IRIS Services Initiative Improving Data Access and Integration for the GeoSciences Linus Kamb, Joanna Muench, Tim Ahern IRIS Data Management Center

1 About 1100 stations in real time Nearly 50TB of seismic data Growing currently at ~9TB / year EarthScope contribution raises to ~20TB / year Station and instrument metadata

2 Historical Access Methods Request methods – requests BREQ_FAST NetDC –Web-based request tools WILBER, BUD tools Delivery methods –Tapes –FTP

3 DHI CORBA-based system Available since 2001 Standard data access interfaces Core services: –Network (metadata) server –Event (earthquake info) server –Data (waveform) server

4 DHI Implementations Server implementations at: –IRIS, South Carolina, CalTech, Berkeley, Orfeus, Geofon Example client applications: –Vase, JWeed, SOSA, GEE, SOD –SAC, Matlab, GEON SynSeis –EarthMotionMonitor

5 JWeed

6 DHI 2.0

7 New Directions for IRIS Mandate to provide data to broader geosciences community Provide access to data and data products through web services Expand range of services provided –Computational workflows –Added value services

8 IRIS Services Initiative Develop a Service Oriented Architecture to complement and enhance core access services Internally and externally available components Components include: –data access –pre- and post-processing, filters, transformations –plotting and mapping Move some standard computation to the data Provide access methods appropriate to a wider variety of users Get useful and usable information to the end user

9 Characteristics of SOA Services have contracts Provides information about itself Establishes agreement between provider and requestor Services are loosely coupled Can operate together or independently Changes to one implementation should not break another Services are composable Multiple services can be linked together as workflows Implies contracts are compatible eg. raw data seismogram = processed seismogram

10 Current and Planned Services SOA Registry

11 Workflows Structure and order of a series of tasks Movement of data inputs and outputs through computational steps Composed of service components –Must be logical composition Can be expressed, saved, revised, and re-executed

12 Record Section Plot

13 Workflow Example

14 Workflow Example

15 Workflow Example

16 Workflow Example

17 Workflow Example

18 Workflow Example

19 SPADE Searchable Product Archive and Discovery Engine Archive arbitrary XML data products –Hypocenters, CMTs, historic data, PGV maps, etc. –As yet unknown data products Interface to search by product-specific metadata Query across products by common fields –Geospatial, Time, Other (eg., Dublin Core, keywords,... )

20 SPADE Overview

21 Query - Select Product

22 Query - Enter Filters

23 Query - Results

24 Query - Common Metadata

25 Query - Results

26 IRIS Services Architecture Core data access services Enhanced data tools Wider range of products and services Enable scientific workflows Increased value and service to the broader geosciences community

27 Challenges Service –Description, Registration, Discovery Process composition and orchestration –Data management –Value extraction Data type coordination –Controlled vocabularies Interface-level independence

28 Community Value Improve quality and maintainability of IRIS core services Enable customization of user experience Integrate into other organizations’ computational programs through improved accessibility to IRIS data and products Support a broader geosciences services architecture

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30 Tomographic Visualization MIDSEA project Van der Lee, et al 3D Reference Earth Model Laske, Masters