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Semantic Technologies: Activities and Impacts (TIWG Sub-Group)

Semantic Technologies: Activities and Impacts (TIWG Sub-Group). Brian Wilson (Mike Little) Hook Hua. ESDSWG Meeting November 13 – 15, 2012 Annapolis, MD. Semantic Technologies. Semantics – more than just OWL/RDF semantic web stack Web mining using text understanding (auto-classification)

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Semantic Technologies: Activities and Impacts (TIWG Sub-Group)

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  1. Semantic Technologies:Activities and Impacts(TIWG Sub-Group)

    Brian Wilson (Mike Little) Hook Hua ESDSWG Meeting November 13 – 15, 2012 Annapolis, MD
  2. Semantic Technologies Semantics – more than just OWL/RDF semantic web stack Web mining using text understanding (auto-classification) Topic & keyword extraction: DBpedia Spotlight, OpenCalais, etc. Linked Open Data (LOD) RDF data graphs published on open Internet Data integration by simply merging triples SPARQL query endpoints, explore logical triples Return JSON for web mashups Extending Ontologies (OWL) E.g.: Concepts from SWEET, Noesis, W3C PROV for provenance Semantic mediation using ontologies Query terms broaden/narrow, synonyms, OWL “SameAs” Graph Visualization Provenance, collaboration, joint authorship, social network
  3. Semantic Web Stack Linked Open Data (LOD)
  4. Resource Description Framework (RDF) Built on the logical triple, a 3-tuple consisting of Subject, Predicate, and Object Example graph below: Resource: Some entity. Property: An attribute of a resource. Literal: A string of characters which can be the value of a property. <http://www.example.org/index.html> <http://purl.org/dc/elements/1.1/creator> <http://www.example.org/staffid/85740> . <http://www.example.org/index.html> <http://www.example.org/terms/creation-date> "August 16, 1999" . <http://www.example.org/index.html> <http://purl.org/dc/elements/1.1/language> "en" .
  5. TouchGraph: Facebook social graph
  6. Activities of the Group Developing “killer apps” for semantics Demo session at Jan. 2012 ESIP Federation meeting Evolving “best practices” and tools experience Jena API, Protégé, COE, Virtuoso, SPARQL, LODSpeakr Extending ontologies (joint with ESIP Semantic Web Cluster) Future of SWEET maintenance OWL/RDF vocabularies for the AGU app. Publishing NASA metadata as Linked Open Data (LOD) Prototype publication of LOD for ECHO collections, GCMD services New interfaces: “Instant Browse” of ECHO collections Proposed (future) community task for consideration: “Publishing NASA Metadata for Semantic Mashups”
  7. Linked Data Publication (5 stars) Make your stuff available on the web (whatever format) Make it available as structured data (e.g. excel instead of image scan of a table) Non-proprietary format (e.g. csv instead of excel) Use URLs to identify things, so that people can point at your stuff Link your data to other people’s data to provide context LOD is about authoring “rich linkages” between data Use of URIs/URLs to permanently identify resources is crucial! Things that should have a permanent URL: Every NASA dataset registered in GCMD & ECHO All registered services and tools AGU authors, meeting abstracts, sessions AGU journal articles (DOIs)
  8. Linked Open Data
  9. Benefits of Open Metadata Both LOD and “casting” technologies free our metadata Openly published on the web in interoperable formats Objects are permanently named by URI GCMD, ECHO, DAACs should use their HTTP namespaces The real estate “grab” on the web has already occurred Any third-party can make logical assertions about your objects Crowdsource“rich linkages” between metadata objects E.g.: tools to datasets, datasets to all relevant web services, science papers to datasets used, granule to QC annotations, people/projects graph to find new collaborators. Semantic Mashups as “killer apps” Event Linkages: phenomenon, data, services, tools, human impacts [Your APP here.]
  10. Application Demonstrations Demo session at Jan. 2012 ESIP meeting Linked Open Data for AGU Abstracts, Sessions, & People (Eric Rozell, Tom Narock) LOD, text understanding (Dbpedia), SPARQL The ESIP Collaboration Network (Erin Robinson) social graph, visualization, data integration Noesis 2.0: Smart Search for Collections & Services (Rahul Ramachandran) query expansion by ontology, meta-search, topics, user taxonomies Saving & Querying Production Provenance Graphs using the Earth Science extension to W3C PROV standard (Hook Hua) PROV-ES ontology, RDF graphs, SPARQL, viz Graph Visualization Tools (Ruth Duerr, Joe Glassy) RDF viz. tools
  11. Application Demonstrations (2) DQSS: Data Quality Screening Service (Chris Lynnes) Ontology for applying pixel-level quality screening Spy Glass - Ontology based text mining (Rahul Ramachandran, John Rushing) Hybrid system for text understanding
  12. AGU App: Sessions, Abstract, Authors AGU Meeting at a Glance: Web app. for iPhone and browser
  13. OWL/RDF Vocabularies foaf – Friend of a Friend dc – Dublin Core swrc – Semantic Web for Research Communities swc – Semantic Web Conference tw – Tetherless World geo – WGS84 Lat/Long sweet – Semantic Web for Earth & Environmental Terminology skos – Simple Knowledge Organization System xsd – XML Schema ao – Annotation Ontology
  14. ESIP Collaboration Network
  15. Noesis 2.0: Ontology-Enhanced Search Broaden Terms Search Multiple Sources
  16. PROV-ES: Processing Graph Each process “Uses” its input files and “Generates” its output files ACCESS-2009 project, PI Hook Hua (JPL)
  17. App. Demos in Telecons VisKo: Semantic Auto-Composition of Visualization Workflows (D. Pennington, Nicholas Del Rio; UTEP) Automate format conversions, selection of viz. type, data transforms Instant Browse of ECHO Collection Metadata (B. Wilson) Publish as LOD for mashups (prototype) ToolMatch (C. Lynnes) Match datasets to tools that manipulate them Session at the July ESIP Federation meeting
  18. VisKo: Auto-Construction of Workflows
  19. Richer Linkages Needed Knowledge Algorithms & Processing Peer-rev. Journals ATBD’s Tools Services: OGC/WXS, DAP Quality Control Equations AGU Sessions Panoply ? GCMD, ECHO DAACs, SIPs DQSS Meeting At-a-Glance App Tool Match Variables AGU Authors Collections Granules ESIP LinkedIn Data People have Roles.
  20. Recommendations Openly Publish All NASA Metadata Collection & Data Casting, Service Casting, Event Casting Linked Open Data Continue to Develop “Killer Mashups” Tools to datasets Datasets to all relevant services (OpenSearch, WMS, DAP) Science publications to datasets/variables used Granules to Quality Control annotations (by DAACs & users) AGU/ESIP People/papers/projects collaboration graph  recommend new collaborators and papers to read [YOUR App HERE.]
  21. Publish ECHO Collections as LOD LODSpeakr and other tools provide generic browse or custom apps.
  22. Instant Browse of ECHO Collections Drill-down by semantic facets and keyword search, with instant results
  23. Instant Browse of GCMD Services Drill-down by semantic facets and keyword search, with instant results
  24. Event Cast Browser with KML Layers Cyclone Tracks for Western Pacific in 2011 – with A-Train L2 Variables Carbon Cycle
  25. Augmenting Event Casts On-the-Fly A Near Real-Time Mashup Standards & Tools Reused: Event or Pattern Observed Event Cast format: Atom, xlink Carbon Cycle georss Publish Event Cast w/ geoloc & time LOD Subscribers Receive Announcement ECHO Mirador NSIDC etc. CollectionInstant Browse, Select Datasets/Variables Space/time Locations Third-Parties Iterate GranuleOpenSearch, Link to OPeNDAP URL’s Augmented Cast Linking to Variables Visualize variable, generateKML Layers Link to KML version of cast Re-publish augmented casts
  26. Community Proposal for WG
  27. Community Proposal for WG (2)
  28. Community Proposal for WG (3)
  29. Recommendations Openly Publish All NASA Metadata Collection & Data Casting, Service Casting, Event Casting Linked Open Data Continue to Develop “Killer Mashups” Tools to datasets Datasets to all relevant services (OpenSearch, WMS, DAP) Science publications to datasets/variables used Granules to Quality Control annotations (by DAACs & users) AGU/ESIP People/papers/projects collaboration graph  recommend new collaborators and papers to read [YOUR App HERE.]
  30. Backup
  31. Federated OpenSearch: (1) Find Collections Search multiple sources: ECHO, MIRADOR, GHRC, NSIDC, PO.DAAC, etc.
  32. Federated OpenSearch: (2) Find Granules Search multiple sources: ECHO, MIRADOR, GHRC, NSIDC, PO.DAAC, etc.
  33. Publish GCMD Datasets (DIFs) as LOD LODSpeakr and other tools provide generic browse or custom apps.
  34. Publish GCMD Services (SERFs) as LOD LODSpeakr and other tools provide generic browse or custom apps.
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