Teaching Geoinformatics: A Geoscience Teaching Geoinformatics: A Geoscience PerspectivePerspective

Randy KellerRandy Keller

Professor and Professor and Edward Lamb McCollough Chair in Geophysics

School of Geology and GeophysicsSchool of Geology and Geophysics

University of Oklahoma University of Oklahoma

Geoinformatics - the visionGeoinformatics - the vision

It is too hard to find and It is too hard to find and work with data that already work with data that already

exist.exist.

It is too hard to acquire It is too hard to acquire software and make it work.software and make it work.

We have too little access to We have too little access to modern IT tools that would modern IT tools that would

accelerate progress.accelerate progress.

The result is too little time The result is too little time for science!for science!

To To understand understand

the structure the structure (evolution) (evolution)

and and deformationdeformationof the North of the North

American American continentcontinent

in four in four dimensionsdimensions

(x,y,z,t)(x,y,z,t)

The EarthScopeEarthScope Scientific Vision

Future research opportunities in the geosciences will be significantly affected both by the availability and utilization of Information Technology. Understanding the rock record that preserves ~4.5 billion years of history, Earth structure, and

the processes at work is the key to answering scientific questions associated with studies of biodiversity, climate

change, planetary processes, natural resources and hazards, and the 4-D architecture and evolution of

continents. It has become evident that we can only answer these complex questions through the integration integration of all the

data we have at hand and that this will require the application of modern IT toolsapplication of modern IT tools.

EarthScope

Cyberinfrastructure for the GeosciencesCyberinfrastructure for the GeosciencesWhy do we need it?Why do we need it?

What is Geoinformatics?Geoinformatics is a science which develops and uses information science infrastructure to address the problems of geosciences and related branches of engineering.

The three main tasks of geoinformatics are:

･ development and management of databases of geodata

･ analysis and modeling of geodata

･ development and integration of computer tools and software for the first two tasks.

Geoinformatics is related to geocomputation and to the development and use of geographic information systems or Spatial Decision Support Systems

Applications ･ An object-relational database (ORD) or object-relational database management system (ORDBMS) Object-relational mapping (or O/RM) Geostatistics

Geoinformatics Research & Education Geoinformatics Research Group, School of Civil Engineering & Geosciences, Newcastle University, UK

Geoinformatics - Some key elementsGeoinformatics - Some key elements A strong partnership between domain experts (geoscientists) A strong partnership between domain experts (geoscientists)

and computer scientists and computer scientists A shared goal of doing better (and more) scienceA shared goal of doing better (and more) science A desire to create products that the scientific community A desire to create products that the scientific community

actually needs and will use (not what you think they need or actually needs and will use (not what you think they need or should want) should want)

Always give credit to original sources of data, software, etc. Always give credit to original sources of data, software, etc. A desire to preserve data, make it easily used and discovered, A desire to preserve data, make it easily used and discovered,

and create living databasesand create living databases A desire to create user friendly and platform independent A desire to create user friendly and platform independent

software software A desire to facilitate data integrationA desire to facilitate data integration A desire to create cyberinfrastructure breakthroughs (e.g., A desire to create cyberinfrastructure breakthroughs (e.g.,

visualization, 3-D model building editing, etc.)visualization, 3-D model building editing, etc.) A desire to democratize the use of cutting edge technology in A desire to democratize the use of cutting edge technology in

geoscience research and educationgeoscience research and education

www.Geoinformatics.info

A Scientific Effort VectorA Scientific Effort Vector

Background Background ResearchResearch

Data Collection and Data Collection and CompilationCompilationSoftware IssuesSoftware Issues

ScienceScience

Back-Back- groundground

ResearchResearch

Data Collection Data Collection and Compilation and Compilation

Software IssuesSoftware IssuesScienceScience

ScienceScience - Analysis, Modeling, Interpretation, Discovery

Data SetData Set: A relatively raw compilation of data (standards, formats, completeness may be questionable)

Data BaseData Base: A mature data compilation that has been “cleaned”, standardized with input from the scientific community, formatted for use by others (independent of proprietary software, e.g., ORACLE)

Data SystemData System: A linked and organized set of data bases including public domain software (not platform dependent), tutorials, workflows, and procedures to analyze the data

Some Definitions about DataSome Definitions about Data

Property X Y Z(elevation)

Z(depth)

T

Seismicity Earthquake location

Gravity Density inferred

Aeromagnetic MagneticSusceptibility

inferred

Seismic Reflection Arrival times inferred

Seismic Refraction Arrival times inferred

Electromagnetic Electrical conductivity

inferred

Heat Flow Thermalconductivity

Drill Hole Data Depth, Lithology, Physical

properties

Data systems neededData systems needed

Property X Y Z(elevation)

Z(depth)

T

Geologic Maps Distributionof units

Faults(mapping and imaging)

Geometry inferred

Geochemistry/Petrology Composition inferred

Geochronology Age

Global Positioning System Position

Digital Elevation Model Elevation grid

Remote Sensing (SAR) Image of reflectivity

Remote Sensing(multispectral)

Image of reflectivity

Paleontology Ancient life

Sedimentology Ancient environments

inferred inferred

Data systems needed (continued)Data systems needed (continued)

Data is only the beginningData is only the beginning

DataData

InformationInformation

KnowledgeKnowledge

DecisionDecisionSupportSupport

Value

Value

Volume

Volume

Some considerations in setting up a classSome considerations in setting up a class

The audience (obviously) - what do they know coming in? The audience (obviously) - what do they know coming in? (Geospatial skills, computer programming skills, general (Geospatial skills, computer programming skills, general computer skills, mathematical background, geological computer skills, mathematical background, geological background)background)

How formal will the structure be? (mix of lecture, lab, seminar How formal will the structure be? (mix of lecture, lab, seminar style)style)

How mathematical do you want to be?How mathematical do you want to be?

What is mix of computer science and geoscience?What is mix of computer science and geoscience?

Relation to “Computer Applications in the Geoscience” class?Relation to “Computer Applications in the Geoscience” class?

I strongly recommend that a computer science colleague be I strongly recommend that a computer science colleague be involved to some degree and that there be some computer involved to some degree and that there be some computer science students in the class.science students in the class.

Learning EnvironmentsLearning Environments

FaceFaceToTo

FaceFace

LibraryLibrary

Drop-inDrop-inLabLab

Tele / VideoTele / Videoconferenceconference

EmailEmail

TimeTime

Pla

ceP

lace

Same

Sam

e

Different

Diff

ere

nt

Cyberinfrastructure

DATA

Collaboratory

The independent scientist is not a thing of the past, but more The independent scientist is not a thing of the past, but more and more big advances are made through collaboration.and more big advances are made through collaboration.

A class schedule

A class schedule

(cont.)

Uncertainty, reliability, provenance. Etc.Uncertainty, reliability, provenance. Etc.

Class assignments Class assignments Read papers from the recent literature (<2004 is old )

Set up a modest personal website

Laboratory exercise on EXCEL

Laboratory exercise on GIS

Laboratory exercise on MATLAB

Laboratory exercise on using Google Earth quantitatively

Find an interesting piece of software on-line and demo it to the class

Create a modest web service

Term project to create a modest web portalTerm project to create a modest web portal

The class project

The class project - some topics

Geoinformatics: Data to

Knowledge

GSA Special Paper

Table of Contents I

Table of Contents II

Geoinformatics - Cambridge University Press

Geoinformatics: Cyberinfrastructure for the Solid Earth SciencesCo-editors: G. Randy Keller, University of Oklahoma, USA

Chaitanya Baru, San Diego Supercomputer Center, University of CaliforniaI. INTRODUCTION

1. Introduction to Science Needs and ChallengesG. Randy Keller, University of Oklahoma

2. Introduction to IT Concepts and Challenges Chaitanya Baru, University of California, San Diego

II. DATA COLLECTION AND MANAGEMENT3. Framework for Managing LiDAR/Remote Sensing Data, Ramon Arrowsmith, and Christopher Crosby, Arizona State University4. Algorithms for Gridding and Analysis of Remote Sensing Data,

S. B. Baden, Christopher Crosby, Ramon Arrowsmith, Arizona State University5. Digital Field Data Collection, John Oldow and Douglas Walker, University of Idaho and University of Kansas6. Sensor Networks and Embedded Cyberinfrastructure for Sensor Networks, Tony Fountain, Frank Vernon, Scripps Institute of Oceanography

Geoinformatics - Cambridge University Press

III. MODELING SOFTWARE AND COMMUNITY CODES7. Community Codes for Geodynamics, Mike Gurnis and Walter Landry, CalTech8. Community Codes for Earthquake Wave Propagation Research: The TeraShake PlatformPhilip Maechling, Yifeng Cui, Kim Olsen, David Okaya, Ewa Deelman, Amit Chourasia, Gaurang Mehta, Reagan Moore, and Thomas H. Jordan, Southern California Earthquake Center, University of Southern California9. Parallelizing Finite Element Codes for GeodynamicsMian Liu, University of Missouri10.Designing and Building a Grid-enabled Synthetic Seismogram Computational Resource Dogan Seber, Choonhan Youn, Tim Kaiser, Cindy Santini, University of California at San Diego11. The PaleoAtlas for ArcGISChris Scotese, University of Texas at Arlington

Geoinformatics - Cambridge University Press

IV. VISUALIZATION AND DATA REPRESENTATION12. Visualization of Seismic Model DataSteve Cutchin and Amit Chourasia, UCSD

13. Integrated Visualization of 4D DataCharles Meertens, UNAVCO

14. Visualization and Fusion of Remote Sensing DataEric Frost, San Diego State University

15. Database Development and Visualization for the Yellowstone National Park RegionRobert B. Smith, Jaime Farrell, and Charles Meertens, University of Utah, UNAVCO

Geoinformatics - Cambridge University PressV. KNOWLEDGE MANAGEMENT AND DATA INTEGRATION

16. Data Integration for Paleo Studies: Why and How?Allister Rees, Chris Scotese, Ashraf Memon, John Alroy, Univeristy of Arizona, UCSD, University of California at Santa Barbara, University of Texas at Arlington,

17. Creating a dynamic, calibrated geologic time-line using databases, Web applications, and services, Cinzia Cervato and Peter Sadler, Iowa State University

18. Data Models and Tools for Geochemistry Databases, Kerstin Lehnert, Doug Walker, Richard Carlson, Columbia University, University of Kansas, Carnegie Institution of Washington

19. Spatial and Process Ontologies of Subduction Zones, Hassan Babaie, Georgia State University

20. GeoSciML - A GML application for geoscience information interchangeStephen M. Richard and CGI Interoperability working group, Arizona Geological Survey

21. Bottom-Up Ontologies and Recommendation Systems for Geoscience ApplicationsMark Gahegan, Pennsylvania State University

22. Knowledge Representation in Geology, Krishna Sinha and Kai Lin, Virginia Tech University, University of California at San Diego

Geoinformatics - Cambridge University PressV. KNOWLEDGE MANAGEMENT AND DATA INTEGRATION

23. Web Services and Observation Data Catalogs for Uniform Hydrologic Data Access and Analysis

I. Zaslavsky, D. Valentine, T. Whitenack, D. MaidmentUniversity of California at San Diego, University of Texas at Austin

24. Web Services for Seismic Data ArchivesTim Ahern and Linus Kamb, IRIS

25. Creating CI resources for gravity and magnetic data: Algorithms, Tools, and Web ServicesLeo Salayandia, Raed Aldouri, Ann Gates, Vladik Kreinovich, and G. Randy Keller, University of Texas at El Paso and University of Oklahoma

26. Use of Scientific Workflows in GeoscienceIlkay Altintas, Efrat Jaeger-Frank, Bertram LudaescherUniversity of California at Davis, University of California at San Diego

27. Workflow-Driven Ontologies: A methodology to create scientific workflows from domain knowledge

Leonardo Salayandia, Paulo Pinheiro da Silva, and Ann Q. Gates, UTEP

28. Science Portal for Research and Education in GeosciencesAshraf Memon, Sandeep Chandra, Choonhan Youn, UCSD

Geoinformatics - Cambridge University Press

VII. Emerging International Efforts29. The evolution of Earth Science data integration in the Federal Government of the US: Policy, Practice, and InformaticsLinda Gunderson, U. S. Geological Survey

30. Geosciences Data in India K. V. Subbarao, Indian Institute of Technology. Department, Department of Earth Sciences

31. Global Earth Observations GridSatoshi Sekiguchi, Satoshi Tsuchida, and Ryosuke Nakamura, National Institute of Advanced Industrial Science and Technology (AIST), Japan

32. GEO-GRID – eScience for the Earth- and Environmental ScienceJens Klump, GeoForschungsZentrum, Potsdam, Germany

Some thoughts about a Geoinformatics Some thoughts about a Geoinformatics curriculumcurriculum

(B.S. in Geoscience with Computer Science Minor)(B.S. in Geoscience with Computer Science Minor)

Mathematics background (Calculus, statistics, numerical Mathematics background (Calculus, statistics, numerical analysis)analysis)Computer Programming [which language(s)?]Computer Programming [which language(s)?]GISGISGeophysics/Remote Sensing (Introductory classes)Geophysics/Remote Sensing (Introductory classes)Geology (at least a minor)Geology (at least a minor)Database - Data StructuresDatabase - Data StructuresSoftware Engineering (informal participation)Software Engineering (informal participation)Computer Applications in the GeosciencesComputer Applications in the Geosciences

Skills needed: Data manipulation, web presence, uncertainty Skills needed: Data manipulation, web presence, uncertainty analysis, visualization/graphics, basic hardware handlinganalysis, visualization/graphics, basic hardware handling

•The Geosciences are a discipline that is strongly data drivenstrongly data driven, and large data sets are often developed by researchers and government agencies.•The complexity of the fundamental scientific questions being addressed require a variety of data with highly integrative and highly integrative and innovative approachesinnovative approaches if we are to find solutions. •Geoscientists have a tradition of sharing of datatradition of sharing of data, but being willing to share data if asked or even maintaining an obscure website accomplishes little. Also as a community, we have no mechanisms to share the work that has been done when a third party cleans up, reorganizes or embellishes an existing database.•We waste a large amount of human capitalwaste a large amount of human capital in duplicative efforts and fall further behind by having no mechanism for existing databases to grow and evolve via community input.

SomeSome Thoughts About the Need for CyberinfrastructureThoughts About the Need for Cyberinfrastructure