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GEON: The User Perspective

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Title: GEON: The User Perspective


1
GEON The User Perspective
  • Choonhan Youn
  • Dogan Seber, Chaitan Baru, Ashraf Memon
  • San Diego Supercomputer Center,
  • University of California at San Diego

2
GEON (GEOscience Network)
  • A cyberinfrastructure project for geosciences
    funded by NSF ITR.
  • creating an IT infrastructure to enable
    interdisciplinary geoscience research -- not a
    group of researchers, but the entire community
    will benefit
  • Vision Enable new discoveries in the geosciences
    by building an easy-to-use and comprehensive
    data, software, tools, and information network by
    utilizing state-of the-art information technology
    resources.

3
Current GEON member institutions
  • Partners
  • California Institute for Telecommunications and
    Information Technology Cal-IT2
  • Chronos
  • CUAHSI
  • ESRI
  • Geological Survey of Canada
  • Georeference Online
  • IBM
  • Kansas Geological Survey
  • Lawrence Livermore National Laboratory
  • U.S. Geological Survey (USGS)
  • Other Affiliates
  • Southern California Earthquake Center (SCEC),
    EarthScope, IRIS, NASA
  • Members
  • Arizona State University
  • Bryn Mawr College
  • Penn State University
  • Rice University
  • San Diego State University
  • San Diego Supercomputer Center / University of
    California, San Diego
  • University of Arizona
  • University of Idaho
  • University of Missouri, Columbia
  • University of Texas at El Paso
  • University of Utah
  • Virginia Tech
  • UNAVCO, Inc.
  • Digital Library for Earth System Education (DLESE)

4
GEOSCIENCE CHALLENGES
  • Exponential Increase in Data Volume
  • How to manage vast amounts of data can be used by
    all scientists in an easy-to-use environment
  • Data Storage, Access and Preservation
  • How to build a framework to exchange data and
    help preserving collected data sets
  • Data Integration (semantic and syntactic)
  • How to merge multiple geology maps to make a
    seamless (integrated) map
  • Computational Challenges
  • How to build a system that helps scientists run
    advance software without having access to
    significant resources (computers and technical),
    focusing on the science problem
  • Advance Visualization (3D/4D)
  • How to build a visualization system that helps
    scientists analyze large and complex data sets
    dynamically
  • Archiving and publications of results with
    reusable components (reusability)
  • How to preserve scientific results and help
    others to repeat the analysis as efficiently as
    possible?

5
GEON Cyberinfrastructure (CI) Principles
  • CI Support the day to day conduct of science
    (e-science), in addition to hero computations
  • An equal partnership
  • IT works in close conjunction with science
  • Create shared science infrastructure
  • Integrated online databases, with advanced search
    and query engines
  • Online models, robust tools and applications
  • Leverage from other intersecting projects
  • Much commonality in the technologies, regardless
    of science disciplines, e.g. BIRN, SEEK, and many
    others

6
Main e-Research facilities I
  • A Resource Registration System for Data Providers
  • Register ontologies (domain knowledge) and
    ontology articulations
  • Register datasets with metadata including data
    access information
  • Optionally register datasets to ontologies (which
    is crucial for data integration and smart
    search) Ontology enabled semantic integration
  • Shapefile, ASCII, Excel, GMT Raster, Geo TIFF,
    Relational Database, PDF, tool, WMS service, Web
    service, etc.
  • A Search Engine for Data Users
  • Metadata based search
  • Spatial coverage based search
  • Temporal coverage based search
  • Concept based search
  • Ontology based data discovering

7
Main e-Research facilities II
  • The user workspace, called myGEON area.
  • Users are able to search and collect their data
    sets from the GEON search engine and integrate
    them.
  • For example, users can review and analyze
    "SYNSEIS ouputs that are generated by job
    running.
  • Computational HPC
  • SYNSEIS (Synthetic Seismogram toolkit)
  • Workflow
  • LiDAR an end-to-end solution for the
    distribution, interpolation and analysis of LiDAR
    / ALSM point data.
  • Atype workflow generates map for all plutonic
    bodies in Virginia from the VA Igneous rocks
    database based on the certain inputs.

8
Constraints for main e-Research facilities
  • Dynamic workflow issues due to the web-based
    system on the GEON
  • Large computational clusters for simulating GEON
    applications as needed
  • GEON has three small cluster nodes on partner
    sites

9
GEON Portal Usability
  • Easy of use
  • GEON Search, SYNSEIS, many of them, etc.
  • Make complex tasks easy to specify
  • LiDAR
  • Highly interactive
  • SYNSEIS
  • Integrated access to tools and resources
  • myGEON, Mapping Integration

10
Computational HPC for SYNSEIS
11
Lessons Learnt
  • Its main strengths
  • Standard-compliant ways
  • Using open source libraries and tools for most of
    implementations
  • Its main weaknesses
  • Highly user interactive, friendly interface
    issues within the portlet franework
  • Would you consider alternatives to a portal
    solution?
  • Currently, No

12
Future Plan
  • Will add and develop new functionalities based on
    the requests from GEON PIs and geoscience
    community.
  • Will keep improving the portal usability.
  • For example, in case of SYNSEIS, add more user
    capabilities in the user interface for complex
    earthquake simulations.
  • Will expand its use within geoscience community
    internationally
  • Center on GEON PIs first

13
GEON The Developer Perspective
Choonhan Youn Dogan Seber, Chaitan Baru, Ashraf
Memon San Diego Supercomputer Center, University
of California at San Diego
14
Methods of GEONs Design
  • Several workshops were held with participation
    from scientists from different disciplines like
    geochemistry, geophysics etc.
  • Also Principal Investigators (PIs) visits SDSC
    for focused discussion on their requirements
  • Prototypes are built using gathered requirements
    and then spiral model of software development is
    followed to enhance the prototype.

15
Service-Oriented Approach
16
Priority of Functional and non-functional
requirements
  • Start with functional requirement from the
    principal investigators or local geo-science PI
  • Prototypes are built and functional requirements
    are tested
  • Then focus on to non-functional requirements like
    usability

17
Technical Strategy
  • The two-tier approach
  • Use best practices, including use of commercial
    tools and open standards, where applicable
  • start with development using the technology
    available now
  • while developing advanced technology, and doing
    CS research
  • push for open source and best practices as much
    as possible

18
GEONSearch, Registration, myGEON Portlet
User Access (via Portal)
19
SYNSEIS toolkit
User Access (via Web Browser)
GEONGrid Portal
Cornell Map Server
HTTP
SYNSEIS Portlet
myGEON Portlet
Flash Application
SOAP
SOAP
SOAP
SOAP
Web Services
Data Model Service
Job Submission/Monitoring and File Service
Data Archives Service
SAC Service
CORBA(IIOP)
JDBC
Grid Services
Grid FTP
IRIS DMC
HPC Resources
TeraGrid clusters
20
Development Issues
  • Constraints
  • Interoperability issues due to use of existing
    tools
  • Use of existing tools developed in Fortran and
    some machine dependent algorithms and code GRASS
    based GIS processing.
  • Incompatible implementation of same standard
    (OGCs WMS)
  • Usability requirements
  • Portlets UI is designed by the software
    developers and so they are not very user friendly
  • Part of our tension in the project is that
  • while this is an RD project for the IT folks,
    the science folks want some of it to look like
    production software
  • lack of user input in some cases,
  • because some users are still trying to get up to
    speed with the IT concepts so they havent really
    used the system.

21
Evaluation
  • Usually success of our GEON services is
    determined by user satisfaction!
  • Usability workshop was held recently with domain
    scientist involved and their feedback was taken.
  • Based on this report, we are working on it
  • Another workshop will be held after the
    implementation of the suggested changes.

22
Lessons Learnt
  • The most successful aspects
  • Integrating with other grid, such as TeraGrid
  • Data registration, search capabilities for
    geoscience community
  • Community involvement
  • The least successful aspects
  • Community still is evaluating this system.

23
Future Plans
  • Will provide a secure role-based authorization
    control (using SAML) to fully integrate into the
    GEON portal.
  • Will add WSRP service.
  • The definition of conventions for managing state
    may be handled through standard ways such as WSRF
    so that applications discover, bind, and
    communicate with stateful resources in standard
    and interoperable ways.

24
GEON Search Portlet
25
GEON Resource Registration Portlet
26
User Workspace
27
Mapping Integration Portlet
Geon Dataset Ids
Client Portlet
Map Integration Portlet (Mediator)
Gridsphere
  • Dataset Ids to Dataset Names
  • Dataset Ids to Ontology Ids
  • Ontology Ids to Ontology Names
  • Ontology Ids to Ontology Concepts

Redefine Query
Generate Map
GEON Metadata Catalogue
Execute Query
Mapping Services
Ontology Service
Query Service
Webservices
SRB
Mapping
Download Datasets
Query Tracking DB
Knowledge Representation
GET_EXTRACT
Store Query Results
GET_MAP
Query Result Indexing
Ontology Engine
ArcIMS
28
DATA PROCESSING(LiDAR Portlet)
Client
GEON Catalog
x,y,z and attribute
NFS Mounted Disk
IBM DB2
maps/data
Software Tools
GEONSearchService
process output
GEON Portal
raw data
DB2SpatialFunction
GRASS
ARCINFO
GMT
GEONSearchPortlet
SpatialQueryService
WWW
LiDARProcessPortlet
Compute Cluster
LiDARProcessingService
TeraGrid DataStar
OtherPortlet
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