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UC Santa Barbara. U New Mexico. UC San Diego. U Kansas. Vermont, Napier, ASU, UNC. Science Environment for Ecological Knowledge . Bertram Ludäscher San Diego Supercomputer Center University of California, San Diego. http://seek.ecoinformatics.org. Architecture Overview .

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science environment for ecological knowledge

UC Santa Barbara

U New Mexico

UC San Diego

U Kansas

Vermont, Napier, ASU, UNC

Science Environment for Ecological Knowledge

Bertram Ludäscher

San Diego Supercomputer Center

University of California, San Diego

http://seek.ecoinformatics.org

architecture overview
Architecture Overview
  • Analysis & Modeling System
    • Design and execution of ecological models and analysis
    • End user focus
    • application-/upperware
  • Semantic Mediation System
    • Data Integration of hard-to-relate sources and processes
    • Semantic Types and Ontologies
    • upper middleware
  • EcoGrid
    • Access to ecology data and tools
    • middle-/underware

(cf. GEON + Cyberinfrastructure)

  • Plus Working Groups:
  • – Knowledge Representation (SEEK-KR)
  • – Classification and Nomenclature (TAXON)
  • – Biodiversity and Ecological Analysis and Modeling (BEAM)
seek ecogrid
SEEK EcoGrid
  • Goal: standardize interfaces (using web and grid services)
    • We have standardized data via EML
    • Integrate diverse data networks from ecology, biodiversity, and environmental sciences
  • Grid-standardized interfaces
    • Uniform interface to:
      • Metacat, SRB, DiGIR, Xanthoria, etc.
      • Anyone can implement these interfaces
      • Hides complexity of underlying systems
  • Metadata-mediated data access
    • Supports multiple metadata standards
    • EML, Darwin Core as foci
  • Computational services
    • Pre-defined analytical services
    • On-the-fly analytical services
grid versus web services
Grid versus Web Services
  • Grid Services are Web Services
    • Add authentication, lifecycle management, notification, etc.
    • Globus Toolkit 3: Implements Open Grid Services Architecture (OGSA)
  • Implications for use
    • Write a normal web service extending GridService base class
    • When deployed within GT3, you get these extra functions for ‘free’
    • Supports distributed computation via proxy authentication
  • Problems
    • Complex system to understand
    • GT3 can be difficult to deploy
    • Proposals to incorporate grid services within the Web services community (Web Services Resource Framework [WSRF])
ecogrid client interactions
EcoGrid client interactions
  • Modes of interaction
    • Client-server
    • Fully distributed
    • Peer-to-peer
  • EcoGrid Registry
    • Node discovery
    • Service discovery
  • Aggregation services
    • Centralized access
    • Reliability
    • Data preservation
building the ecogrid

LUQ

AND

HBR

VCR

NTL

Building the EcoGrid

LTER Network (24) Natural History Collections (>> 100)

Organization of Biological Field Stations (180)

UC Natural Reserve System (36)

Partnership for Interdisciplinary Studies of Coastal Oceans (4)

Multi-agency Rocky Intertidal Network (60)

Metacat node

SRB node

VegBank node

DiGIR node

Xanthoria node

Legacy system

kepler scientific workflows
Kepler: Scientific Workflows

Query EcoGrid to find data

Archive output to EcoGrid

EML provides semi-automated data binding

Scientific workflows represent knowledge about the process; Kepler captures this knowledge

garp invasive species model

DiGIR

Species presence &absence points (invasion area) (a)

Test sample (d)

DiGIR

Species

presence &

absence points

(native range)

(a)

Native range prediction

map (f)

Training sample (d)

GARP

rule set (e)

Data

Calculation

EcoGrid

Query

EcoGrid

Query

Map

Map

Validation

User

Validation

Sample

+A3

+A2

Model quality

parameter (g)

Integrated

layers

(native range) (c)

Layer

Integration

Layer

Integration

+A1

SRB

Environmental layers (native

range) (b)

Model quality

parameter (g)

SRB

Environmental layers (invasion area) (b)

Integrated

layers

(invasion area) (c)

Invasion

area prediction map (f)

GARP Invasive Species Model

Scientific workflows represent knowledge about the process; AMS captures this knowledge

Slide from D. Pennington

kepler team projects sponsors
Ilkay Altintas SDM

Chad Berkley SEEK

Shawn Bowers SEEK

Jeffrey Grethe BIRN

Christopher H. Brooks Ptolemy II

Zhengang Cheng SDM

Efrat Jaeger GEON

Matt Jones SEEK

Edward A. Lee Ptolemy II

Kai Lin GEON

Bertram Ludäscher BIRN, GEON, SDM, SEEK

Steve Mock NMI

Steve Neuendorffer Ptolemy II

Jing Tao SEEK

Mladen Vouk SDM

Yang Zhao Ptolemy II

Kepler Team, Projects, Sponsors

Ptolemy II

database access efrat jaeger geon
Database Access (Efrat Jaeger, GEON)

Note: EML descriptions of relational sources would allow automated data ingestion

distributed workflows in kepler
Distributed Workflows in KEPLER
  • Web and Grid Service plug-ins
    • WSDL (now) and Grid services (stay tuned …)
    • ProxyInit, GlobusGridJob, GridFTP, DataAccessWizard
    • SSH, SCP, SDSC SRB, OGS?-???… coming
  • WS Harvester
    • Import query-defined WS operations as Kepler actors
  • XSLT and XQuery Data Transformers
    • to link not “designed-to-fit” web services
  • WS-deployment interface (planned)
web service actor ilkay altintas sdm

Configure - select service

operation

Web Service Actor (Ilkay Altintas, SDM)
  • Given a WSDL and the name of an operation of a web service, dynamically customizes itself to implement and execute that method.
set parameters and commit
Set Parameters and Commit

Set parameters

and commit

web service harvester ilkay altintas sdm
Web Service Harvester (Ilkay Altintas, SDM)
  • Imports the web services in a repository into the actor library.
  • Has the capability to search for web services based on a keyword.
an oversimplified model of the grid

g

f

X Y Z

An (oversimplified) Model of the Grid
  • Hosts: {h1, h2, h3, …}
  • Data@Hosts: d1@{hi}, d2@{hj}, …
  • Functions@Hosts: f1@{hi}, f2@{hj}, …
  • Given: data/workflow:
  • … as a functional plan: […; Y := f(X); Z := g(Y); …]
  • … as a logic plan: […; f(X,Y)g(Y,Z); …]
  • FindHost Assignment: di hi , fj hj for all di ,fj

… s.t. […; d3@h3 := f@h2(d1@h1), …] is a valid plan

shipping handling algebra sha

f@a

f@a

f@a

f@a

x@b

x@b

x@b

x@b

y@c

y@c

y@c

y@c

Shipping & Handling Algebra (SHA)

Logical view

(1)

  • plan Y@C = F@A of X@B =
  • [ X@B to A, Y@A := F@A(X@A), Y@A to C ]
  • [ F@A => B, Y@B := F@B(X@B), Y@B to C ]
  • [ X@B to C, F@A => C, Y@C := F@C(X@C) ]

(2)

(3)

Physical view: SHA Plans

grid enabling ptii handles
Grid-Enabling PTII: Handles
  • AGA: get_handle
  • GAA: return &X
  • AB: send &X
  • BGB: request &X
  • GBGA: request &X
  • GA GB: send *X
  • GBB: send done(&X)
  • Example:
  • &X = “GA.17”
  • *X =<some_huge_file>
  • Candidate Formalisms:
  • GridFTP
  • SSH, SCP
  • SDSC SRB
  • OGS?-??? … WSRF?

Logical token transfer (3) requires get_handle(1,2); then exec_handle(4,5,6,7) for completion.

Keplerspace

3

A

B

4

7

2

1

5

Gridspace

GA

GB

6

homogeneous data integration
Homogeneous Data Integration
  • Integration of homogeneous or mostly homogeneous data via EML metadata is relatively straightforward
heterogeneous data integration
Heterogeneous Data integration
  • Requires advanced metadata and processing
    • Attributes must be semantically typed
    • Collection protocols must be known
    • Units and measurement scale must be known
    • Measurement relationships must be known
      • e.g., that ArealDensity=Count/Area
semantic mediation
Semantic Mediation
  • Label data with semantic types
  • Label inputs and outputs of analytical components with semantic types
  • Use reasoning engines to generate transformation steps
    • Beware analytical constraints
  • Use reasoning engine to discover relevant components

Data

Ontology

Workflow Components

ecological ontologies
Ecological ontologies
  • What was measured (e.g., biomass)
  • Type of measurement (e.g., Energy)
  • Context of measurement (e.g., Psychotria limonensis)
  • How it was measured (e.g., dry weight)
  • SEEK intends to enable community-created ecological ontologies using OWL
    • Represents a controlled vocabulary for ecological metadata
extensions semantic types
Extensions: Semantic Types
  • Take concepts and relationships from an ontology to “semantically type” the data-in/out ports
  • Application: e.g., design support:
    • smart/semi-automatic wiring, generation of “massaging actors”

m1

(normalize)

p3

p4

Takes Abundance Count

Measurements for Life Stages

Returns Mortality Rate Derived

Measurements for Life Stages

semantic types
Semantic Types
  • The semantic type signature
    • Type expressions over the (OWL) ontology

m1

(normalize)

p3

p4

SemType m1 ::

Observation & itemMeasured.AbundanceCount &

hasContext.appliesTo.LifeStageProperty

->

DerivedObservation & itemMeasured.MortalityRate &

hasContext.appliesTo.LifeStageProperty

extended type system here owl semantic types
Extended Type System (here: OWL Semantic Types)

SemType m1 ::

Observation & itemMeasured.AbundanceCount &

hasContext.appliesTo.LifeStageProperty

 DerivedObservation & itemMeasured.MortalityRate & hasContext.appliesTo.LifeStageProperty

Substructure association:

XML raw-data =(X)Query=> object model =link => OWL ontology

deriving data transformations from semantic service registration
Deriving Data Transformations from Semantic Service Registration

[Bowers-Ludaescher,

DILS’04]

structural and semantic mappings
Structural and Semantic Mappings

[Bowers-Ludaescher,

DILS’04]

seek impact
SEEK Impact
  • Fundamental improvements for researchers
    • Global access to ecologically relevant data
    • Rapidly locate and utilize distributed computation
    • Capture, reproduce, extend analysis process
acknowledgements
Acknowledgements

This material is based upon work supported by:

The National Science Foundation under Grant Numbers 9980154, 9904777, 0131178, 9905838, 0129792, and 0225676.

PBI Collaborators: NCEAS, University of New Mexico (Long Term Ecological Research Network Office), San Diego Supercomputer Center, University of Kansas (Center for Biodiversity Research)

Kepler contributors: SEEK, Ptolemy II, SDM/SciDAC, GEON