1. U.S. Department of the Interior U.S. Geological Survey CDI Webinar Sept. 5, 2012 Janice Gordon September 5, 2012 Semantic Technologies for Integrating USGS Data

2. Science Support Framework

3. 3 CDI Webinar Sept. 5, 2012 1. Learn about Semantic Web technologies 2. Integrate sample data sets using a common ontology 3. Develop a semantic data integration prototype application Project Goals

4. 4 CDI Webinar Sept. 5, 2012 “the idea of having data on the web derived and linked in a way that it can be used by machines not just for display purposes, but for automation, integration and reuse of data across various applications” Tim Berners-Lee (2001) “The main idea of the semantic web is to support a distributed web at the level of data rather than at the level of presentation” Semantic Web for the Working Ontologist (2011) What is the Semantic Web?

5. “Generic” WebSemantic Web 1Viewpoint of a PersonViewpoint of a Machine 2Web of Documents (web pages) Web of Data 3Presents Documents to People Makes Data Meaningful to Machines 4Hypertext Markup Language (HTML) Resource Description Framework (RDF) 5HTML Describes SyntaxRDF represents Semantics (meaning) 6WikiPediaDBPedia

6. Past, Present, Future(?) of The Web

7. 7 CDI Webinar Sept. 5, 2012  We knew the technologies we wanted to learn about  We had a team and some data sets in mind  Aquatic Bioassessment Data for the Nation (BioData)  Mineral Resources Online Spatial Data (MrData)  Mulitstate Aquatic Resources Information System (MARIS)  National Hydrography Dataset (NHD)  We Wanted to Use a Known Methodology Let’s Use a Development Methodology

8. Semantic Web Methodology & Technology Development Process Graphic Credit & Copyright: Dr. Peter Fox, Rensselaer Polytechnic Institute (RPI) Methodology

9. 9 CDI Webinar Sept. 5, 2012 Goal: Combine data from a variety of sources into a single dataset to support aquatic habitat research of freshwater fish species in the Susquehanna River Basin. Summary: Studies of aquatic fish ecology and habitat requirements depend on the availability and effective use of disseminated and heterogeneous data assets. Data often need to be integrated in order to build new knowledge about habitat conservation and rehabilitation. In this use case a biologist needs access to combined data about the Susquehanna River Basin that are currently contained in disparate databases. The data needed describe (1) the abundance of freshwater fish; (2) hydrology of the river basin region; (3) water quality and contaminant data; and (4) historical stream sediment geochemical data. The goal is to enable a modeler to understand the relation of fish populations to major habitat contaminants in the Susquehanna River Basin through the combination of these data assets. Defining the Use Case

10. Semantic Web Methodology & Technology Development Process Graphic Credit & Copyright: Dr. Peter Fox, Rensselaer Polytechnic Institute (RPI) Methodology

11. Heterogeneous Information Models NHD BioData MARIS MRDATA

12. Open Geospatial Consortium: Observations & Measurements Ontology (O & M) OBSERVATION Capturing Event FEATURE OF INTEREST target object PROCEDURE Description of the capturing process RESULT The captured data OBSERVED PROPERTY What was measured?

13. O & M Observation Example Standard Length Observation BDB- 00032488 Specimen 1 FISH SPECIMEN 1 MINNOW SEINE 27 mmSTANDARD LENGTH Feature of Interest Procedure Result Observed Property OBSERVATION

14. Example in RDF a om:Observation, usgs:TotalLengthObservation; om:featureOfInterest ; om:observedProperty usgs:total_length ; om:result [ a basic:Length, usgs:TotalLength; basic:number "27"^^xsd:float; basic:unit ]. a sam:Process. a sam:Specimen, usgs:Fish ; sam:samplingMethod ; usgs:fromCollection ; rdfs:label "fish #1".

15. Semantic Web Methodology & Technology Development Process Graphic Credit & Copyright: Dr. Peter Fox, Rensselaer Polytechnic Institute (RPI) Methodology

16. 16 CDI Webinar Sept. 5, 2012 High Level Architecture Apache Jena Framework a configurable way to access RDF data using simple RESTful URLs that are translated into queries to a SPARQL endpoint

17. Semantic Web Methodology & Technology Development Process Graphic Credit & Copyright: Dr. Peter Fox, Rensselaer Polytechnic Institute (RPI) Methodology

18. 18 CDI Webinar Sept. 5, 2012  Phase 1: Ontology Development and Data Transformation  Phase 2: Technical Infrastructure Implementation  Phase 3: Backend Services & Client UI Development  Phase 4: Visualization of Integrated Data Prototype Development  

19. The Prototype… So Far, So Good

20. 20 CDI Webinar Sept. 5, 2012  Finish the Prototype Development  Create and Post Technical Documentation  Publish Open File Report Next Steps…

21. Development Team James Curry Mini Mathew Bruce Powell Julie Recker Jeff Wendel Brad Williams Project Collaborators Project Group Nina Chkhenkeli James Curry Dave Govoni Fran Lightsom Andrea Ostroff Peter Schweitzer Phethala Thongsavanh Dalia Varanka Stephan Zednik Lisa Zolly

22. 22 CDI Webinar Sept. 5, 2012 janicegordon@usgs.gov https://my.usgs.gov/confluence/display/cdi/Se mantic+Web+Working+Group Thanks!