Ontologic View of Earth Sciences Why ontologies Ontologic View of Earth Sciences Why ontologies? EarthCube’s Ontology and Semantic Web Workshop Ballston, VA April 30-May 1, 2012 X L Y L Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012 Hassan Babaie1, 2 and Raj Sunderraman2 1Department of Geosciences, Georgia State University 2Department of Computer Science, Georgia State University

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

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

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

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

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

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

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) Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012 subject predicate (property) object inContactWith ReservoirRock Caprock

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 Need to map the building blocks of scientific knowledge (facts) into the building blocks of ontologies (RDF triples) in OWL composition Ore Mineral Object properties level Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012 crystallizeInto Magma IgneousRock depth Lake 1000 m Datatype Properties richterMagnitude Earthquake 8.1

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: 10-3-106 m) Groundwater contains Process containedIn recharge Precipitation Aquifer Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012 subPropertyOf permeability 10-12 m2 isA infiltrate Raining porosity 0.16

Processes change state of objects ThermalProperty OpticalProperty thermProp opticProp physProp chemProp PhysicalProperty EarthMaterial ChemicalProperty isA melt meltProduct Solid Melting Liquid gasProduct Gas condition Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012 isA isA Rock Magma MeltingCondition hasPart partOf 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) Mineral

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? Earth science level Discipline level Hassan Babaie & Raj Sunderraman EarthCube's "Ontology and Semantic Web" Workshop, April 30-May 1, 2012 Sub-discipline level To individual level Which technology can achieve the optimum solution to reach the goals of EarthCube?

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

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

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

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

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