Lightning Talks: All EartCube Funded Projects
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Transcript of Lightning Talks: All EartCube Funded Projects
EARTHCUBE FUNDED PROJECTS: LIGHTNING TALKS
EarthCube Portfolio WorkshopBoulder COFebruary 12-14, 2014
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 GeorgiaBurcu Bolukbasi, UIUC
Nosh Contractor, Northwestern UniversityLeslie DeChurch, Georgia Tech University
Courtney Flint, Utah State UniversityGabe Gershenfeld, Cleveland Indians
Michael Haberman, UIUCJohn L. King, University of Michigan
Eric Knight, University of SydneySpenser Lewis, General Dynamics
Barbara Lawrence, UCLAEthan Masella, Brandeis Uniersity
Charles Mcelroy, Case Western Reserve University
Barbara Mittleman, Nodality, Inc.Mark Nolan, UIUC
Melanie Radik, Brandeis UniversityNamchul Shin, Pace University
Susan Winter, University of MarylandIl Z l k UCSD
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
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 professionalassociations
Facilitation support for chartering/instantiation ofEC assembliesScholarly articles on “Cooperation and competition
in the Geosciences,” “Vies on standards,” and others2015 Elements of a theory framework for the “science of
scienceinstitutions”
C4PCyberinfrastructure for Paleobiosciences
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.
C4P: Challenges• A typical ‘Long-tail’ community: Much fossil data are ‘dark’• Many databases & informatics efforts, but little
coordination or interoperability
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
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.
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
C4P: Activities
C4P: Activities• Outreach via Social Media
• Twitter: #EarthCubeC4P• EarthCube Website: http://workspace.earthcube.org/c4p• YouTube Channel: http://www.youtube.com/cyber4paleo• Discussion group: [email protected]
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)
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; ShananPeters, 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/workshopsDeadline: March 10th
e-mail applications to [email protected]
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
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
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
SEN milestones and deliverables h\p://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
Enterprise Architecture forTransformative 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 ActivitiesUsage
Log
Recommendations Impact
Analysis
PublicationDiscussionData useData revisionAnnotation…
PeopleModelsData…
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
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
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
User Interfaces
Applications
Data
Services
GeoscientistsEarthCube Administrator Educators
On-Demand Work-Flow Chaining Layer
Interdisciplinary Data & Business Interoperability Layer
GeologicalGeophysical Biological Climatology
Data and Information Provenance
Geospatial Portal
Geochemistry PetrologySedimentology
… …
Modeling Capability
Big Data Analytics
Pre and Post Processing
Public
Generic CI Services
Data Discovery
Data Access
Data Visualization
Data PublicationModeling
Geological Portal
Modeling GUI
Rivers Portal
Citizen Science Portal
Seismic Portal
… …
… …
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 ModelLogical Data Model
Technical Standards
EarthCube Enterprise Architecture Overview
Overarching aspects of architecture that relate to
EarthCubeEnterprise Architecture
EarthCube Architecture DictionaryArticulate the data relationships and alignm
ent structures in the EarthCube Architecture Content
Technical StandardsArticulate applicable O
perational and Technical standards and guidance
EarthCube OperationalArticulate EarthCube operational
scenarios, processes, activities and requirements
EarthCube ServicesArticulate the performers, activities,
services, and their exchanges providing for, or supporting EarthCube functions
EarthCube SystemsArticulate the legacy systems or
independent systems, their composition, interconnectivity, and context providing for
or supporting EarthCube functions
EarthCube ProjectExem
plify how to use the EarthCube
EA to G
uide Project Design
Volume I Volume III Volume II Volume IV
Overall Aims of the Project
Our Conceptual Design project targets the conceptual design of an EarthCube enterprise architecture to facilitate data communication and human collaboration in pursuit of collaborative geosciences.
EarthCube CapabilityArticulate the capability requirement,
delivery timing, and deployed capability
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
Milestones and Deliverables
EarthCube Design Initial Write-up
Volume I Overview and Summary InformationVolume II EarthCube Cyberinfrastructure Architecture Design: System, Operation, and StandardsVolume III EarthCube Enterprise Architecture DictionaryVolume IV EarthCube EA Use Case – Polar CI Project
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
EarthCube Building Block ODSIP: Open Data Services Invocation
ProtocolDave Fulker (OPeNDAP), PI
Mohan Ramamurthy (Unidata), Co-PISenior Personnel: Brian Blanton (RENCI), Steve
Businger (U-Hawaii), Peter Cornillon (U-Rhode Island)
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.
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
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
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 supporttheir creation.
• The ODSIP project will contribute toward addressing challenges EarthCube faces toward truly transforming multiscale and multidisciplinary research and education.
A Rough Time Table
Software Stewardship for GeosciencesPrincipal Investigators:
Christopher J. DuffyDepartment of Civil and Environmental Engineering, Penn State University
Yolanda GilInformation Sciences Institute, University of Southern CaliforniaDepartment of Computer Science, University of Southern California
James D. HerbslebInstitute for Software Research, Carnegie Mellon University
Chris A. MattmannNASA Jet Propulsion LaboratoryDepartment of Computer Science, University of Southern California
Scott D. PeckhamDepartment of Hydrologic Sciences, University of Colorado
Erin RobinsonFoundation for Earth Science
NSF ICER-1343800
geosoft.earthcube.org
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
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.
Problems: (II) Reproducibility
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
Fully coupled multi-process model Edited by CDuffy11 Feb 14 2:56pm
Push API(to CSDMS and others
http://www.isi.edu/ikcap/geosoft/ontology/csdms.owl
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
Earth System BridgeAn NSF funded EarthCube Building Block
Scott Peckham, CU-Boulder, PICo-PIs
Jennifer Arrigo (CUAHSI), Cecelia Deluca (NOAA, CIRES), David Gochis (NCAR), Rocky Dunlap (GA Tech), Anna
Kelbert & Gary Egbert (OSU), Eunseo Choi (Memphis)
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 existingresources. 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.
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-OperationsOperations-to-Research
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
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
Community Inventory of EarthCubeResources 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 teamhttp://workspace.earthcube.org/cinergi
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)
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
Inte
rfac
es to
the
wor
ld
Resource descriptions
Ye Most Excellent EarthCube Inventory System
Modular components
EarthCube Building Blocks – Web Services
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
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
WS-BB
IRIS UNAVCO
CUAHSISDSC
ColumbiaIEDA
Unidata
CaltechGPlates
CINERGYB-Cube
GGP
UTEPGravity
InterMagnet
StructuralGeology
NEON
NGDC
OOI
WOVODAT
RAMADDA Long Tail Data
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
BCube: A Broker Framework for Next Generation Geoscience
An EarthCube Amendment II Building Block Award
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
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
Key Milestones and Deliverables
4
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 DataDavid 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
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, ...
2014 Outreach Workshop 1
CUAHSI + Unidata Users Committees
Examine interoperability of
hydrologic & atmospheric data
Tasks for 2014-2015UT 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
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
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
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
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
February 2014 – Boulder, CO – Pascal Hitzler 5
Flexible, extendable approach
Ontology Design Patterns
R2R BCO-DMO MBLWHOI Library
NSF
UI Views
User Interface
mappings
…
February 2014 – Boulder, CO – Pascal Hitzler 6
Thanks!
www.oceanlink.org
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 (Eds.): Spatial Information Theory - 11th International Conference, COSIT 2013, Scarborough, UK, September 2-6, 2013. Proceedings. Lecture Notes in Computer Science Vol. 8116, Springer, 2013, pp. 438-456.
• http://ontologydesignpatterns.org
February 2014 – Boulder, CO – Pascal Hitzler 8
References
• Pascal Hitzler, Frank van Harmelen, A reasonable Semantic Web. Semantic Web 1 (1-2), 39-44, 2010.
• Prateek Jain, Pascal Hitzler, Peter Z. Yeh, Kunal Verma, Amit P. Sheth, Linked Data is Merely More Data. In: Dan Brickley, Vinay K. Chaudhri, Harry Halpin, Deborah McGuinness: Linked Data Meets Artificial Intelligence. Technical Report SS-10-07, AAAI Press, Menlo Park, California, 2010, pp. 82-86. ISBN 978-1-57735-461-1. Proceedings of LinkedAI at the AAAI Spring Symposium, March 2010.
• Pascal Hitzler, Markus Krötzsch, Sebastian Rudolph, Foundations of Semantic Web Technologies. Chapman and Hall/CRC Press, 2009.
• Krzysztof Janowicz, Pascal Hitzler, The Digital Earth as Knowledge Engine. Semantic Web 3 (3), 213-221, 2012.
February 2014 – Boulder, CO – Pascal Hitzler 9
References
• Pascal Hitzler, Krzysztof Janowicz, Linked Data, Big Data, and the 4th Paradigm. Semantic Web 4 (3), 2013, 233-235.
• Gary Berg-Cross, Isabel Cruz, Mike Dean, Tim Finin, Mark Gahegan, Pascal Hitzler, Hook Hua, Krzysztof Janowicz, Naicong Li, Philip Murphy, Bryce Nordgren, Leo Obrst, Mark Schildhauer, Amit Sheth, Krishna Sinha, Anne Thessen, Nancy Wiegand, Ilya Zaslavsky, Semantics and Ontologies for EarthCube. In: K. Janowicz, C. Kessler, T. Kauppinen, D. Kolas, S. Scheider (eds.), Workshop on GIScience in the Big Data Age, In conjunction with the seventh International Conference on Geographic Information Science 2012 (GIScience 2012), Columbus, Ohio, USA. September 18th, 2012. Proceedings.
• Krzysztof Janowicz, Pascal Hitzler, Thoughts on the Complex Relation Between Linked Data, Semantic Annotations, and Ontologies. In: Paul N. Bennett, Evgeniy Gabrilovich, Jaap Kamps, Jussi Karlgren (eds.), Proceedings of the 6th International Workshop on Exploiting Semantic Annotation in Information Retrieval, ESAIR 2013, ACM, San Francisco, 2013, pp. 41-44.