2. Enabling Transformation
in the Social Sciences,
Geosciences, and
Cyberinfrastructure
Support from the National Science Foundation is deeply
appreciated:
NSF-VOSS EAGER 0956472, “Stakeholder Alignment in Socio-
Technical Systems,”
NSF OCI RAPID 1229928, “Stakeholder Alignment for EarthCube,”
NSF GEO-SciSIP-STS-OCI-INSPIRE 1249607, “Enabling
Transformation in the Social Sciences, Geosciences, and
Cyberinfrastructure,”
NSF OCI 12-56163, “Envisioning Success: A Workshop for Next
Generation EarthCube Scholars and Scientists,”
NSF I-CORPS 1313562 “Stakeholder Alignment for Public-Private
Partnerships,”
Stakeholder Alignment Visualization Patent Pending: Serial No.
13/907,291 (2013).
Joel Cutcher-Gershenfeld,
University of Illinois, Urbana-Champaign
Nick Berente, University of Georgia
Burcu Bolukbasi, UIUC
Nosh Contractor, Northwestern University
Leslie DeChurch, Georgia Tech University
Courtney Flint, Utah State University
Gabe Gershenfeld, Cleveland Indians
Michael Haberman, UIUC
John L. King, University of Michigan
Eric Knight, University of Sydney
Spenser Lewis, General Dynamics
Barbara Lawrence, UCLA
Ethan Masella, Brandeis Uniersity
Charles Mcelroy, Case Western
Reserve University
Barbara Mittleman, Nodality, Inc.
Mark Nolan, UIUC
Melanie Radik, Brandeis University
Namchul Shin, Pace University
Susan Winter, University of Maryland
3. 1. What are the overall aims
of your project?
• Enable agile, sustainable institutional arrangements in
support of the EarthCube mission
• Document lessons for similar initiatives in other domains,
advancing organizational and institutional theory
2. How will your project contribute to the overall
success for EarthCube?
• Providing situational awareness on views about sharing
data, software, and models, as well as related matters,
across the geoscience and cyber communities
• Helping to facilitate the chartering/instantiation of EC
assemblies
4. 3. What are the key milestones and
deliverables for your project?
2013 Stakeholder surveys (v1.5) and feedback to 22 EC
end user workshops (n=798 / 1,511)
Scholarly articles on “internal alignment” and
“making data public”
2014 Development and administration of stakeholder
survey (v2.0) for past respondents and professional
associations
Facilitation support for chartering/instantiation of
EC assemblies
Scholarly articles on “Cooperation and competition
in the Geosciences,” “Vies on standards,” and others
2015 Elements of a theory framework for the “science of
scienceinstitutions”
7. C4P: Objective
• advance the role of
cyberinfrastructure (CI) in the
study of the geological record
• to unravel the large-scale, long-
term evolution of the Earth-life
system,
• across the whole Earth surface,
• for any time interval,
• at any relevant temporal and spatial
resolution.
This image cannot currently be displayed.
8. C4P: Challenges
• A typical ‘Long-tail’ community: Much fossil data are ‘dark’
• Many databases & informatics efforts, but little
coordination or interoperability
9. C4P: Components
• Build new partnerships and collaborations among
geoscientists and technologists
• Survey and catalog existing resources
• Share news of the latest advances in cyberscience and
paleo-geoinformatics
• Facilitate development of common standards and
semantic frameworks
CoreWall
10. C4P: Themes
• SAMPLES
• improve access and re-use of samples through integration into
digital data infrastructures;
• METHODS
• document provenance of data and derived data products in
compliance with emerging best practices and standards to ensure
re-usability, reproducibility and trust for data providers and data
users;
• SYNTHESIS
• improve utilization of time as a unifying parameter in
paleogeoscience CI and broader EarthCube interoperability
• develop & promote metadata standards and data services to
integrate paleobioscience CI resources.
11. C4P: Activities
• Cataloging existing cyberinfrastructure resources in the
paleobiosciences
• Sub award to NCDC to generate ISO metadata records, work with
CINERGI
• Workshops:
• Paleobioinformatics (May 21-23, 2014, COL, Washington, DC)
• Geochronology “Overcoming Barriers to Computation and
Visualization with Geologic Time” (Fall 2014, Madison, WI)
• Synthesis (Spring 2015, Lamont)
• Town Halls & Early Career Symposia at GSA, AGU, ESIP
• Travel support for early career scientists
13. C4P: Activities
• Outreach via Social Media
• Twitter: #EarthCubeC4P
• EarthCube Website: http://workspace.earthcube.org/c4p
• YouTube Channel: http://www.youtube.com/cyber4paleo
• Discussion group: cyber4paleo@earthcube.org
14. C4P: Steering Committee
• Lehnert, Kerstin IEDA, Columbia University
• Anderson, David M. NOAA, National Climatic Data Center
• Fils, Douglas Consortium for Ocean Leadership
• Jenkins, Chris University of Colorado at Boulder
• Lenhardt, Christopher Renaissance Computing Institute
• Noren, Anders University of Minnesota
• Olszewski, Thomas Texas A&M University
• Smith, Dena University of Colorado at Boulder
• Uhen, Mark George Mason University
• Williams, Jack University of Wisconsin-Madison
• Project Management: Leslie Hsu (IEDA, Columbia University)
15.
16. EC3—Earth-Centered Communication for Cyberinfrastructure:
Challenges of field data collection, management, and
integration
Steering Committee Membership: Richard Allmendinger, Cornell U; Jim Bowring,
College of Charleston; Marjorie Chan, U of Utah; Amy Ellwein, Rocky Mountain Bio
Lab; Yolanda Gil, U of Southern CA; Paul Harnik, Franklin and Marshall College; Eric
Kirby, Penn State U; Ali Kooshesh, Sonoma State U; Matty Mookerjee, Sonoma State
U; Rick Morrison, Comprehend Systems Inc; Terry Pavlis, U of Texas, El Paso; Shanan
Peters, U of Wisc, Madison; Bala Ravikumar, Sonoma State U; Paul Selden, U of
Kansas; Thomas Shipley, Temple U; Frank Spear, Rensselaer Poly. Inst; Basil Tikoff, U
of Wisc, Madison; Douglas Walker, U of Kansas; Mike Williams, U of Mass., Amherst
Initiate relationships and
collaborations between field-based
geoscientists and computer
scientists
Why Concentrate on Field-based
disciplines of the Geosciences?
Common set of challenges with regards to
digitizing our data and making those data
available through community databases.
Fieldwork provides essential information
about the long-term history of the Earth’s
atmosphere, oceans, and tectonic cycles.
There is no better place to have these conversations than in the field
Summer 2014 field trip: Yosemite/Owen’s Valley, Aug 4th-8th
Summer 2015 field trip: TBA
Applications to participate in fieldtrips:
Form available at: http://earthcube.org/page/workshops
Deadline: March 10th
e-mail applications to matty.mookerjee@sonoma.edu
17.
18. RCN
SEN:
Building
a
Sediment
Experimentalists
Network
Wonsuck
Kim
(UT
AusAn)
Leslie
Hsu
(LDEO)
Brandon
McElroy
(U
Wyoming)
Raleigh
MarAn
(UCLA)
deltas
ripples
floods
channels
meanders
mountains
19. Overall
aims
of
SEN
project
• Build
the
community
and
discussion
forums:
provide
places
for
sharing
ideas
and
work,
acAvely
recruiAng
content.
• Create
centralized
resources:
a
place
to
go
to
find
informaAon
and
ask
quesAons
about
data
management
and
experimental
procedures.
• Disseminate
guidelines,
standards,
best
prac@ces:
have
the
discussion
of
what
metadata
and
standards
are
needed
to
re-‐use
data
and
re-‐create
experiments.
EarthCube
PorTolio
MeeAng,
Feb
2014,
RCN
SEN
20. SEN
Contribu@ons
to
EarthCube
• “Real”
domain
scien@sts
and
data:
tractable
group
size
(order
100s)
with
close
Aes
to
larger
Earth
surface
group
(order
1000s),
Aght-‐knit
community
• Early
career
component:
many
or
most
experimentalists
are
early
career
–
graduate
students
or
postdocs,
more
willing
to
try
new
tools
• Almost
a
blank
slate:
A
community
with
fewer
organized
legacy
databases
and
tools
–
acknowledges
the
need
for
help,
more
likely
to
use
EC
resources
EarthCube
PorTolio
MeeAng,
Feb
2014,
RCN
SEN
21. SEN
milestones
and
deliverables
hp://workspace.earthcube.org/sen/group-‐tasks/sen-‐year-‐1-‐tasks
• SEN-‐KB:
Knowledge
base:
Wiki
and
data
catalog
for
experimental
data
and
procedures
• SEN-‐ED:
Educa@on
Discussion
and
disseminaAon
of
standards
and
guidelines.
DocumentaAon
of
discussion
and
outcomes.
• SEN-‐EC:
Experimental
collaboratories:
Networked
laboratories
with
broadcasAng
abiliAes
for
shared
experiments
EarthCube
PorTolio
MeeAng,
Feb
2014,
RCN
SEN
22.
23. Enterprise Architecture for
Transformative Research and
Collaboration Across the Geosciences
Paradigm: Emergence, Self-organizing system requires
more direct interaction between agents in the system
Technology-enabled feedback between users cultivates
an emergent, self-organizing system
Resources Activities
Usage
Log
Recommendations Impact
Analysis
Publication
Discussion
Data use
Data revision
Annotation…
People
Models
Data…
24. How it fits in an Integrated EarthCube
• Provide specific proposal for system design as
a straw man to promote community
convergence
Milestones
• Draft white paper
– Use cases
– Requirements
– Existing architecture
– Proposed design
• System architects
summit
• Final white paper
25. Products
• Community discussion of scope, use cases,
integration of existing components
• White paper documenting vision and
conceptual architecture
• Concrete proposal to drive community
discussion and convergence on EarthCube
design
26.
27. CD: Developing a Data-Oriented
Human-Centric Enterprise
Architecture for EarthCube
Phil Yang and Chen Xu,
NSF Spatiotemporal Innovation Center
George Mason Univ.
Carol Meyer, ESIP
28. User
Interfaces
Applications
Data
Services
Geoscientists
EarthCube
Administrator
Educators
On-Demand Work-Flow Chaining Layer
Interdisciplinary Data & Business Interoperability Layer
Geological
Geophysical Biological Climatology
DataandInformationProvenance
Geospatial
Portal
Geochemistry Petrology
Sedimentology
… …
Modeling
Capability
Big Data
Analytics
Pre and Post
Processing
Public
Generic CI Services
Data
Discovery
Data
Access
Data
Visualization
Data
Publication
Modeling
Geological
Portal
Modeling
GUI
Rivers
Portal
Citizen Science
Portal
Seismic
Portal
… …
… …
29. EarthCube Project
Project Portfolio
Relationships
Project
Timelines
Project to
Capability Mapping
Capability
Vision
Capability
Taxonomy
Capability
Phasing
Capability
Dependencies
Capability to
Operational
Capability to
Services
High Level
Operational
Operational
Resource Flow
Operational
Relationships
Operational
Activities
Service
Context
Service
Resource Flow
Service to
System
System
Interface
System
Resource Flow
System to
System
System
Functionality
System back to
Operational
Conceptual
Data Model
Physical Data
Model
Logical Data Model
Technical Standards
31. Benefits to the
EarthCube
Enterprise
• Supporting strategic planning and alignment of business and EarthCube goals and
objectives
• Maintaining baseline and target architecture information in a system repository
• Ensuring EarthCube projects align with Enterprise Architecture
• Defining a performance management framework for guiding the success of projects
• Identifying technical and process improvement opportunities
• Identifying opportunities for collaboration, reuse, data sharing and consolidation
• Documenting enterprise service capabilities available for use across the EarthCube
• Ensuring alignment with relevant cross-disciplinary and International initiatives
Collection
PresentationProcess
Multi-Party
Collaboration
Data-Owner
Obligation
Public
Partaking
CKN
The Core EarthCube Conceptual Model
Collection: Data / service
Process: Data analytics
Presentation: Results visualization
Data-owner: EarthCube stakeholders
capable of data production
Multi-party: EarthCube participants
Public: Third party outside of
EarthCube enterprise
32. Milestones and
Deliverables
EarthCube Design Initial Write-up
Volume I Overview and Summary Information
Volume II EarthCube Cyberinfrastructure
Architecture Design: System, Operation, and
Standards
Volume III EarthCube Enterprise Architecture
Dictionary
Volume IV EarthCube EA Use Case – Polar CI
Project
33. EarthCube Enterprise Architecture
Workshop at ESIP Summer Meeting
• Point of Contact: Carol Meyer, ESIP Executive Director
• Date: July 7, 2014
• Location: Copper Mountain, Colorado
• Content: Domain experts to review and comment on
the design
– Pick one or more volumes to comment
– Discuss comment at ESIP Summer Meeting
– Provide advice on improving the EA
• Support:
– $700/expert for up to 10 experts
• Call for participation will be out soon, please help get the
word out
34.
35. EarthCube Building Block ODSIP:
Open Data Services Invocation
Protocol
Dave Fulker (OPeNDAP), PI
Mohan Ramamurthy (Unidata), Co-PI
Senior Personnel: Brian Blanton (RENCI), Steve
Businger (U-Hawaii), Peter Cornillon (U-Rhode Island)
36. Overarching Goal
• We propose building blocks—open specifications,
realized in client/server libraries—for a model and
protocol by which clients invoke a rich set of data-
acquisition services.
– Services will range from statistical summarization and
criteria-driven subsetting to regridding/resampling.
• ODSIP will build on the newest version of OPeNDAP’s
data-access protocol, DAP4, now being tested under a
collaborative, NOAA-funded OPeNDAP-Unidata project,
designed to accommodate extensions of the sort
proposed here.
37. Building Block Objectives
• An open specification for ODSIP (as a DAP4
extension, suitable for eventual OGC adoption).
– DAP, Data Access Protocol, is the underpinning for
OPeNDAP
• Reference implementations of ODSIP in open-
source libraries callable from multiple languages.
• Demonstrations, in openly accessible clients and
servers, illustrating how ODSIP services may be
invoked to support diverse geoscience scenarios
38. Representative Use Cases
1. Accelerated Visualization/Analysis of Model
Outputs on Non-Rectangular Meshes
2. Dynamic Downscaling of Climate Predictions
for Regional Utility
3. Feature-Oriented Retrievals of Satellite
Imagery
39. EarthCube Relevance
• EarthCube will benefit from a conceptually rich and
widely deployed protocol for data-acquisition. To that
end, our BB work will enable development of servers
and clients that implement just such a protocol,
namely, ODSIP.
• While the eventual benefits of our work will be
manifest as numerous ODSIP-compliant servers and
clients, the immediate outcomes will be to support
their creation.
• The ODSIP project will contribute toward addressing
challenges EarthCube faces toward truly transforming
multiscale and multidisciplinary research and
education.
42. Software Stewardship for Geosciences
Principal Investigators:
Christopher J. Duffy
Department of Civil and Environmental Engineering, Penn State University
Yolanda Gil
Information Sciences Institute, University of Southern California
Department of Computer Science, University of Southern California
James D. Herbsleb
Institute for Software Research, Carnegie Mellon University
Chris A. Mattmann
NASA Jet Propulsion Laboratory
Department of Computer Science, University of Southern California
Scott D. Peckham
Department of Hydrologic Sciences, University of Colorado
Erin Robinson
Foundation for Earth Science
NSF ICER-1343800
geosoft.earthcube.org
43. The Importance of Geosciences Software
• EarthCube aims to enable scientists solve challenging
problems that span diverse geoscience domains
– This requires not only data sharing but new forms of knowledge
sharing
• The focus of our project is on helping scientists to share
knowledge concerning the software they develop
44. Problems: (I) Software Cost
– “Scientists and engineers spend more than 60% of
their time just preparing the data for model input
or data-model comparison” (NASA A40)
“Common Motifs in Scientific Workflows: An Empirical Analysis.” Garijo, D.; Alper, P.;
Belhajjame, K.; Corcho, O.; Gil, Y.; and Goble, C. Future Generation Computer Systems, 2013.
46. GeoSoft: Software Stewardship for Geosciences
• An on-line community for sharing knowledge
about geosciences software
• Project involves: geoscientists, social scientists
expert in on-line communities, and computer
scientists expert in knowledge capture, open
source software, and software reuse
50. GeoSoft: Software Stewardship for Geosciences
• Ongoing work:
– Intelligent assistance to describe new software: how to
use it appropriately, what kinds of data, how it relates
to other software
– Sophisticated search capabilities to find software for
their needs
– Interactive advice on open source software, forming
successful developer communities, and other software
sharing topics
51.
52. Earth System Bridge
An NSF funded EarthCube Building Block
Scott Peckham, CU-Boulder, PI
Co-PIs
Jennifer Arrigo (CUAHSI), Cecelia Deluca (NOAA, CIRES),
David Gochis (NCAR), Rocky Dunlap (GA Tech), Anna
Kelbert & Gary Egbert (OSU), Eunseo Choi (Memphis)
53. What is the Big Picture?
Geoscientists are problem solvers. Problem solving is sometimes
about creating new resources (e.g. models, data sets or web
services), but very often requires connecting a set of existing
resources. The problem is that these resources are very
hetereogeneous and are often designed for a specific environment
(e.g. PC or HPC) . This makes them hard to connect.
We seek interoperability. We have learned that the key to
interoperability is to have standardized "metadata" descriptions of
the resources that need to be connected to solve a problem. Given
sufficient metadata, frameworks can be designed to automatically
query and then reconcile differences between the resources to be
connected.
54. The Science Goal: Improving
Environmental Modeling Predictions
∗ Mission-Driven agencies
providing predictions
∗ Efficient data and
computational enterprise
∗ Information to protect life and
property ∗ Academic Enterprise
∗ Geoscientists advancing the
science
∗ Computer scientists
advancing the technology
∗ Scientific inquiry and
hypothesis testing
“Bridging the Gap” to Enable
Research-to-Operations
Operations-to-Research
55. Building the Bridge
∗ Framework Definition Language
(FDL)
∗ Metadata specification
∗ Application Architecture
∗ Protocols for interaction
∗ Mechanics and Implementation
∗ Build a series of bridges
∗ Semantic
∗ Frameworks
∗ new services to improve the
integration of inter-agency, four-
dimensional databases with
more heterogeneous academic
databases
56. Initial Groups for Demonstration
∗ ESMF- Earth System
Modeling Framework
∗ NUOPC - National Unified
Operational Prediction
Capability – Layer to
enhance interoperability
∗ CSDMS - Community Surface
Dynamics Modeling System
∗ Pyre -Python Framework for
Coupling CIG Models
∗ CUAHSI data services
∗ NCAR/UCAR resources
∗ WRF
∗ CESM
∗ CSS-Wx
∗ CIG, EarthScope, IRIS, and
UNAVCO resources
FEDERAL
ACADEMIC
57.
58. Community
Inventory of
EarthCube
Resources for
Geoscience
Interoperability
Goals:
- Create an EathCube platform for registering,
finding and evaluating geoscience resources to
facilitate Earth Science Research
- Engage the community in building and growing
high quality content
- Eventually: cross-link different types of
resources for better navigation and search
CINERGI
Ilya Zaslavsky, Steve Richard
And the CINERGI team
http://workspace.earthcube.org/cinergi
59. How it fits in an Integrated EarthCube
• Key gateway to EC resources for users
• A platform for other projects to register and find resources, providing
resource cataloguing and metadata value adding (we succeed together)
• A vehicle for people to announce their resources to EC
• Addresses a key EC mode of failure: not knowing what exists
• Basis for metrics, evaluation, identification of gaps, planning
Milestones
• Staging metadata aggregation
• Documentation refinement
• User interfaces
• Community participation (community resource inventories)
60. Staging
Database
Document processing
components
Harvest adapters
Public access
components
Harvest adapters: components that connect to
information sources and import descriptions of
EarthCube resources into the staging database.
Staging Database: document database that persists the
originally harvested descriptions in their native state, as
well as any additional information or updates resulting
from subsequent processing/curation of the description
Document processing components: components that
pull documents from the staging database, perform
various functions to upgrade content or transform
presentation. The processed document may be pushed
back to the staging database or out to the public access
components
Public access components: components that connect to
document processors and implement external interfaces
to present content for users
Interfacestotheworld
Resource descriptions
Ye Most Excellent EarthCube Inventory System
Modular components
63. To simplify
data discovery
▪ Standard and simplified web services supporting space-
time (and more) queries
Data access
▪ Simplified services also mean simple clients
▪ PERL, MatLab, R, wget, etc
Data Usability
▪ When possible standard widely used formats will be
supported and when reasonable text output formats will
be available to aid in interdisciplinary access
64. Identical or similar access to data resources
across 14 different GEO data collections
Both domestic and international
Expansion of the RAMADDA system to
support long-tail of science data
Data integration for one use case scenario
66. Standardized space-time queries for 14
geosciences data types/centers
Data discovery client
Standardized documentation
URL builders
GUI to URL builders to provide proper URL
construction
Development of Simple clients
Standard and Simple cross-domain formats
developed
67.
68. BCube: A Broker Framework
for Next Generation Geoscience
An EarthCube Amendment II
Building Block Award
69. Aims of the Brokering Building Block
(BCube) Project
• Facilitate the discovery, access and use of data and
information needed by geoscientists working across
disciplinary boundaries
– By mediating (i.e. brokering) interactions between
disciplinary resources (data stores, web-based services)
– In a manner that does not impose requirements on the
providers of those resources
• Document, understand, and suggest ways to enhance
uptake of CI developments by geoscientists
2
70. How BCube Will Contribute to the
Success of EarthCube
• Demonstrate
– Increased efficiency of geoscientists using the
brokering framework
– Ability to interconnect major disciplinary data
repositories (weather, hydrology, oceans, polar)
– Enhanced data utilization by early career scientists
and education professionals
• Exploring sustainability models for EarthCube
middleware (core infrastructure)
3
73. Phase 1: Describe water & atmospheric
properties over a domain of space and time
• History
• Current conditions
• Forecasts
Precipitation
Evaporation
Soil Moisture
Streamflow
Groundwater
Reservoirs
• Discrete spatial domains: GIS features (point, line and area) with observations & measurements
• Continuous spatial domains: Grids of measured or modeled variables in geophysical fluid sciences
• Spatially discrete or continuous data may also vary discretely or continuously in time:
one-time samples vs. random points of time vs. regularly spaced intervals of time
EC BB for Integrating Discrete & Continuous Data
David Arctur, Univ of Texas at Austin, February 2014 (DisConBB)
Phase 2: Apply concepts and
methods in other domains
• Solid Earth
• Cryosphere
• Oceans
Common Information Model
+
Data migration
+
Server & user tools
74. Prototype: Soil Moisture Map & Time Series
This is a common pattern across geosciences –
• Solid Earth: seismic activity, soil chemistry over deep time, …
• Oceans: SST, acidification, …
• Cryosphere: ice thickness, trapped gas content, ...
75. 2014 Outreach
Workshop 1
CUAHSI + Unidata
Users Committees
Examine
interoperability of
hydrologic &
atmospheric data
Tasks for 2014-2015
UT Austin + CUAHSI + Unidata + BYU
2014 Deliverables:
– Information model, server & client tools, and web architecture documentation
– Outreach Workshop 1 – Austin, summer/fall: Hydro + Atmospheric communities
2015 Tasks & Deliverables:
– Continue development based on workshop results; what further work is needed?
– Coordinate with Solid Earth, Oceans, and Cryosphere domains & scenarios
– Outreach Workshop 2 – Boulder, summer/fall: All participating communities
Visualize
and
analyze
Store water
data time
series in
netCDF;
develop
server-based
conversion
tools
Develop
common
Information
Model:
• CUAHSI
Ontology;
• OGC web
services &
WaterML2;
• CF
Conventions
Metadata
& Data
Services
Discovery &
Access
Broker
BCube / GEOSS
EC BB
76.
77. February 2014 – Boulder, CO – Pascal Hitzler
OceanLink Building Block:
Leveraging Semantics and Linked Data
for Geoscience Data Sharing and
Discovery
Pascal Hitzler
DaSe Lab for Data Semantics
Wright State University
http://www.pascal-hitzler.de
78. February 2014 – Boulder, CO – Pascal Hitzler 2
OceanLink collaborators
Robert Arko, Columbia University
Suzanne Carbotte, Columbia University
Cynthia Chandler, Woods Hole Oceanographic Institution
Michelle Cheatham, Wright State University
Timothy Finin, University of Maryland, Baltimore County
Pascal Hitzler, Wright State University
Krzysztof Janowicz, University of California, Santa Barbara
Adila Krisnadhi, Wright State University
Thomas Narock, Marymount University
Lisa Raymond, Woods Hole Oceanographic Institution
Adam Shepherd, Woods Hole Oceanographic Institution
Peter Wiebe, Woods Hole Oceanographic Institution
The presented work is part of the NSF OceanLink project:
EarthCube Building Blocks, Leveraging Semantics and Linked Data
for Geoscience Data Sharing and Discovery
79. February 2014 – Boulder, CO – Pascal Hitzler 3
Cost of data reuse
Weak/no
conceptual model
Strong/monolithic
conceptual model
High reuse cost
Low reuse cost
80. February 2014 – Boulder, CO – Pascal Hitzler 4
EarthCube requires
• information integration
• interoperability
• conceptual
modeling
• intelligent
search
• data-model
intercomparison
• data publishing
support
Semantic Web studies
• information integration
• interoperability
• conceptual
modeling
• intelligent
search
• data-model
intercomparison
• data publishing
support
Pascal Hitzler, WSU; Krzysztof Janowicz, UCSB
81. February 2014 – Boulder, CO – Pascal Hitzler 5
Flexible, extendable approach
Ontology Design Patterns
R2R BCO-DMO MBLWHOI
Library
NSF
UI Views
User Interface
mappings
…
82. February 2014 – Boulder, CO – Pascal Hitzler 6
Thanks!
www.oceanlink.org
83. February 2014 – Boulder, CO – Pascal Hitzler 7
References
• BCO-DMO: Biological & Chemical Oceanography Data
Management Office, http://www.bco-dmo.org/
• R2R: Rolling Deck to Repository, http://www.rvdata.us
• OceanLink website and publications are forthcoming at
http://www.oceanlink.org/
• Yingjie Hu, Krzysztof Janowicz, David Carral, Simon Scheider,
Werner Kuhn, Gary Berg-Cross, Pascal Hitzler, Mike Dean, Dave
Kolas, A Geo-Ontology Design Pattern for Semantic Trajectories.
In: Thora Tenbrink, John G. Stell, Antony Galton, Zena Wood
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