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Ontologic View of Earth Sciences Why ontologies? EarthCube’s Ontology and Semantic Web Workshop Ballston, VA April 30-May 1, 2012 Hassan Babaie 1, 2 and.

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Presentation on theme: "Ontologic View of Earth Sciences Why ontologies? EarthCube’s Ontology and Semantic Web Workshop Ballston, VA April 30-May 1, 2012 Hassan Babaie 1, 2 and."— Presentation transcript:

1 Ontologic View of Earth Sciences Why ontologies? EarthCube’s Ontology and Semantic Web Workshop Ballston, VA April 30-May 1, 2012 Hassan Babaie 1, 2 and Raj Sunderraman 2 1 Department of Geosciences, Georgia State University 2 Department of Computer Science, Georgia State University X L Y L Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012

2 The Earth is a system composed of major, globally interconnected complex components: Atmosphere Hydrosphere Biosphere Geosphere Cryosphere Each has its own sub-components Earth Systems Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012

3 5 Interacting components Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012

4 Hydrosphere Cryosphere Atmosphere BiosphereGeosphere Process Earth’s major components interact through processes Earth scientists study the components and their parts at all scales Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012

5 These unintegrated data actually stand in the way of both discovering new knowledge and raising new questions regarding the unknown In other words, the un- utilized facts in these data prevent us from knowing what we do NOT know! There are immense volumes of data collected from each Earth system Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012

6 Self-similar Research The self-similarity that characterizes the research of interacting Earth science communities, and that of many geological processes, requires: Fractal structuring of resources: e.g., software, database, ontology, service, tools From groups of individuals to progressively larger communities, on the Earth science network Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012

7 What’s the Problem? Understanding of data in databases requires effective accessibility, query mechanism, usability, and post-search visualization by scientists Integration of the heterogeneous schema and vocabulary of these distributed databases requires significant programming, at high cost Knowledge management systems, dependent on these distributed and heterogeneous databases, if they exist, can only be scaled with difficulty and significant cost through constant updates Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012

8 Motivation for the RDF Data Model Most of Earth science Knowledge is available in publications Information is distributed and fragmented No means to efficiently browse/search this knowledge Structured data in relational database (RDB) systems do not carry semantics (meaning) Changes in representation would cause the database schema to change Making software interoperable and the RDB and other data types (text, HTML) machine understandable requires conversion of their data type into the Semantic Web RDF data model in the form of triples in ontologies (subject-predicate-object) subject predicate (property) object inContactWith ReservoirRock Caprock Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012

9 composition crystallizeInto depth Earth System Science approach At each scale, Earth’s interacting complex objects are investigated by Earth scientists at their atomic or sub- component levels. Goal: Integrate data and knowledge units (facts) from the subsystem level and apply them to the global scale, i.e., to the whole Earth system Magma IgneousRock Ore Mineral Lake 1000 m Earthquake 8.1 richterMagnitude Object properties level Datatype Properties Need to map the building blocks of scientific knowledge (facts) into the building blocks of ontologies (RDF triples) in OWL Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012

10 containedIn permeability porosity Translate facts about both spatial objects and spatio- temporal objects (processes) Complex and simple objects communicate through processes; some occurring over several orders of magnitude (e.g., Faulting: 10 -3 -10 6 m) infiltrate Precipitation Aquifer recharge Raining isA Groundwater 10 -12 m 2 0.16 contains Process subPropertyOf Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012

11 hasPart partOf thermProp opticProp physPropchemProp gasProduct meltProductmelt Processes change state of objects Melting Solid Rock isA Liquid Mineral MeltingCondition Magma isA condition EarthMaterial ChemicalProperty isA PhysicalProperty OpticalPropertyThermalProperty Gas Data about specific instances of these interactions, which are stored in domain databases and other kinds of files, can readily be converted into RDF data model (e.g., through RDB-to-RDF wrappers) Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012

12 Unintegrated Communities of Research How many levels of ontology do we want to build? Do we need a system for faster/easier integration of smaller communities, or one to allow wider inter-operability among larger communities, or both? To individual level Earth science level Discipline level Sub-discipline level Which technology can achieve the optimum solution to reach the goals of EarthCube? Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012

13 Minimum Requirements A mechanism to globally identify and integrate data from variably-sized, locally-integrated but globally-distributed nodes of Earth scientists One solution: Linked Open Data (LOD) Cloud Support mapping/integration of globally distributed community databases, text, etc. Provide ways to discover/use data stored in these local and Web-distributed databases by both Earth scientists and software agents Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012

14 Requirements cont’d Develop ways to convert Web documents and paper and digital scientific publications into machine interpretable formats (e.g., RDF) Include all aspects of scientific research about the data (metadata) in ontologies, such as: provenance, assumptions, quality, error, precision, accuracy, uncertainty Support distribution, discovery, use, and reuse of ontologies) in all fields. Encourage the use of the controlled vocabularies in domain database Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012

15 Let data come to us Linked Open Data Cloud Use the linked data space to connect the RDF data models of all Earth science communities The cloud will incrementally foster public trust through transparency and community involvement It will allow community driven, Wikipedia type, RDF data curation, to guarantee maintenance of, and access to, high quality, relevant and trusted information Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012

16 New data published will include multiple RDF links to the geospatial nodes on the LOD Cloud, such as GeoNames and Linked GeoData. These links allow additional data to be discovered from the cloud. The current position is used to search all the linked data in a query. We can publish our current position, images, and descriptions, say of an outcrop, to the cloud while standing on/by the outcrop Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012

17 X L Y L Thank you! Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012


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