eScience -- A Transformed Scientific Method"

Slides:



Advertisements
Similar presentations
Microsoft Research Microsoft Research Jim Gray Distinguished Engineer Microsoft Research San Francisco SKYSERVER.
Advertisements

Trying to Use Databases for Science Jim Gray Microsoft Research
Online Science -- The World-Wide Telescope Archetype
World Wide Telescope mining the Sky using Web Services Information At Your Fingertips for astronomers Jim Gray Microsoft Research Alex Szalay Johns Hopkins.
1 Online Science the New Computational Science Jim Gray Microsoft Research Alex Szalay Johns Hopkins.
1 Online Science The World-Wide Telescope as a Prototype For the New Computational Science Jim Gray Microsoft Research Talk at
1 Online Science -- The World-Wide Telescope as an Archetype Jim Gray Microsoft Research Collaborating with: Alex Szalay, Peter Kunszt, Ani
1 Online Science The World-Wide Telescope as a Prototype For the New Computational Science Jim Gray Microsoft Research
Online Science The World-Wide Telescope as a Prototype For the New Computational Science Jim Gray Microsoft Research
1 Online Science The World-Wide Telescope as a Prototype For the New Computational Science Jim Gray Microsoft Research
The Australian Virtual Observatory e-Science Meeting School of Physics, March 2003 David Barnes.
Astronomy Data Bases Jim Gray Microsoft Research.
The Data Lifecycle and the Curation of Laboratory Experimental Data Tony Hey Corporate VP for Technical Computing Microsoft Corporation.
C van Ingen, D Agarwal, M Goode, J Gupchup, J Hunt, R Leonardson, M Rodriguez, N Li Berkeley Water Center John Hopkins University Lawrence Berkeley Laboratory.
14 October 2003ADASS 2003 – Strasbourg1 Resource Registries for the Virtual Observatory R.Plante (NCSA), G. Greene (STScI), R. Hanisch (STScI), T. McGlynn.
Virtual Observatory & Grid Technique ZHAO Yongheng (National Astronomical Observatories of China) CANS2002.
EPrints Workshop, January eBank UK: Dissemination of research data using EPrints Simon Coles, School of Chemistry, University of Southampton.
Long-Term Preservation of Astronomical Research Results Robert Hanisch US National Virtual Observatory Space Telescope Science Institute Baltimore, MD.
A Web service for Distributed Covariance Computation on Astronomy Catalogs Presented by Haimonti Dutta CMSC 691D.
William Y. Arms Corporation for National Research Initiatives March 22, 1999 Object models, overlay journals, and virtual collections.
Long-Term Preservation of Astronomical Research Results Robert Hanisch US National Virtual Observatory Space Telescope Science Institute Baltimore, MD.
LÊ QU Ố C HUY ID: QLU OUTLINE  What is data mining ?  Major issues in data mining 2.
1 Where The Rubber Meets the Sky Giving Access to Science Data Jim Gray Microsoft Research Alex.
A long tradition. e-science, Data Centres, and the Virtual Observatory why is e-science important ? what is the structure of the VO ? what then must we.
Supported by the National Science Foundation’s Information Technology Research Program under Cooperative Agreement AST with The Johns Hopkins University.
Alex Szalay, Jim Gray Analyzing Large Data Sets in Astronomy.
Functions and Demo of Astrogrid 1.1 China-VO Haijun Tian.
Astronomical data curation and the Wide-Field Astronomy Unit Bob Mann Wide-Field Astronomy Unit Institute for Astronomy School of Physics University of.
Science with the Virtual Observatory Brian R. Kent NRAO.
1 Managing Data for the World Wide Telescope aka: The Virtual Observatory Jim Gray Alex Szalay SLAC Data Management Workshop.
1 The World Wide Telescope an Archetype for Online-Science Jim Gray (Microsoft) Alex Szalay (Johns Hopkins University) Microsoft Academic Days in Silicon.
Metadata and Geographical Information Systems Adrian Moss KINDS project, Manchester Metropolitan University, UK
1 Where The Rubber Meets the Sky Giving Access to Science Data Talk at National Institute of Informatics, Tokyo, Japan October 2005 Jim Gray Microsoft.
Public Access to Large Astronomical Datasets Alex Szalay, Johns Hopkins Jim Gray, Microsoft Research.
What is Cyberinfrastructure? Russ Hobby, Internet2 Clemson University CI Days 20 May 2008.
Wenjing Wu Computer Center, Institute of High Energy Physics Chinese Academy of Sciences, Beijing BOINC workshop 2013.
Fourth Paradigm Science-based on Data-intensive Computing.
The Data Avalanche Jim Gray Microsoft Research Talk at HP Labs/MSR: Research Day July 2004.
Federation and Fusion of astronomical information Daniel Egret & Françoise Genova, CDS, Strasbourg Standards and tools for the Virtual Observatories.
Wiss. Beirat AIP, ClusterFinder & VO-Methods H. Enke German Astrophysical Virtual Observatory ClusterFinder VO Methods for Astronomical Applications.
2007. Software Engineering Laboratory, School of Computer Science S E Web-Harvest Web-Harvest: Open Source Web Data Extraction tool 이재정 Software Engineering.
NVO Review -- San Diego Jan The VO compared to Other O‘s Jim Gray Microsoft T HE US N ATIONAL V IRTUAL O BSERVATORY.
Some Grid Science California Institute of Technology Roy Williams Paul Messina Grids and Virtual Observatory Grids and and LIGO.
Cyberinfrastructure What is it? Russ Hobby Internet2 Joint Techs, 18 July 2007.
Sky Survey Database Design National e-Science Centre Edinburgh 8 April 2003.
The International Virtual Observatory Alliance (IVOA) interoperability in action.
Data Archives: Migration and Maintenance Douglas J. Mink Telescope Data Center Smithsonian Astrophysical Observatory NSF
Real Web Services Jim Gray Microsoft Research 455 Market St, SF, CA, Talk at Charles Schwab.
Pan-STARRS PS1 Published Science Products Subsystem Presentation to the PS1 Science Council August 1, 2007.
Cyberinfrastructure Overview Russ Hobby, Internet2 ECSU CI Days 4 January 2008.
1 Online Science The World-Wide Telescope as a Prototype For the New Computational Science Jim Gray Microsoft Research
Microsoft “information at your fingertips” for scientists Collaborating with Scientists to build better ways to organize, analyze, and understand.
Entering the Data Era; Digital Curation of Data-intensive Science…… and the role Publishers can play The STM view on publishing datasets Bloomsbury Conference.
CombeDay Making Data Openly Available Simon Coles.
1 Where The Rubber Meets the Sky Giving Access to Science Data Jim Gray Microsoft Research Alex.
Distributed Archives Interoperability Cynthia Y. Cheung NASA Goddard Space Flight Center IAU 2000 Commission 5 Manchester, UK August 12, 2000.
Visual Knowledge ® Software Inc. Visual Knowledge BioCAD Case Study Parallels to Other Domains VK Semantic Web Server.
Microsoft Research San Francisco (aka BARC: bay area research center) Jim Gray Researcher Microsoft Research Scalable servers Scalable servers Collaboration.
HELIO: Discovery and Analysis of Data in Heliophysics Robert Bentley, John Brooke, André Csillaghy, Donal Fellows, Anja Le Blanc, Mauro Messerotti, David.
There is an inherent meaning in everything. “Signs for people who can see.”
Enhancements to Galaxy for delivering on NIH Commons
e-Science and Cyberinfrastructure
Online Science The World-Wide Telescope as a Prototype For the New Computational Science Jim Gray Microsoft Research
Jim Gray Alex Szalay SLAC Data Management Workshop
BARC Scaleable Servers
Rick, the SkyServer is a website we built to make it easy for professional and armature astronomers to access the terabytes of data gathered by the Sloan.
Data Warehousing and Data Mining
Jim Gray Researcher Microsoft Research
Jim Gray Microsoft Research
Google Sky.
Presentation transcript:

eScience -- A Transformed Scientific Method" Jim Gray, eScience Group, Microsoft Research http://research.microsoft.com/~Gray

Outline What’s Computer Science? What Do I do? eScience? What’s that? Peer-Reviewed Literature and Data online? How would that work?

What’s Computer Science We have the patent on: the byte (aka information) the algorithm (aka process) This covers just about everything interesting Music is software Literature is software Life is just software DNA is information Metabolism is a process It’s digital

What’s Science Pasteur’s Quadrant Einstein Pasteur Anti-Intellectual Edison Theoretical Practical

The Scholarly Life Applies to science, engineering, medicine, law, philosophy, art,..

An Amazing Thing Intellectual property is property (has value) Cyberspace is Real Estate! Columbus discovered a New World lots of new real estate CyberSpace is a new world EverQuest and Second Life and … And … Windows, Office, Google, …. And music and medicine and …. A $ invested in research pays off 10x or more in NEW IDEAS.

Outline What’s Computer Science? What Do I do? eScience? What’s that? Peer-Reviewed Literature and Data online? How would that work?

What I Do Meditation Service Teaching Inventing new ways to organize data Inventing new ways to search data Using scientific data as the vehicle (eScience) Service Serve on government boards Professional societies Trying to help scientists Trying to get scientific literature and data online Teaching here I am  Advise students Mentor (younger) colleagues

Outline What’s Computer Science? What Do I do? eScience? What’s that? Peer-Reviewed Literature and Data online? How would that work?

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 changing. 10

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 instruments Or generated by simulator Processed by software Information/Knowledge stored in computer Scientist analyzes database / files using data management and statistics 11

X-Info ? The evolution of X-Info and Comp-X for each discipline X How to codify and represent our knowledge Experiments & Instruments Simulations facts answers questions Literature Other Archives ? The Generic Problems Data ingest Managing a petabyte Common schema How to organize it How to reorganize it How to coexist with others Query and Vis tools Building and executing models Integrating data and Literature Support/training Performance

Experiment Budgets ¼…½ Software Millions of lines of code Repeated for experiment after experiment Not much sharing or learning CS can change this Build generic tools Workflow schedulers Databases and libraries Analysis packages Visualizers … Software for Instrument scheduling Instrument control Data gathering Data reduction Database Analysis Modeling Visualization

New Approaches to Data Analysis Looking for Needles in haystacks – the Higgs particle Haystacks: Dark matter, Dark energy Needles are easier than haystacks Global statistics have poor scaling Correlation functions are N2, likelihood techniques N3 As data and computers grow at same rate, we can only keep up with N logN A way out? Discard notion of optimal (data is fuzzy, answers are approximate) Don’t assume infinite computational resources or memory Requires combination of statistics & computer science

Analysis and Databases Much statistical analysis deals with Creating uniform samples – data filtering Assembling relevant subsets Estimating completeness Censoring bad data Counting and building histograms Generating Monte-Carlo subsets Likelihood calculations Hypothesis testing Traditionally these are performed on files Most of these tasks are much better done inside a database Move Mohamed to the mountain, not the mountain to Mohamed.

Outline What’s Computer Science? What Do I do? eScience? What’s that? Peer-Reviewed Literature and Data online? How would that work?

Peer-Reviewed Science Literature Is Coming Online Agencies and Foundations mandating research be public domain. NIH (30 B$/y, 40k PIs,…) (see http://www.taxpayeraccess.org/) Wellcome Trust Japan, China, Italy, South Africa,.… Public Library of Science.. Other agencies will follow NIH Publishers will resist (not surprising) Professional societies will resist (amazing!)

Pub Med Central International “Information at your fingertips” Deployed US, China, England, Italy, South Africa, Japan (not public on Internet yet) 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.

Peer Review Currently support a conference peer-review system (~300 conferences) Form committee Accept Manuscripts Declare interest/recuse Review Decide Form program Notify Revise

Publishing Peer Review Add publishing steps Form committee Accept Manuscripts Declare interest/recuse Review Decide Form program Notify Revise Publish & improve author-reader experience Manage versions Capture data Interactive documents Capture Workshop presentations proceedings Capture classroom ConferenceXP Moderated discussions of published articles Connect to Archives

So… What about Publishing Data? The answer is 42. But… What are the units? How precise? How accurate 42.5 ± .01 Show your work data provenance

Thought Experiment You have collected some data and want to publish science based on it. How do you publish the data so that others can read it and reproduce your results in 100 years? Document collection process? How document data processing (scrubbing & reducing the data)? Where do you put it?

Objectifying Knowledge This requires agreement about Units: cgs Measurements: who/what/when/where/how CONCEPTS: What’s a planet, star, galaxy,…? What’s a gene, protein, pathway…? Need to objectify science: what are the objects? what are the attributes? What are the methods (in the OO sense)? This is mostly Physics/Bio/Eco/Econ/... But CS can do generic things

Objectifying Knowledge This requires agreement about Units: cgs Measurements: who/what/when/where/how CONCEPTS: What’s a planet, star, galaxy,…? What’s a gene, protein, pathway…? Need to objectify science: what are the objects? what are the attributes? What are the methods (in the OO sense)? This is mostly Physics/Bio/Eco/Econ/... But CS can do generic things Warning! Painful discussions ahead: The “O” word: Ontology The “S” word: Schema The “CV” words: Controlled Vocabulary Domain experts do not agree

The Best Example: Entrez-GenBank http://www.ncbi.nlm.nih.gov/ Sequence data deposited with Genbank Literature references Genbank ID BLAST searches Genbank Entrez integrates and searches PubMedCentral PubChem Genbank Proteins, SNP, Structure,.. Taxonomy… Many more Nucleotide sequences Protein sequences Taxon Phylogeny MMDB 3 -D Structure PubMed abstracts Complete Genomes PubMed Entrez Genomes Publishers Genome Centers

The Vision: Global Data Federation Massive datasets live near their owners: Near the instrument’s software pipeline Near the applications Near data knowledge and curation Each Archive publishes a (web) service Schema: documents the data Methods on objects (queries) Scientists get “personalized” extracts Uniform access to multiple Archives A common global schema Federation

Web Services: Enable Federation Your program Web Server http Web page Web SERVER: Given a url + parameters Returns a web page (often dynamic) Web SERVICE: Given a XML document (soap msg) Returns an XML document Tools make this look like an RPC. F(x,y,z) returns (u, v, w) Distributed objects for the web. + naming, discovery, security,.. Internet-scale distributed computing Now: Find object models for each science. Your program Data In your address space Web Service soap object in xml

Outline What’s Computer Science? What Do I do? eScience? What’s that? Peer-Reviewed Literature and Data online? How would that work? And give an example 

World Wide Telescope Virtual Observatory http://www. us-vo Premise: Most data is (or could be online) So, the Internet is the world’s best telescope: It has data on every part of the sky In every measured spectral band: optical, x-ray, radio.. As deep as the best instruments (2 years ago). It is up when you are up. The “seeing” is always great (no working at night, no clouds no moons no..). It’s a smart telescope: links objects and data to literature on them.

Why Astronomy Data? It has no commercial value IRAS 25m It has no commercial value No privacy concerns Can freely share results with others Great for experimenting with algorithms It is real and well documented High-dimensional data (with confidence intervals) Spatial data Temporal data Many different instruments from many different places and many different times Federation is a goal There is a lot of it (petabytes) 2MASS 2m DSS Optical IRAS 100m WENSS 92cm NVSS 20cm GB 6cm ROSAT ~keV

Time and Spectral Dimensions The Multiwavelength Crab Nebulae Crab star 1053 AD X-ray, optical, infrared, and radio views of the nearby Crab Nebula, which is now in a state of chaotic expansion after a supernova explosion first sighted in 1054 A.D. by Chinese Astronomers. Slide courtesy of Robert Brunner @ CalTech.

SkyServer.SDSS.org A modern archive Also used for education Access to Sloan Digital Sky Survey Spectroscopic and Optical surveys Raw Pixel data lives in file servers Catalog data (derived objects) lives in Database Online query to any and all Also used for education 150 hours of online Astronomy Implicitly teaches data analysis Interesting things Spatial data search Client query interface via Java Applet Query from Emacs, Python, …. Cloned by other surveys (a template design) Web services are core of it.

SkyServer SkyServer.SDSS.org Like the TerraServer, but looking the other way: a picture of ¼ of the universe Sloan Digital Sky Survey Data: Pixels + Data Mining About 400 attributes per “object” Spectrograms for 1% of objects

Demo of SkyServer Shows standard web server Pixel/image data Point and click Explore one object Explore sets of objects (data mining)

SkyQuery (http://skyquery.net/) Distributed Query tool using a set of web services Many astronomy archives from Pasadena, Chicago, Baltimore, Cambridge (England) Has grown from 4 to 15 archives, now becoming international standard WebService Poster Child Allows queries like: SELECT o.objId, o.r, o.type, t.objId FROM SDSS:PhotoPrimary o, TWOMASS:PhotoPrimary t WHERE XMATCH(o,t)<3.5 AND AREA(181.3,-0.76,6.5) AND o.type=3 and (o.I - t.m_j)>2

SkyQuery Structure Each SkyNode publishes Portal is Schema Web Service Database Web Service Portal is Plans Query (2 phase) Integrates answers Is itself a web service 2MASS INT SDSS FIRST SkyQuery Portal Image Cutout

Schema (aka metadata) Everyone starts with the same schema <stuff/> Then the start arguing about semantics. Virtual Observatory: http://www.ivoa.net/ Metadata based on Dublin Core: http://www.ivoa.net/Documents/latest/RM.html Universal Content Descriptors (UCD): http://vizier.u-strasbg.fr/doc/UCD.htx Captures quantitative concepts and their units Reduced from ~100,000 tables in literature to ~1,000 terms VOtable – a schema for answers to questions http://www.us-vo.org/VOTable/ Common Queries: Cone Search and Simple Image Access Protocol, SQL Registry: http://www.ivoa.net/Documents/latest/RMExp.html still a work in progress.

SkyServer/SkyQuery Evolution MyDB and Batch Jobs Problem: need multi-step data analysis (not just single query). Solution: Allow personal databases on portal Problem: some queries are monsters Solution: “Batch schedule” on portal. Deposits answer in personal database.

Outline ? The Evolution of X-Info Online Literature Online Data The World Wide Telescope as Archetype Experiments & Instruments Simulations facts answers questions Literature Other Archives ? The Big Problems Data ingest Managing a petabyte Common schema How to organize it How to reorganize it How to coexist with others Query and Vis tools Integrating data and Literature Support/training Performance Execute queries in a minute Batch query scheduling

Outline What’s Computer Science? What Do I do? eScience? What’s that? Peer-Reviewed Literature and Data online? How would that work?