integration and representation of geological knowledge with semantic web technologies
DESCRIPTION
Integration and Representation of Geological Knowledge with Semantic Web Technologies. Hassan Babaie Departments of Geosciences & Computer Science, GSU. www.gsu.edu/~geohab. Outline of the talk. Define the Semantic Web (SW) and its benefits Ontological view to the world - PowerPoint PPT PresentationTRANSCRIPT
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Hassan BabaieDepartments of Geosciences & Computer Science, GSU
www.gsu.edu/~geohab
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Outline of the talkDefine the Semantic Web (SW) and its
benefitsOntological view to the worldCategorize real entities into two disjoint setsDefine taxonomy and meronomy of processes
and events and their relational semanticsHow knowledge is modeled in an ontologyWhat is a knowledge baseSemantic Web languages – geological
examples
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Present WebMost of the resources on the current Web are
available in weakly structured form such as text, audio, and video, making it difficult to search, extract, maintain, discover, and view the information content embedded in them
The main aspect of the current document-centric Web is that the information sources which are presented on it, including those automatically generated from databases, often lack semantics, and understanding the meaning of the terms is the responsibility of the knowledgeable human users
These users interpret the meaning of the terms and sentences based on their context and own experience and know-how
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Knowledge infrastuctureThe Semantic Web is transforming the role of the
current Web from carrier of data to consumer and transformer of information and knowledge“Learning is less about getting data than it is about using
the knowledge behind the data!”
We have entered a decade that brings us an era in which societies of ontology-based software agentsAutomatically collect Web content through
Semantic Web services provided by diverse global sources
Process the information coming from distributed knowledge bases and databases, and
Exchange the results with other agents
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Semantic Web Semantic Web helps building models, applying
taxonomies and partonomies, to understand a complex reality, constructing reasoning machines that can draw conclusions from formalized, encoded knowledge (applying language inference rules), and exchanging distributed knowledge on a global scale (applying URI)
A
ED
CB
F Reason Infer
Globally exchange
knowledgeEncode
Knowledge
Complex geological reality
Structure the reality
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Current state of affairsCompounded on the lack of accuracy and
inefficiency in linking the data, the sheer volume of Earth data, collected by modern instruments, requires machine processing, which can be provided with the Semantic Web technologies
Currently, changes that occur in the data of one sub-community or department are commonly not traceable in other parts of the community
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How can the Semantic Web help?Inference, i.e., extracting implicit data from
what is explicitly asserted, is very difficult and challenging using traditional databases, because the semantics of the data is not globally defined
Semantic web can help linking disconnected data, collected by different individuals or groups
In the Semantic Web model, as is in scientific research, “Anyone can say Anything about Any topic” [AAA]
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SW is a specification for data modelingSemantic Web languages, such as OWL and
RDF/S, conform to a well defined set of theorems, with clear meanings (semantics) that are founded on the set theory
So, how can the Semantic Web help? It would allow all data sources and applications, and domain rules to have an RDF (a graph data model) interface, practically providing them with cheaper and automatic global (Web-scale) exposure and integration capability, powerful search, and inherent inference-based reasoning
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Knowledge is the key!Geoscientific knowledge will be
structured to provide meaning for the immense volumes of seemingly unrelated data and information on the web
The Semantic Web technologies allow us to formally structure the knowledge in every discipline as a series of integrable ontologies
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Ontological view to the worldEach part of the Earth system includes
material, concrete things (objects) that exist, at specific times independent and outside of our minds, as substantial individuals (e.g., Brevard Fault zone)
Each object (individual), including the Earth itself, denoted by a special sign or symbol (e.g., a term in natural languages such as ‘fault’), is referenced by a concept that instantiates a universal type (e.g., Fault)
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Individual vs. UniversalWhile objects exist in space and time
(e.g., Brevard Fault), the universal is a construct (e.g., Fault) that exists only in our mind
‘Brevard Fault’ (a symbol), which refers to a specific, real fault (an object) in SE USA, instantiates the universal type ‘Fault’
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PropertiesEvery part of the Earth system, as a
substantial object, is endowed with a series of properties, which represent relationships among objects, and their attributes
The real, individual Brevard Fault is one of many objects in the Fault class, which conform to this universal type by possessing the set of properties that characterizes Fault
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Properties are related = EeScientists have discovered that properties
in a given type are related to each other through physical (natural) laws that are defined for the universal type, and that are themselves complex properties
For example, the linear law of elasticity, that relates stress () and strain (e), applies to rocks deforming at shallow depths, under a restricted range of mechanical and environmental conditions (e.g., low e, , T)
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Types of entitiesEntities occupy space and time
Entities on the surface of the Earth, below its surface, and in the atmosphere around it, can be grouped, based on their mode of existence and persistence, into two general, non-overlapping (i.e., disjoint) categories:
1.Enduring entities (endurants, continuants)2.Perduring entities (perdurants, occurrents)
Entity
Endurant Perdurant
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Enduring entitiesInclude substantial objects (both material
and immaterial) such as:fault, water, gas, subduction zone, mylonite, and cave (an immaterial entity)
Occur in all Earth’s subsystemsHave spatial parts that exist at all time instants, ti
All ordinary things, e.g., fault, rockDatabase record of an outcrop or a
mineral
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Endurants keep identityContinuants endure by preserving
their (same but not necessarily exact) identity through time despite the continuous change in their property, e.g., , in their length, density, and temperature
Occur as complete wholes, in spatial regionsThis means that, at each instant of time, an
endurant object occurs in its entirety, i.e., it persists as a self-connected mereological whole (e.g., Brevard Fault, Chattahoochee River)
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Perdurant entitiesThe perdurant (occurrent) Earth objects
such as processes, events, on the other hand, occur in intervals of time (ti+n-ti) through a succession of temporal parts (phases, stages), which are different from the whole
An example is a video of a hurricane or tsunami, taken over a period of time by a satellite, showing different phases of the same hurricane or tsunami
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An earlier temporal part (phase, stage) of the perdurant Katrina Hurricane
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A later temporal part (phase, stage) of the perdurant Katrina Hurricane
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Perdurants …Perdurants such as processes
(e.g., eruption) unfold themselves over time and, at each time slice (t)they present an incomplete part of the whole, meaning that they are mereologically incomplete (i.e., does not occur in its entirety)
A perdurant whole unfolds over a time interval by adding temporal parts
Past parts do not exist anymore!
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EventHappens in an instant of time, t
Defines the boundaries of states of entities
Start and end processes and subprocessese.g., the beginning/ending instants of a volcanic eruption
Two types of perdurant
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ProcessIs an spatio-temporal that brings state
change to the endurants (Folding deforms Bedding)May occur over several spatial and
temporal regions, e.g., landslide, deformation, hurricane
May not be a whole (e.g., sub-process)
A complex process is an inhomogeneous aggregate of two or more processes of different types (e.g., parts of an eruption include pyroclastic flow, mudflow)
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For spatial and spatio-temporal entities, a database or knowledge base should be able to answer the questions of the following types:
Where were the P- & S-waves 5 s after a seismic rupture?
Which process followed the melting of ice on a volcano 10 minutes after the eruption of lava?
Was pyroclastic flow partially synchronous with lahar? The answers require time and process ontologies
Need ontologies
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ObjectProcess
Object ObjectSub-Process
Process
Event
TimeInstant
TimeInterval
begins-at/ends-at
is-a is-a
causesoccurs-in
involves
p
bounded-by
participates-in
Values for the properties of classes and their properties store into a knowledge base
A knowledge base instantiates an ontology, such as the above, with values
An ontology is a formal model of reality, i.e., of objects and their relations
Fold has Axial Plane
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Ontologies are based on logicEnd of pyroclastic ejection (i) ending a
period of volcanic eruption (j)
i is a final sub-interval of j i and j end together
beg(j) < beg(i) end(i) = end(j)occursi (E, i) = e (type (e, E) time(e) = i)
Meaning: Event E occurs in interval i if there exists e, an occurrence of E, whose time of occurrence is interval i
e.g. formalizing a sub-process ending a process
Pyroclastic ejection
Eruptionbeg(j) end (j)
end (i)beg(i)
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We acquire data about individualsThe reality is populated by the instances
of the universal types, e.g.: San Andreas Fault, Idaho batholith
To gain and improve knowledge about the universals, geologists acquire data about the instances of the spatial and process entities in the field and laboratory, and through experimentation, simulation, and computation
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Information makes sense with knowledgeA collection of data may become
meaningful and useful, i.e., become information, when they are put together, e.g., in a plot or map
Same information may be interpreted differently applying different knowledge based on different truths, beliefs, perspectives, judgments, and know-how!Information, is therefore, the meaning of the
data based on background knowledge
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KnowledgeKnowledge is a collection or total sum
of true beliefs (statements) about real objects in a field (domain), which can be used to make a decision. True statements:Clay has low permeabilityRocks are made of one or more mineralsCleavage is a planar structure
The true beliefs are mainly about universals (i.e., types of things such as fault, mineral), but also include facts about individuals
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Knowledge fragmentsKnowledge, which is stored in people’s
head, books, and scientific journals, is a collection of true statements:
Rock is made of one or more mineralsx y [Rock (x) Mineral (y) has-Part (x, y)]
Thrusting moves older rocks on younger rocksx y z [Rock (x) Rock (y) Thrusting (z) older (age(x), age(y)) involves (z, x) involves (z, y) moves (onTop (x, y))]
Mylonite forms in some ductile shear zonex y [Mylonite (x) DuctileShearZone (y)
forms-in (x, y)]
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What is knowledge base (KB)?A knowledge-base uses an ontology to translate
the knowledge fragments into a machine-understandable and processable code
CataclasticFlow forms Gouge
Ontology is a formal, explicit model of the domain knowledge, which describes the terms and their relationships, and is built using semantic languages of RDF, RDFS, and OWL
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KB has explicit assertionsLaramide Orogeny deformed most rocks
in Wyoming during the Late Cretaceous period:
x y i [Orogeny (x) Laramide (x) Rock (y) located-in (y, Wyoming) TimeInterval (i) Deformed (x, y) during (Period (i, “Late Cretaceous”))]
Crystal-plastic deformation involves recrystallization, recovery, or both:
x y z [CrystalPlasticDeformation (x) has-Part (Recrystallization (y) Recovery (z))]
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Inference RulesComputers can also make use of
information through inference rules if we explicitly formalize our knowledge with specific rule-based machine language and logic
Automatic processing of information and performing inference about it requires specific languages (e.g., RDF, RDFS, and OWL) with built-in inference rules
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EntailmentKnowledge-based model of reality
(ontology), represent the semanticsof our knowledge by identifying real domain objects, and modeling the relationships among these objects and processes that involve them
Ontologies have embedded metadata and inference rules, that can be used to draw implicit entailments from the explicitly asserted facts
CataclasticFlow
FaultRock
CataclasticRock
Gouge
forms
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The inference-based semantics is very powerful for the integration of heterogeneous data coming from autonomous, distributed sources on the Web
The reason is that RDFS and OWL inferencing query engines, that know OWL inference rules, will infer (during a query) unasserted information from the directly asserted triples in the RDF store
Benefits of Inference Rules
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struc:FaultRock rdfs:subClassOf petr:Rock.struc:Mylonite rdf:type struc:FaultRock.
SPARQL query: Find things that are of type Rock?x rdf:type petr:Rock.
Despite the fact that there is no statementin the above triple store, with predicate rdf:type and object petr:Rock, the query will return the following inferred result using the
RDFS’s inference query engine:
?x = struc : Mylonite.
(i.e., the reasoner infers: Mylonite)
KB returns inferred statements
Rock
FaultRock
Mylonite
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Subduction
SubductionErosion
UnderplatingOffscraping
is-a
AccretionEndurant object Nankai Accretionary Prism
Perdurant (process): Accretion
Sub-processes: Offscraping, underplating, subduction erosion
occursDuringAccretionaryPrism
formsAn ontology
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Formal temporal relations
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Endurants (e.g., lava) are created (P1: eruption), transformed (P2: cooling), or destroyed (P3: erosion) by perdurants (processes, Pi)
e.g., in the case of an eruption (P1), the change occurs between the instant the lava starts to erupt (event E1) and the instant it completely freezes (event E2)
Perdurants change the state of the endurants over time intervals
Endurants keep their state between start & end eventsBut begin to change their properties at events
Life of an Endurant
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State At any instant of time, the state of any
object (e.g., rock) that participates in a process (e.g., deformation), defined by the collection of values for its properties, is in constant flux
The change of state (e.g., crystallization of magma), a subject of study by Earth scientists, occurs in a lawful state space, which is constrained by the properties, the physical laws, and environmental conditions
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An endurant object X (e.g., fault) has a lawful state space SL(X), which represents the collection of its possible states (e.g., sliding, stuck, but not swimming!) over time (through its properties)
The lawful state space is a subset of a larger conceivable state space: SL(X) S (X)
For every object, there is a series of lawful states: Si(x), Sj(X), … SL(X)
Lawful State Space
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Every possible state of a thing is givenby a point Si in the lawful state space SL(X)
The trajectory of the actual state of a thing at a given time and space, represents the actual change (due to processes between events) for the individual
Function F (e.g., constitutive law) maps the states (Si) w.r.t. a reference frame, along the state trajectory
History is a segment of the trajectory between Si
Transition from state S1 to S2 occurs in a possible event space, E(x), which starts a series of processes characterized by specific functions
State Trajectory
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How does science advance?For example, the state space for rock
deformation (a process) is within the range of pressure and temperature (conditions) in which rocks (endurants) remain solid (state)
Science progresses by discovering new properties and laws that restrict the relationship among properties for a given universal type, and the processes that change the state of objects that conform to the type
Fault_Rock
Crystal Plastic Deformation Mylonite
formsis_a
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Spatial and Temporal RegionsTemporal Region: interval of time in which active processes (tsunami) act on the interacting endurant objects that happen to be present in the spatial region where the starting/ending events occur
Spatial Region: space in which the objects of our interest (e.g. tsunami) occupy a specific interval of time
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Depending on granularity of our study, the spatial region can be represented as:a point, with long/lat or KML pointa polygon on a GIS layeran address (e.g., Fernbank Museum)
Temporal data can refer to:instants (e.g., October 18, 2009 at 10:00
AM)Discrete interval of time (Thanksgiving)Continuous period of time (Century, Triassic)
Representing spatial and temporal regions
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Geological processes occur in spatial and temporal regions, i.e. spacetime
For example, the seismic rupture that started the tsunami, initiated the propagation of a series of different types of seismic and tsunami waves, which occupied different spatial regions at different time intervals
Handling spatio-temporal knowledge
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Processes can occur synchronically (i.e., within same time intervals) or polychronically, involving same or different endurant objects, in the same or different spatial regions
The temporal region of an aggregate process (e.g., deformation) may be divided into several sub-intervals within which unique, but possibly (causally) related, sub-processes occurred
Process Relations
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Processes and spacetime
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P1
Cataclasis
PBrittleDeformation
is-aProcesses can be organized in
hierarchical structures using the ‘is-a’ and ‘part-of’ relations, reflecting specialization and part-whole relations
If a process P subsumes another process P1 (i.e., P1 is-a P), then for all x, if x is an occurrence of P1, x is also an occurrence of Px P1(x) P(x)
Oxidation is-a Weathering or Folding is-a Deformation, states that instances of Oxidation or Folding are also instances of the Weathering or Deformation processes, respectively
Taxonomy of Processes
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OWL (Web Ontology Language)<ow:Class rdf:about=“BrittleDeformation”/><owl:Class rdf:about=“Cataclasis”>
<rdfs:subClassOfrdf:resource=“BrittleDeformation”/>
</owl:Class>
OWL code snippet, part of Structural Geology ontology, asserting that Cataclasis is a type of Brittle Deformation Cataclasis
BrittleDeformation
is-a
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DynamicCrystallization
CrystalPlasticDeformation
is-a
GrainBoundaryMigration
is-a
<owl:Class rdf:about=“CrystalPlasticDeformation”/><owl:Class rdf:about=“DynamicRecrystallization">
<rdfs:subClassOf rdf:resource=“CrystalPlasticDeformation”/></owl:Class><owl:Class rdf:about=“GrainBoundaryMigration">
<rdfs:subClassOf rdf:resource="DynamicRecrystallization”/></owl:Class>
The actual (individual) occurrences of grain boundary migration recrystallization that occur during an actual mylonitization in a specific shear zone, are also occurrences of dynamic recrystallization which is a mechanism of crystal plasticity
These explicit assertions imply (through OWL’s inference rules) that the actual (individual) mylonite that participated in the sub-process also participated in the super-process (i.e., crystal plasticity)
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An individual process p1 is part-of p if and only if an instance of p1 is also an instance-level part-of pRotation part-of CataclasisShearing part-of FrictionalSliding
The mereological (part-whole) structure of processes is defined by their temporal partsFlow, diffusion, or subduction may have temporal parts
(i.e, phases or stages) that occur say faster than other parts
The parts are assumed to be contiguous, and without temporal gaps (which lead to sub-process or a new process)
Meronomy of Processes P
Cataclasis
P1
Rotation
part-of
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Assume the Analysis and XRF classes are defined
Define a new class constrained to have all of its individuals be of type XRF
<owl : Class rdf : about = “XRFAnaysis”>
<rdfs : subClassOf rdf : resource = “Analysis”/> <owl : Restriction> <owl : onProperty rdf : resource =
“typeOfAnalysis”/> <owl : allValuesFrom rdf : resource = “XRF”/> </owl : Restriction </rdfs : subClassOf>
</owl : Class>
XRF AnalysisXRFAnalysis
Analysis
is-a
XRF
typeOfAnalysis
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Building the REE class out of existing Analysis and by constraining the REE class to contain only individuals, at least one of which is a rare earth element
<owl : Class rdf : about = “REE”> <rdfs : subClassOf rdf : resource = “Analysis”/>
<owl : Restriction> <owl : onProperty rdf : resource = “elements”/> <owl:someValuesFrom rdf : resource =
“RareEarthElements”/> </owl : Restriction</rdfs : subClassOf>
</owl : Class>
Rare Earth Elements REE
REE
Analysis
is-a
RareEarthElements
elements
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Assume ‘orbits’ has a Planet domain and an XSD string range
<owl : Class rdf : about = “PlanetOrbitingSun”> <rdfs : subClassOf rdf : resource = “Planet”/> <owl : Restriction> <owl : onProperty rdf : resource = “orbits”/> <owl : hasValue rdf : resource = “Sun”/> </owl : Restriction </rdfs : subClassOf>
</owl : Class>
Planets that orbit around the sun
PlanetsOrbitingSun
Planet
is-a
Sunorbits
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<owl : Class rdf : about = “HydrogenIsotope”> <rdfs : subClassOf rdf : resource = “Isotope”/> <owl : Restriction> <owl : onProperty rdf : resource =
“numberOfIsotopes”/> <owl : maxCardinality rdf : datatype = “&xsd;nonNegativeInteger”> 3 <owl : maxcardinality> </owl : Restriction </rdfs : subClassOf></owl : Class>
Example: Hydrogen has at most three isotopes
HydrogenIsotope
Isotope
is-a
3
numberOfIsotopes
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Thank you!
Questions?
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OWL does not include a standard for spatial data
W3C’s OWL-Time is an ontology of temporal concepts (www.w3.org/TR/owl-time/)
XML XSD typed literals provide some support for time
GeoRSS provides support for point, line, box, and polygon (www.georss.org) based on the WGS84 standard
Basic Geo Vocabulary is an RDF encoding of long/lat values based on WGS84 standard (www.w3.org/2003/01/geo)
Spatio-temporal Technology
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<owl:Class rdf:ID="Instant"> <rdfs:subClassOf rdf:resource="#TemporalEntity"/>
</owl:Class> <owl:Class rdf:ID="Interval">
<rdfs:subClassOf rdf:resource="#TemporalEntity"/></owl:Class> <owl:Class rdf:ID="TemporalEntity">
<owl:unionOf rdf:parseType="Collection"> <owl:Class rdf:about="#Instant" /> <owl:Class rdf:about="#Interval" />
</owl:unionOf> </owl:Class>
Some Code from OWL-Time (Feng Pan and Jerry R. Hobbs)
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OWL-Time’s interval relations: intervalEquals, intervalBefore, intervalMeets, intervalOverlaps, intervalStarts, intervalDuring, intervalFinishes
and their reverse interval relations: intervalAfter, intervalMetBy, intervalOverlappedBy, intervalStartedBy, intervalContains, intervalFinishedBy
<owl:ObjectProperty rdf:ID="begins">
<rdf:type rdf:resource="&owl;FunctionalProperty" />
<rdfs:domain rdf:resource="#TemporalThing" />
<rdfs:range rdf:resource="#InstantThing" />
</owl:ObjectProperty>
OWL-Time Defines Properties for Processhttp://www.w3.org/2001/sw/BestPractices/OEP/Time-Ontology-20060518#examples
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Parthood is denoted by: Pxy or P(x, y) or part-of(x,y)
Reflexivity: Pxx, which means x is part of itself
Antisymmetry: Pxy Pyx x=ytwo distinct things cannot be part of each other
Transitivity: Pxy Pyz Pxzif x is part of y, and y is part of z, then x is part of
z
part-of (Faulting, Extension) part-of (Extension, Plate_Divergence) part-of (Faulting, Plate_Divergence)
part-of (Fluid_Inclusion, Quartz) part-of (Quartz, Vein) part-of (Fluid_Inclusion, Vein)
Axioms
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Querying knowledge bases that use the two diverse SNAP and SPAN perspectives requires trans-ontloogical relations that relate endurants to the processes/events
The formal relations should traverse across the:(1) border between the two perspectives, connecting
the endurants and processes together:<SNAP, SPAN>, <SPAN, SNAP><SNAPi, SNAPj> of distinct time indices i and j<SPAN, SPAN>
(2) granularity boundaries (microscopic-lithospheric)
(3) temporal divide, e.g., between now and later times
Formal, Perdurant Relations
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The ternary has-participant relation relates an instance of a process p to an instance of a continuant c at time t, i.e., p has-participant c at t
Hydrolytic_Softening has-participant Water at tCataclasis has-participant Rock at t
The occurring-at relation relates an instance of a process p, to time t (p occurring-at t)Recrystallization occurring-at tFrictional_Sliding occurring-at t
The ‘terminate’ relation holds where a SNAP entity terminates a processFree surface terminates fracture propagation
Special Spatio-temporal Relations
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The ‘facilitate’ relation holds where a SNAP entity facilitates a processRain or clay facilitate landslidehydroxyl ions (OH-) facilitate deformation of silicates (by
substituting for O)
The ‘hinders’ or ‘prevents’ relation holds when a SNAP entity has a negative effect on a processPoint defect hinders dislocation glide
The ‘mediates’ relation obtains when a SNAP entity indirectly brings participants of a process togetherWater or heat mediates alteration of rock (by bringing
ions in contact with mineral constituents)
Special Relations, cont’d
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The ‘realize’, and its subtypes: ‘initiate, ‘persist’, and ‘terminate’, are types of relation that hold between a SNAP dependent (i.e., qualities, roles, functions) and a process
Water realizes hydrolytic_Weakening of rock (at high T)Pore pressure realizes hydraulic_Fracturing of rockVolume increase realizes dilation of rockGrowth of high-density minerals realize metamorphism
(at high pressure)
The ternary realizes relation holds between a SNAP (mineral), a SNAP dependent entity (increase in volume), and a process (dilation)
(e.g., Mineral volume_increase realizes Rock_Dilation)
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Relations between SPAN processes and SNAP entities include the ‘involves’ relation, which is the converse of the ‘participates’ relation that obtains between a SNAP and SPAN entities
Mylonitization involves Rock
A process can also ‘destroy’ a SNAP entityMylonitization destroys original rock texture
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Temporal Relations
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Conclusions:
1) Processes are first class entities with a full set of ontological relations, taxonomy, and meronomy
2) Process ontology requires time ontology
3) W3C provides some technology for building geoprocess ontologies
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Knowledge
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Universal types for objects in reality 1. Continuant (Endurant) entities
Endure or persist through time by being fully present at any time instant, te.g., aquifer, mineral, volcano
Are mereological wholes with continuant spatial parts
Participate in occurrents, through which they can change their propertiesIons participate-in Mineralization
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Ad-hoc Database SchemasThese scientists may store their data in
relational databases with diverse and uneven design model (schema)
The terms for the attributes (fields) in their database tables are as variable as the number of their databases
The variable name designs make it difficult to integrate the schemas across domains
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Even if these databases become a node on the Web, and available for human consumption
They cannot be processed and integrated with different software distributed over the Web because the database schemas generally do not match
Heterogeneous Schemas
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Ontologic relations form the SWFormal OWL language syntax and inference
rules provide semantics for knowledge bases, for both software and human consumptionSemantic relations (e.g., mereology,
topology, subsumption, aggregation, associations, restriction) form the Semantic Web
RDF triple statements in a KB, which link data via the URI, provide both location and semantics, enabling global, machine-processable integration and sharing of knowledge at the Web scale
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Open World AssumptionThe closed model of databases assumes
that data not known to be true (i.e., those which are not currently in the database) are false
This is in contrast with the open-world knowledge bases which assume that all answers are possible; of which some could be proven to be correct, incorrect, or ambiguousi.e., an answer is not false unless it is
absolutely proven to be false
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Feature Database Knowledge base
Structure Schema Ontology statements
Data Rows (records) Instance statements
Language DDL Ontology statements
Query Language
SQL SPARQL
Relationships Foreign keys Multidimensional
Logic External to database/triggers
Formal logic statements
Nature of storage
static dynamic, extensible
Assumption Closed world Open World
A Comparison of RDB and KB
After: J. Hebeler et al., 2009 “Semantic Web Programming’, Wiley
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: dependsOn owl: inverseOf :enables: sliceSpecimen : enables : makeChip.: makeChip : enables : polishChip.: polishChip : enables : mountChip.: mountChip : enables : polishSection.: polishSection : enables : putCoverslide. : dependsOn rdfs : subPropertyOf : requires.: requires rdf : type owl : TransitiveProperty.: enables rdfs : subPropertyOf : requiredFor.: requiredFor rdf : type owl : TransitiveProperty
From the above statements we infer the following requirements for ‘mountChip’: : mountChip : requires : polishChip;: requires : makechip;: requires : sliceSpecimen.
Code for the workflow
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SummaryRepresentation and management of
knowledge is as important as its acquisition
Database or knowledge base can fulfill different needs; the former is good for data storage and query, and the latter for data and knowledge storage and query
Ontologies and knowledge bases are the foundation of the coming Semantic Web
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After precipitation, water infiltrates into the ground and/or runs off on the surface of the ground
: infiltrates rdfs : subPropertyOf : recharges
If water infiltrates the Floridan Aquifer (an instance):hydro: Water hydro: infiltrates hydro: FloridanAquiferhydro: Water hydro: recharges hydro: FloridanAquifer
This is a one way inference, i.e., when water infiltrates an aquifer, it recharges it, but if an aquifer is recharged, it may not be because of infiltration
Example
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Since these steps are in order, then each step may enable the next step, or each step depends or requires the previous step:
Workflow
makeChip mountChippolishChippolishSectio
n
putCoverSlide
sliceSpecimen
dependsOn or requires
enables