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

Architecture Overview • Analysis & Modeling System – Design and execution of ecological models Architecture Overview • Analysis & Modeling System – Design and execution of ecological models and analysis – End user focus – application-/upperware • Semantic Mediation System – Data Integration of hardto-relate sources and processes – Semantic Types and Ontologies – upper middleware • Eco. Grid – Access to ecology data and tools – middle-/underware SEEK Overview, 3/2004 (cf. GEON + Cyberinfrastructure) • Plus Working Groups: – Knowledge Representation (SEEK-KR) – Classification and Nomenclature (TAXON) – Biodiversity and Ecological Analysis and Modeling (BEAM) 2

SEEK Eco. Grid • Goal: standardize interfaces (using web and grid services) – We SEEK Eco. Grid • 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, Di. GIR, 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 SEEK Overview, 3/2004 3

Grid versus Web Services • Grid Services are Web Services – Add authentication, lifecycle 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 Grid. Service base class – When deployed within GT 3, you get these extra functions for ‘free’ – Supports distributed computation via proxy authentication • Problems – Complex system to understand – GT 3 can be difficult to deploy – Proposals to incorporate grid services within the Web services community (Web Services Resource Framework [WSRF]) SEEK Overview, 3/2004 4

Eco. Grid client interactions • Modes of interaction – Client-server – Fully distributed – Eco. Grid client interactions • Modes of interaction – Client-server – Fully distributed – Peer-to-peer • Eco. Grid Registry – Node discovery – Service discovery • Aggregation services – Centralized access – Reliability – Data preservation SEEK Overview, 3/2004 5

Building the Eco. Grid NTL AND HBR VCR LUQ Metacat node Veg. Bank node Building the Eco. Grid NTL AND HBR VCR LUQ Metacat node Veg. Bank node Xanthoria node SEEK Overview, 3/2004 SRB node Di. GIR node Legacy system 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) 6

Kepler: Scientific Workflows Query Eco. Grid to find data Archive output to Eco. Grid Kepler: Scientific Workflows Query Eco. Grid to find data Archive output to Eco. Grid EML provides semi-automated data binding Scientific workflows represent knowledge about the process; Kepler captures this knowledge 7 SEEK Overview, 3/2004

GARP Invasive Species Model Di. GIR Species presence &absence points (invasion area) (a) Eco. GARP Invasive Species Model Di. GIR Species presence &absence points (invasion area) (a) Eco. Grid Query Di. GIR Species presence & absence points (native range) (a) Test sample (d) +A 1 +A 2 +A 3 Training sample (d) Sample GARP rule set (e) Map Data Calculation Native range prediction map (f) Model quality parameter (g) Integrated layers (native range) (c) SRB Environmental layers (native range) (b) Eco. Grid Query Validation User Layer Integration Model quality parameter (g) SRB Environmental layers (invasion area) (b) Layer Integration Integrated layers (invasion area) (c) Map Invasion area prediction map (f) Validation Scientific workflows represent knowledge about the process; AMS captures this knowledge Slide from D. Pennington SEEK Overview, 3/2004 8

Kepler Team, Projects, Sponsors • Ilkay Altintas SDM • Chad Berkley SEEK • Shawn 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 • … SEEK Overview, 3/2004 9 Ptolemy II

Kepler Understands EML Data (Chad Berkley, SEEK) SEEK Overview, 3/2004 10 Kepler Understands EML Data (Chad Berkley, SEEK) SEEK Overview, 3/2004 10

Kepler: Ecological Modeling (Chad Berkley, SEEK) SEEK Overview, 3/2004 11 Kepler: Ecological Modeling (Chad Berkley, SEEK) SEEK Overview, 3/2004 11

Database Access (Efrat Jaeger, GEON) Note: EML descriptions of relational sources would allow automated Database Access (Efrat Jaeger, GEON) Note: EML descriptions of relational sources would allow automated data ingestion SEEK Overview, 3/2004 12

Mineral Classification with Kepler … (Efrat Jaeger, GEON) SEEK Overview, 3/2004 13 Mineral Classification with Kepler … (Efrat Jaeger, GEON) SEEK Overview, 3/2004 13

… inside the Classifier SEEK Overview, 3/2004 14 … inside the Classifier SEEK Overview, 3/2004 14

Standard Browser. UI: Client-Side SVG SEEK Overview, 3/2004 15 Standard Browser. UI: Client-Side SVG SEEK Overview, 3/2004 15

SWF Reengineering (Ilkay, SDM; Ashraf, Efrat, Kai, GEON) SEEK Overview, 3/2004 16 SWF Reengineering (Ilkay, SDM; Ashraf, Efrat, Kai, GEON) SEEK Overview, 3/2004 16

Data. Mapper Sub-Workflow SEEK Overview, 3/2004 17 Data. Mapper Sub-Workflow SEEK Overview, 3/2004 17

Result launched via Browser. UI actor (coupling with ESRI’s Arc. IMS) SEEK Overview, 3/2004 Result launched via Browser. UI actor (coupling with ESRI’s Arc. IMS) SEEK Overview, 3/2004 18

Distributed Workflows in KEPLER • Web and Grid Service plug-ins – WSDL (now) and Distributed Workflows in KEPLER • Web and Grid Service plug-ins – WSDL (now) and Grid services (stay tuned …) – Proxy. Init, Globus. Grid. Job, Grid. FTP, Data. Access. Wizard – 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) SEEK Overview, 3/2004 19

Web Service Actor (Ilkay Altintas, SDM) Given a WSDL and the name of an 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. Configure - select service operation n SEEK Overview, 3/2004 20

Set Parameters and Commit Set parameters and commit SEEK Overview, 3/2004 21 Set Parameters and Commit Set parameters and commit SEEK Overview, 3/2004 21

Specialized WS Actor (after instantiation) SEEK Overview, 3/2004 22 Specialized WS Actor (after instantiation) SEEK Overview, 3/2004 22

Web Service Harvester (Ilkay Altintas, SDM) • Imports the web services in a repository 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. SEEK Overview, 3/2004 23

Kepler: Grid Services Access (Steve Mock, NMI) SEEK Overview, 3/2004 24 Kepler: Grid Services Access (Steve Mock, NMI) SEEK Overview, 3/2004 24

An (oversimplified) Model of the Grid • Hosts: {h 1, h 2, h 3, An (oversimplified) Model of the Grid • Hosts: {h 1, h 2, h 3, …} • [email protected]: d [email protected]{hi}, d [email protected]{hj}, … • [email protected]: f [email protected]{hi}, f [email protected]{hj}, … X f • Given: data/workflow: • … as a functional plan: • … as a logic plan: Y g Z […; Y : = f(X); Z : = g(Y); …] […; f(X, Y) g(Y, Z); …] • Find Host Assignment: di hi , fj hj for all di , fj … s. t. […; d [email protected] 3 : = [email protected] 2(d [email protected] 1), …] is a valid plan SEEK Overview, 3/2004 25

Grid-Enabling PTII: Handles 1. 2. 3. 4. 5. 6. 7. Logical token transfer (3) Grid-Enabling PTII: Handles 1. 2. 3. 4. 5. 6. 7. Logical token transfer (3) requires get_handle(1, 2); then exec_handle(4, 5, 6, 7) for completion. Kepler space 1 Grid space SEEK Overview, 3/2004 3 A B 4 2 Example: &X = “GA. 17” *X = 7 5 GA 6 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) Candidate Formalisms: • Grid. FTP • SSH, SCP • SDSC SRB • OGS? -? ? ? … WSRF? GB 27

Homogeneous Data Integration • Integration of homogeneous or mostly homogeneous data via EML metadata Homogeneous Data Integration • Integration of homogeneous or mostly homogeneous data via EML metadata is relatively straightforward SEEK Overview, 3/2004 28

Heterogeneous Data integration • Requires advanced metadata and processing – – Attributes must be 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 SEEK Overview, 3/2004 • e. g. , that Areal. Density=Count/Area 29

Semantic Mediation • Label data with semantic types • Label inputs and outputs of Semantic Mediation • Label data with semantic types • Label inputs and outputs of analytical components with semantic types Data Ontology Workflow Components • Use reasoning engines to generate transformation steps – Beware analytical constraints • Use reasoning engine to discover relevant components SEEK Overview, 3/2004 30

Ecological ontologies • • What was measured (e. g. , biomass) Type of measurement 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 SEEK Overview, 3/2004 31

Extensions: Semantic Types • Take concepts and relationships from an ontology to “semantically type” 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” m 1 p 3 (normalize) Takes Abundance Count Measurements for Life Stages SEEK Overview, 3/2004 p 4 Returns Mortality Rate Derived Measurements for Life Stages 32

SEEK Overview, 3/2004 33 SEEK Overview, 3/2004 33

SEEK Overview, 3/2004 34 SEEK Overview, 3/2004 34

Semantic Types • The semantic type signature – Type expressions over the (OWL) ontology Semantic Types • The semantic type signature – Type expressions over the (OWL) ontology m 1 p 3 (normalize) p 4 Sem. Type m 1 : : Observation & item. Measured. Abundance. Count & has. Context. applies. To. Life. Stage. Property -> Derived. Observation & item. Measured. Mortality. Rate & has. Context. applies. To. Life. Stage. Property SEEK Overview, 3/2004 35

Extended Type System (here: OWL Semantic Types) Sem. Type m 1 : : Observation Extended Type System (here: OWL Semantic Types) Sem. Type m 1 : : Observation & item. Measured. Abundance. Count & has. Context. applies. To. Life. Stage. Property Derived. Observation & item. Measured. Mortality. Rate & has. Context. applies. To. Life. Stage. Property Substructure association: XML raw-data =(X)Query=> object model =link => OWL ontology SEEK Overview, 3/2004 36

Semantic Types for Scientific Workflows SEEK Overview, 3/2004 37 Semantic Types for Scientific Workflows SEEK Overview, 3/2004 37

Deriving Data Transformations from Semantic Service Registration [Bowers-Ludaescher, DILS’ 04] SEEK Overview, 3/2004 38 Deriving Data Transformations from Semantic Service Registration [Bowers-Ludaescher, DILS’ 04] SEEK Overview, 3/2004 38

Structural and Semantic Mappings [Bowers-Ludaescher, DILS’ 04] SEEK Overview, 3/2004 39 Structural and Semantic Mappings [Bowers-Ludaescher, DILS’ 04] SEEK Overview, 3/2004 39

SEEK Impact • Fundamental improvements for researchers – Global access to ecologically relevant data SEEK Impact • Fundamental improvements for researchers – Global access to ecologically relevant data – Rapidly locate and utilize distributed computation – Capture, reproduce, extend analysis process SEEK Overview, 3/2004 40

Acknowledgements This material is based upon work supported by: The National Science Foundation under 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/Sci. DAC, GEON SEEK Overview, 3/2004 41