eScience: A Transformed Scientific Method

eScience -- A Transformed Scientific Method Jim Gray , eScience Group, Microsoft Research http://research.microsoft.com/~Gray in collaboration with Alex Szalay Dept. Physics & Astronomy Johns Hopkins University http:// www.sdss.jhu.edu/~szalay /

Talk Goals
Explain eScience (and what I am doing) &
Recommend CSTB foster tools for
data capture (lab info management systems)
data curation (schemas, ontologies, provenance)
data analysis (workflow, algorithms, databases, data visualization )
data+doc publication (active docs, data-doc integration)
peer review (editorial services)
access (doc + data archives and overlay journals)
Scholarly communication (wiki’s for each article and dataset)

eScience: What is it?
Synthesis of information technology and science.
Science methods are evolving (tools).
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
publishing data & literature (curation, access, preservation)

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

X-Info
The evolution of X-Info and Comp-X for each discipline X
How to codify and represent our knowledge
Data ingest
Managing a petabyte
Common schema
How to organize it
How to re organize it
How to share with others
Query and Vis tools
Building and executing models
Integrating data and Literature
Documenting experiments
Curation and long-term preservation
The Generic Problems Experiments & Instruments Simulations facts facts answers questions Literature Other Archives facts facts ?

Experiment Budgets ¼… ½ Software
Software for
Instrument scheduling
Instrument control
Data gathering
Data reduction
Database
Analysis
Modeling
Visualization
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
…

Experiment Budgets ¼… ½ Software
Software for
Instrument scheduling
Instrument control
Data gathering
Data reduction
Database
Analysis
Modeling
Visualization
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
…
Action item Foster Tools and Foster Tool Support

Project Pyramids In most disciplines there are a few “giga” projects, several “mega” consortia and then many small labs. Often some instrument creates need for giga-or mega-project Polar station Accelerator Telescope Remote sensor Genome sequencer Supercomputer Tier 1, 2, 3 facilities to use instrument + data International Multi-Campus Single Lab

Pyramid Funding
Giga Projects need Giga Funding Major Research Equipment Grants
Need projects at all scales
computing example: supercomputers, + departmental clusters + lab clusters
technical+ social issues
Fully fund giga projects, fund ½ of smaller projects they get matching funds from other sources
“Petascale Computational Systems: Balanced Cyber-Infrastructure in a Data-Centric World ,” IEEE Computer , V. 39.1, pp 110-112, January, 2006.

Action item Invest in tools at all levels

Need Lab Info Management Systems (LIMSs)
Pipeline Instrument + Simulator data to archive & publish to web.
NASA Level 0 (raw) data Level 1 (calibrated) Level 2 (derived)
Needs workflow tool to manage pipeline
Build prototypes.
Examples:
SDSS, LifeUnderYourFeet MBARI Shore Side Data System.

Need Lab Info Management Systems (LIMSs)
Pipeline Instrument + Simulator data to archive & publish to web.
NASA Level 0 (raw) data Level 1 (calibrated) Level 2 (derived)
Needs workflow tool to manage pipeline
Build prototypes.
Examples:
SDSS, LifeUnderYourFeet MBARI Shore Side Data System.
Action item Foster generic LIMS

Science Needs Info Management
Simulators produce lots of data
Experiments produce lots of data
Standard practice:
each simulation run produces a file
each instrument-day produces a file
each process step produces a file
files have descriptive names
files have similar formats (described elsewhere)
Projects have millions of files (or soon will)
No easy way to manage or analyze the data.

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 N 2 , likelihood techniques N 3
We can only do N logN
Must accept approximate answers New algorithms
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 performed on files
These tasks better done in structured store with
indexing,
aggregation,
parallelism
query, analysis,
visualization tools.

Data Delivery: Hitting a Wall
You can GREP 1 MB in a second
You can GREP 1 GB in a minute
You can GREP 1 TB in 2 days
You can GREP 1 PB in 3 years
Oh!, and 1PB ~4,000 disks
At some point you need indices to limit search parallel data search and analysis
This is where databases can help
You can FTP 1 MB in 1 sec
FTP 1 GB / min (~1 $/GB)
… 2 days and 1K$
… 3 years and 1M$
FTP and GREP are not adequate

Accessing Data
If there is too much data to move around,
take the analysis to the data!
Do all data manipulations at database
Build custom procedures and functions in the database
Automatic parallelism guaranteed
Easy to build-in custom functionality
Databases & Procedures being unified
Example temporal and spatial indexing
Pixel processing
Easy to reorganize the data
Multiple views, each optimal for certain analyses
Building hierarchical summaries are trivial
Scalable to Petabyte datasets
active databases!

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 performed on files
These tasks better done in structured store with
indexing,
aggregation,
parallelism
query, analysis,
visualization tools.
Action item Foster Data Management Data Analysis Data Visualization Algorithms &Tools

Let 100 Flowers Bloom
Comp-X has some nice tools
Beowulf
Condor
BOINC
Matlab
These tools grew from the community
It’s HARD to see a common pattern
Linux vs FreeBSD why was Linux more successful? Community, personality, timing, ….???
Lesson: let 100 flowers bloom.

Talk Goals
Recommend CSTB foster tools and tools for

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 fingertips For everyone-everywhere
Increase Scientific Information Velocity
Huge increase in Science Productivity
Literature Derived and Re-combined data Raw Data

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

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!

Pub Med Central International
“ Information at your fingertips”
Deployed US, China, England, Italy, South Africa, Japan
UK PMCI http://ukpmc.ac.uk/
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 99.99% of the work.

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 articles Data Sets

Overlay Journals
Journal Management System Data Archives articles title page Data Sets

Overlay Journals
Journal Management System Journal Collaboration System Data Archives articles title page comments Data Sets

Overlay Journals
Journal Management System Journal Collaboration System Data Archives Action item Do for other sciences what NLM has done for BIO Genbank-PubMedCentral… articles title page comments Data Sets

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

Conference Management Tool
Currently 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

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.
Let’s have Moderated Wiki re published literature PLoS-One is doing this

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.
Let’s have Moderated Wiki re published literature PLoS-One is doing this
Action item Foster new document authoring and publication models and tools

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

Publishing Data
Exponential growth:
Projects last at least 3-5 years
Data sent upwards only at the end of the project
Data will never be centralized
More responsibility on projects
Becoming Publishers and Curators
Data will reside with projects
Analyses must be close to the data
Roles Authors Publishers Curators Consumers Traditional Scientists Journals Libraries Scientists Emerging Collaborations Project www site Bigger Archives Scientists

Data Pyramid
Very extended distribution of data sets:
data on all scales!
Most datasets are small, and manually maintained (Excel spreadsheets)
Total volume dominated by multi-TB archives
But, small datasets have real value
Most data is born digital collected via electronic sensors or generated by simulators.

Data Sharing/Publishing
What is the business model (reward/career benefit)?
Three tiers (power law!!!)
(a) big projects
(b) value added, refereed products
(c) ad-hoc data, on-line sensors, images, outreach info
We have largely done (a)
Need “Journal for Data” to solve (b)
Need “VO-Flickr” (a simple interface) (c)
Mashups are emerging in science
Need an integrated environment for ‘ virtual excursions ’ for education (C. Wong)

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
Action item Foster Digital Data Libraries (not metadata, real data) and integration with literature Nucleotide sequences Protein sequences Taxon Phylogeny MMDB 3 -D Structure PubMed abstracts Complete Genomes PubMed Entrez Genomes Publishers Genome Centers

Talk Goals
Recommend CSTB foster tools and tools for

backup

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)
OpenSkyQuery Federation 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.

World Wide Telescope Virtual Observatory http://www.us-vo.org/ http://www.ivoa.net/
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
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)
IRAS 100  ROSAT ~keV DSS Optical 2MASS 2  IRAS 25  NVSS 20cm WENSS 92cm GB 6cm

Time and Spectral Dimensions The Multiwavelength Crab Nebulae 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. Crab star 1053 AD

SkyServer.SDSS.org
A modern archive
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
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.

Ecosystem Sensor Net LifeUnderYourFeet.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 LIMS Laboratory Information Management Systems

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

VHA Health Informatics
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

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%)

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eScience: A Transformed Scientific Method

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