Hassan BabaieDepartments of Geosciences & Computer Science, GSU

www.gsu.edu/~geohab

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

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

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

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

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

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]

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

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

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)

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’

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

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)

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

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

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)

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

An earlier temporal part (phase, stage) of the perdurant Katrina Hurricane

A later temporal part (phase, stage) of the perdurant Katrina Hurricane

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!

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

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)

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

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

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)

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

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

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

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)]

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

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))]

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

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

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

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

Subduction

SubductionErosion

UnderplatingOffscraping

is-a

AccretionEndurant object Nankai Accretionary Prism

Perdurant (process): Accretion

Sub-processes: Offscraping, underplating, subduction erosion

occursDuringAccretionaryPrism

formsAn ontology

Formal temporal relations

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

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

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

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

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

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

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

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

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

Processes and spacetime

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

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

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)

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

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

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

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

<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

Thank you!

Questions?

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

<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)

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

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

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

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

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

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)

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

Temporal Relations

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

Knowledge

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

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

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

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

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

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

: 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

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

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

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