accept Manuscripts • Declare interest/recuse • Review • Decide • Form program • Notify • Revise • Publish • Discuss & Critique

  23. Why Not a Wiki? • Peer-Review is different • It is very structured • It is moderated • There is a degree of confidentiality • Wiki is egalitarian • It’s a conversation • It’s completely transparent • Don’t get me wrong: • Wiki’s are great • SharePoints are great • But.. Peer-Review is different. • And, incidentally: review of proposals, projects,… is more like peer-review.

  24. eScience: What is it? • Synthesis of information technology and science. • Science methods are changing. • Science is being codified/objectified.How represent scientific information and knowledge in computers? • Science faces a data deluge.How to manage and analyze information? • Scientific communication changingintegrate online literature and data.

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