The iplant Collaborative Semantic Web Platform

Transcription

1 The iplant Collaborative Semantic Web Platform W O R K S H O P O N S E M A N T I C S I N G E O S PAT I A L A R C H I T E C T U R E S : A P P L I C AT I O N S A N D I M P L E M E N TAT I O N O c t o b e r D A M I A N G E S S L E R, P h. D. S E M A N T I C W E B A R C H I T E C T U N I V E R S I T Y O F A R I Z O N A d g e s s l e r ( a t ) i p l a n t c o l l a b o r a t i v e ( d o t ) o r g

2 Classicism and Scholasticism Think, then look Look, then think St. Thomas Aquinas Fra Bartolommeo ( ) Source: w w w. i p l a n t c o l l a b o r a t i v e. o r g 2

3 Empiricism Look, then think Think, then look Sir Francis Bacon Frans Pourbus the younger ( ) Source: w w w. i p l a n t c o l l a b o r a t i v e. o r g 3

4 Scientific Method Hypothesis Conclusion [ support or refutation ] Prediction Analysis Experiment Sir Francis Bacon Frans Pourbus the younger ( ) Source: w w w. i p l a n t c o l l a b o r a t i v e. o r g 4

5 The Experiment as the Rate Limiting Step Hypothesis Conclusion [ support or refutation ] Prediction Analysis Experiment Charles Darwin Leonard Darwin, 1874 Source: w w w. i p l a n t c o l l a b o r a t i v e. o r g 5

6 Bio(Geo)logy Not too long ago: If you love science and hate math, do Bio(Geo)logy w w w. i p l a n t c o l l a b o r a t i v e. o r g 6

7 All-in-one Analysis + Manuscript Prep + Data Management Plan Not too long ago: What? Me worry? My backups are safe Source: w w w. i p l a n t c o l l a b o r a t i v e. o r g 7

8 Quantity has a Quality all of its own Hypothesis driven Data Driven w w w. i p l a n t c o l l a b o r a t i v e. o r g 8

9 Evidence-based Decision-making Decisions have downstream and unintended consequences; analyses and decisions about our Natural world that utilize a scientific approach bias our odds towards viable solutions. w w w. i p l a n t c o l l a b o r a t i v e. o r g 9

10 The Analysis as the Rate Limiting Step Hypothesis from climate change to Conclusion [ support or refutation ] Prediction high throughput sequencing Analysis Experiment Source: w w w. i p l a n t c o l l a b o r a t i v e. o r g 10

11 Re-revolutionizing the Revolution Think, then look Hypothesis driven Data Driven Look, then think 13 th century 20 th century w w w. i p l a n t c o l l a b o r a t i v e. o r g 11

12 Re-revolutionizing the Revolution Look, then think Data driven Hypothesis Driven Think, then look 16 th century 21 st century w w w. i p l a n t c o l l a b o r a t i v e. o r g 12

13 Conclsn Hypoth Predict Scientific Method, on hyper-cycles Analysis Exprmn t Hypoth Conclsn Predict Analysis Exprmn t Analysis Hypoth Conclsn Hypoth Predict Conclsn Predict Analysis Exprmn t Analysis Exprmn t Source: w w w. i p l a n t c o l l a b o r a t i v e. o r g 13

14 Bridging HPC, Enterprise, and Web assets The iplant Collaborative Mission: To build a cyberinfrastructure for the nation s plant scientists. iplant is a Service/Infrastructure project Foundational Infrastructure iplant Data Store, HPC, etc. High Performance Computing 500K core, 10 PetaFLOPS* Petabyte scale storage PetaFLOP: (million billion) floating point operations per second w w w. i p l a n t c o l l a b o r a t i v e. o r g 14

15 depth Bridging HPC, Enterprise, and Web assets breadth Discovery Environment: world class bioinformatics work station at your browser Enterprise Class Discovery Environment, Atmosphere Atmosphere: instant dedicated work station on the cloud: load, use, discard, repeat Enterprise Class Virtual Work desk, Cloud, Virtual machines Foundational Infrastructure iplant Data Store, HPC, etc. High Performance Computing 500K core, 10 PetaFLOPS* Petabyte scale storage PetaFLOP: (million billion) floating point operations per second w w w. i p l a n t c o l l a b o r a t i v e. o r g 15

16 The Greatest Informatic Asset of all Time Web Just a portal and browser or an infrastructural asset? w w w. i p l a n t c o l l a b o r a t i v e. o r g 16

17 Bridging HPC, Enterprise, and Web assets Web What is the infrastructural role for MODS, CODS, and trillions $$$ in web assets? Enterprise Class Discovery Environment, Atmosphere How does iplant engage, leverage, and enhance the Gramene s, the TAIR s, Soybase s, SGN s, MazieGDB s, PlexDB s,..., of the world? How does iplant engage anything that is not a downloadable, installable Linux/MS program? Foundational Infrastructure iplant Data Store, HPC, etc. MODS: Model Organism Databases CODS: Clade-Oriented Databases w w w. i p l a n t c o l l a b o r a t i v e. o r g 17

18 iplant Semantic Web Program Web Enterprise Class Discovery Environment, Atmosphere SSWAP Semantic Integration Semantic Pipelining Distributed Semantic Web Services Logic-driven semantics Enterprise Class Virtual Work desk Cloud, Virtual machines Foundational Infrastructure iplant Data Store, HPC, etc. High Performance Computing 500K core, 10 PetaFLOPS* Petabyte scale storage PetaFLOP: (million billion) floating point operations per second w w w. i p l a n t c o l l a b o r a t i v e. o r g 18

19 iplant Semantic Web Program Web SSWAP Semantic Integration Semantic Pipelining Distributed Semantic Web Services Logic-driven semantics It is the Semantic aspect of the Semantic Web that allows us to leverage the Web from being an external resource into an integrated infrastructural asset. w w w. i p l a n t c o l l a b o r a t i v e. o r g 19

20 The Actors The World You Your lab Semantic Mediation Layer The World iplant Computational Resources (e.g., TACC) Community MODS (Model Organism Databases) and CODS (Clade Oriented Databases) w w w. i p l a n t c o l l a b o r a t i v e. o r g 20

21 Semantic Mediation Sidney Harris 2006 w w w. i p l a n t c o l l a b o r a t i v e. o r g 21

22 The Antibody Analogy as the Mediation Layer w w w. i p l a n t c o l l a b o r a t i v e. o r g 22

23 Simple Semantic Web Architecture and Protocol W3C OWL RDF/XML Establish the framework for Web resources to describe themselves and their offerings Establish the framework for ontological integration Engage first-order, description logic reasoning Provide a semantically enabled Discovery Server for service and pipeline coordination w w w. i p l a n t c o l l a b o r a t i v e. o r g 23

24 SSWAP Enables Reasoner-assisted Workflows Resource 1 Subject Object rdfs:subclassof Resource 2 Subject Object rdfs:subclassof Resource 3 Subject Object A protocol allows a reasoner to connect chains of resources (services) based on logical (not just lexical) matching of what various resources consume and produce. Web Discovery: from (any) Web site -> semantic pipeline Semantic Pipeline: single chain workflows of distributed semantic Web services hosted anywhere on the Web Workflows constructed via reasoner-assisted, first-order subsumption matching of the output of one service into the input of another w w w. i p l a n t c o l l a b o r a t i v e. o r g 24

25 INDIRECTION LAYER INDIRECTION LAYER iplant Semantic Architecture REPOSITORY BROKER EXPLICIT INTERFACE 2 KB Semantic Broker / Discovery Server RDG RQG RRG Semantic documents described in this talk: PDG: Provider Description Graph RDG: Resource Description Graph RIG: Resource Invocation Graph RRG: Resource Response Graph RQG: Resource Query Graph Web EXPLICIT INTERFACE PDG RDG RIG RRG RESTful API RIG RRG RQG INTERPRETER Web Resource Ontology Servers Protocol Ontology Client Data Algorithm Data and Service Providers 1 OWL RDF/XML Ontologies 3 OWL RDF/XML Clients 4 w w w. i p l a n t c o l l a b o r a t i v e. o r g 25

26 sswap.info/example w w w. i p l a n t c o l l a b o r a t i v e. o r g 26

27 From TreeGenes to High Performance Computing w w w. i p l a n t c o l l a b o r a t i v e. o r g 27

28 Semantic Integration from Third-party Web sites DiversiTree Javascript snippet to launch data for Web Discovery with the press of a button w w w. i p l a n t c o l l a b o r a t i v e. o r g 28

29 HTTP API: sswap.info/api JSON -> OWL RDF/XML transformation transparent to the user (via the SSWAP HTTP API) w w w. i p l a n t c o l l a b o r a t i v e. o r g 29

30 Web Discovery into Semantic Pipelines Reasoner-assisted Web workflows Reasoner uses firstorder, description logic to present services and pipelines that can operate on the data at any given step w w w. i p l a n t c o l l a b o r a t i v e. o r g 30

31 Just-In-Time Ontology Hosting sswap.info/jit w w w. i p l a n t c o l l a b o r a t i v e. o r g 31

32 Web Discovery into Semantic Pipelines Reasoner-assisted Web workflows Reasoner uses firstorder, description logic to present services and pipelines that can operate on the data at any given step w w w. i p l a n t c o l l a b o r a t i v e. o r g 32

33 RESTful Pipeline Execution w w w. i p l a n t c o l l a b o r a t i v e. o r g 33

34 Data Tree View Ontologized data and metadata on-the-fly Data Tree views pre-defined renderers w w w. i p l a n t c o l l a b o r a t i v e. o r g 34

35 Semantic Integration into Third-party Web sites TreeGenes CartograTree Third-party web sites can engage as renderers on result sets w w w. i p l a n t c o l l a b o r a t i v e. o r g 35

36 TreeGenes Sequenced, Genotyped, and Phenotyped Geographical browsing into the TreeGenes database tree species sequences genotypes phenotypes w w w. i p l a n t c o l l a b o r a t i v e. o r g 36

37 AmeriFlux Sites CO 2, Water, Energy w w w. i p l a n t c o l l a b o r a t i v e. o r g 37

38 WorldClim 1 Km 2 climate grids w w w. i p l a n t c o l l a b o r a t i v e. o r g 38

39 ArcGIS Layers Soil layers w w w. i p l a n t c o l l a b o r a t i v e. o r g 39

40 TRY-DB Phenotypes w w w. i p l a n t c o l l a b o r a t i v e. o r g 40

41 CartograTree Custom user interface data selection and analysis Select Analyze Web Discovery w w w. i p l a n t c o l l a b o r a t i v e. o r g 41

42 Semantic Integration from Third-party Web sites Data slicing and contextual augmentation w w w. i p l a n t c o l l a b o r a t i v e. o r g 42

43 Direct and Indirect Data Referencing URI dereferencing of arbitrarily large data sets Serialize the data itself, or a URI to where the data is located w w w. i p l a n t c o l l a b o r a t i v e. o r g 43

44 High Performance Computing Services engage like any other Web services w w w. i p l a n t c o l l a b o r a t i v e. o r g 44

45 Custom Service Parameterization w w w. i p l a n t c o l l a b o r a t i v e. o r g 45

46 Publishing Pipelines Private data, shared service parameterization w w w. i p l a n t c o l l a b o r a t i v e. o r g 46

47 Manage and Publish your Pipelines

48 Phylogenetics Pipeline runs are persisted in OWL and can start new pipelines w w w. i p l a n t c o l l a b o r a t i v e. o r g 48

49 TreeViz Multi-location, multi-institution, Web/HPC run w w w. i p l a n t c o l l a b o r a t i v e. o r g 49

50 Quick Vitals 185,000 lines of code 100+ libraries Open source Free SDK (Software Development Kit) for semantics and reasoning on your servers; run pipeline manager on our servers More info: sswap.info/wiki w w w. i p l a n t c o l l a b o r a t i v e. o r g 50

51 Acknowledgements Special thanks to: iplant Collaborative UC Davis Dendrome / TreeGenes Semantic Web engineering by Clark and Parsia, LLC NSF grants # and #EF w w w. i p l a n t c o l l a b o r a t i v e. o r g 51