Lightning Talks: All EartCube Funded Projects


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Lightning Talks: All EartCube Funded Projects

  1. 1. EARTHCUBE FUNDED PROJECTS: LIGHTNING TALKS EarthCube Portfolio Workshop Boulder CO February 12-14, 2014
  2. 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. 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. 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”
  5. 5. C4P Cyberinfrastructure for Paleobiosciences
  6. 6. 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.
  7. 7. C4P: Challenges • A typical ‘Long-tail’ community: Much fossil data are ‘dark’ • Many databases & informatics efforts, but little coordination or interoperability
  8. 8. 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
  9. 9. 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.
  10. 10. 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
  11. 11. C4P: Activities
  12. 12. C4P: Activities • Outreach via Social Media • Twitter: #EarthCubeC4P • EarthCube Website: • YouTube Channel: • Discussion group:
  13. 13. 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)
  14. 14. 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: Deadline: March 10th e-mail applications to
  15. 15. 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  
  16. 16. 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  
  17. 17. 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  
  18. 18. SEN  milestones  and  deliverables    hp://­‐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  
  19. 19. 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…
  20. 20. 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
  21. 21. 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
  22. 22. 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
  23. 23. 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 … … … …
  24. 24. 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
  25. 25. EarthCubeEnterpriseArchitectureOverview Overarchingaspectsofarchitecturethatrelateto EarthCubeEnterpriseArchitecture EarthCubeArchitectureDictionary Articulatethedatarelationshipsandalignment structuresintheEarthCubeArchitectureContent TechnicalStandards ArticulateapplicableOperationalandTechnical standardsandguidance EarthCube Operational Articulate EarthCube operational scenarios, processes, activities and requirements EarthCube Services Articulate the performers, activities, services, and their exchanges providing for, or supporting EarthCube functions EarthCube Systems Articulate the legacy systems or independent systems, their composition, interconnectivity, and context providing for or supporting EarthCube functions EarthCubeProject ExemplifyhowtousetheEarthCubeEA toGuideProjectDesign 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 Capability Articulate the capability requirement, delivery timing, and deployed capability
  26. 26. 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
  27. 27. 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
  28. 28. 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
  29. 29. 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)
  30. 30. 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.
  31. 31. 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
  32. 32. 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
  33. 33. 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.
  34. 34. A Rough Time Table
  35. 35. 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
  36. 36. 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
  37. 37. 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.
  38. 38. Problems: (II) Reproducibility
  39. 39. 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
  40. 40. Fully coupled multi-process model Edited by CDuffy 11 Feb 14 2:56pm Push API (to CSDMS and others
  41. 41.
  42. 42. 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
  43. 43. 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)
  44. 44. 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.
  45. 45. 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
  46. 46. 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
  47. 47. 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
  48. 48. 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
  49. 49. 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)
  50. 50. 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
  51. 51. EarthCube Building Blocks –Web Services
  52. 52.  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
  53. 53.  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
  54. 54. WS- BB IRIS UNAVCO CUAHSI SDSC Columbia IEDA Unidata Caltech GPlates CINERGYB-Cube GGP UTEP Gravity Inter Magnet Structural Geology NEON NGDC OOI WOVODAT RAMADDA LongTail Data
  55. 55.  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
  56. 56. BCube: A Broker Framework for Next Generation Geoscience An EarthCube Amendment II Building Block Award
  57. 57. 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
  58. 58. 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
  59. 59. Key Milestones and Deliverables 4
  60. 60. 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
  61. 61. 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, ...
  62. 62. 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
  63. 63. 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
  64. 64. 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
  65. 65. 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
  66. 66. 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
  67. 67. February 2014 – Boulder, CO – Pascal Hitzler 5 Flexible, extendable approach Ontology Design Patterns R2R BCO-DMO MBLWHOI Library NSF UI Views User Interface mappings …
  68. 68. February 2014 – Boulder, CO – Pascal Hitzler 6 Thanks!
  69. 69. February 2014 – Boulder, CO – Pascal Hitzler 7 References • BCO-DMO: Biological & Chemical Oceanography Data Management Office, • R2R: Rolling Deck to Repository, • OceanLink website and publications are forthcoming at • 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. •
  70. 70. 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.
  71. 71. 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.