Semantics Modeling and Representation Modeling and Representation Wendy Hui Wang ... • SMSN: Semantics‐based mobile social ... (SDM) Wendy Hui Wang

Semantics Modeling and Representation

Wendy Hui WangCS Department

Stevens Institute of [email protected]

Wendy Hui Wang, SDR Semantics Study April 29 , 2009

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Consider the following data:

011500 18.66 0 0 62 46.271020111 25.220010

011500 26.93 0 1 63 68.951521001 32.651010

020100 33.95 1 0 65 92.532041101 18.930110

020100 17.38 0 0 67 50.351111100 42.160001

– What do they really mean?

– How to model the meaning of data?

– How to represent the meaning of data?


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Outline

• Semantics modeling

• Semantics representation

• SMSN: Semantics‐based mobile social networks

• Brief discussion of Semantics + SDR


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In Database Context

• Semantic modeling is fundamental in database design

• Goal of semantics modeling: accurately model data relationships

• Evolution of semantic models– Early years: representation of structural aspects of (static) business data

– Recent years: incorporating the behavioral (dynamic) aspects of data


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Philosophical Roots of Semantic Modeling

• Semantic models should– Provide a higher level of abstraction for modeling data, and

– Allow database designers to think of data in ways that correlate more directly to how data arise in the world.


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Components of Semantic Modeling

• Explicit representation of objects, and relations between objects

• Type constructors for building complex types

• ISA relationships

• Derived schema components


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World Traveler Example


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objects

objects

Type constructors for building complex types

ISARelation

Derived Schema Component

Semantic Models

• Entity‐relation model (ER)

• Functional data model (FDM)

• Semantic data model (SDM)


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Entity‐relation (ER) Model

• Proposed in 1976.

• One of the first true semantic data models in the literature.

• Still commonly used in database design.

• A graph‐based representation of – abstract sets of entities,

– relationships between these entity sets, and

– attributes defined from both entity and relationship sets


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An Example of ER Model


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More Discussions of ER Model

• Restriction of the use of attributes and aggregation– Attributes must be single valued

– Multi‐valued attributes require the use of a relationship.

• ISA relationships are not represented.


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Functional Data Model (FDM)

• Proposed in 1976

• the first semantic model centered around functional relationships, that is, attributes.

• FDM connects objects directly with attributes without the use of intermediate constructs such as aggregation and grouping.


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FDM V.S. ER

• Attributes in FDM can be – either single‐ or multivalued

– defined on domains that are Cartesian products of the atomic entity sets.

• FDM supports ISA


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An Example of FDM Model


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Semantic Data Model (SDM)

• Proposed in 1981

• The first model to emphasize – grouping constructor, and

– the support of derived schema components.

• Derived schema components permit data relativism, that is, multiple perspectives on the same underlying data set.


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Uniqueness of SDM

• It provides a rich set of primitives for specifying derived attributes and subtypes.

• Subtype relationships in SDM are broken into 4 categories: – Those that are defined by attributes

– Those that are defined by set operations (e.g., intersection) on existing types

– Those that serve as the range of some attribute,

– Those that are user specifiedWendy Hui Wang, SDR Semantics Study

April 29 , 200916

Presenter

Presentation Notes

Type II: define retired-tourists, and union with tourist Type III: define tourists by the countries they have been to. Type IV: define suspicious tourists.

Outline






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Semantics Representation 1: Schema

NAME LENGTH FORMAT LABELinstudy 6 MMDDYY Date of randomization into studybmi 8 Num Body Mass Index.obesity 3 0=No 1=Yes Obesity (30.0 <= BMI)ovrwt 8 0=No 1=Yes Overweight (25 <= BMI < 30)Height 3 Num Height (inches)Wtkgs 8 Num Weight (kilograms)Weight 3 Num Weight (pounds)

• The semantics, i.e. the explanation of what data means, is called metadata or “data about data.”

• Metadata can be represented by schema.


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Semantics Representation 2: XML

• Semantic markup – the eXtensible Markup Language (XML)

• XML supports self‐defined tags, which are used to describe the meaning of the data.

• XML represents the semantics as a layer of machine‐understandable specification built on top of common syntax.


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<bioml><organism name="Homo sapiens (human)"><chromosome name="Chromosome 11"

number="11"><gene name="Insulin gene">

<dna name="Complete HUMINS sequence“ >agagcaccca acaccctcca ...

</dna>...

</gene></chromosome>

</organism></bioml>

An Example of XML


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Components in XML Semantics

• XML Semantics include– The interpretation of element type names, attribute names, and, in some cases, content terms

– The processing rules (also known as business rules) for conducting transactions with valid documents

– The relationship between structured elements of one document and those of another


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Beyond XML

• To describe the meaning of data on WWW, W3C recommend– Resource Description Framework (RDF)

– Web Ontology Language (OWL)


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The Resource Description Framework (RDF)

• RDF is a language for representing information about resources in Web.

• RDF is represented in XML, which provides machine understandable semantics.

• It provides– better precision in resource discovery than

full text search, – assisting applications as schemas evolve, – interoperability of metadata.


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RDF Triples• The semantics of RDF is determined by the set of triples <subject, predicate, object> that are explicitly asserted or inferred.

subject

objectpredicate


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Web Ontology Language (OWL)• OWL is based on RDF .• OWL adds many new features to RDF:

– Functional properties– Inverse functional properties (database keys)– Local domain and range constraints– General cardinality constraints– Symmetric and transitive properties


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Outline






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Social Mobile Computing

• Integration of social networks with mobile computing

• Static case: use mobile devices to access the pre‐built social networks

• Dynamic case: construct social networks from mobile devices– community‐oriented, self‐organizing, self‐adaptive


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Necessity for Semantics• Mobile devices store large amounts of personal data– Address book, text messages, call logs, photos…

• Personal data can be summarized to user profiles (describing interests, behavior, etc.)

• Goal: group users into social communities by their personal profiles

• Challenge: simple exact match of keywords in user profiles misses important semantics – Same concern holds for resources in networksWendy Hui Wang, SDR Semantics Study

April 29 , 200928

My Current Work

• SMSN: Semantics‐based mobile social network computing

• Three components– Ontology‐based user profile representation

– Semantics‐based user profile matching

– Semantics‐driven routing


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Ontology‐based User Profiles (1/2)

• Ontology:– Uses RDF and OWL

– The terminological box (T‐box): defines the common understanding for all the important concepts and their relationships.

• We adapt Friend‐of‐a‐Friend (FOAF) vocabulary


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Ontology‐based User Profiles (2/2)

• User profiles • Annotated instances of the reference T‐Box ontology

<Person rdf:ID="Person_1">

<friendOf>

<Person rdf:ID="Person_2">

<eyeColorrdf:datatype=

“http://www.w3.org/2001/XMLSchema#string">Black</eyeColor>

<weight rdf:datatype="http://www.w3.org/2001/XMLSchema#float">55.0</weight>

<friendOf rdf:resource="#Person_1"/>

…

</Person>


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Semantics‐based User Profile Matching

• Two phases– Phase 1: match user profiles at “general concept” level (T‐box level)

– Phase 2: match user profiles at “detailed concept” level (keyword level)

• Similarity metrics– “Relative” distance of two concepts in the ontology


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Semantics‐driven Routing

• Nodes distribute semantic summary of user/resource profiles within a certain range to their network neighborhood

• A node can make routing decisions by knowing only its immediate neighbors and limited resource information.

• A leap mechanism is used to expedite the searching process by skipping over the “barren” areas, i.e., the areas consisting of few resources/profiles.


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Discussion: SDR + Semantics

• The challenges– Identify the real meaning of semantics

• In database applications, semantics means metadata

• In Web, semantics means the definition of Web resources

• In social networks, semantics means the description of users and their social behaviors

• What does semantics mean in SDR?


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Discussion: SDR + Semantics

• The challenges (continue)• Identify the real meanings of semantics

• Design the semantic models– Can any existing semantic model (ER, FDM, SDM, and

others) be applied to SDR?

• Represent the semantics– Can any existing semantic representation (schema,

XML, RDF, OWL, and others) be applied to SDR?


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Reference

• Richard Hull, Roger King. Semantic Database modeling: survey, applications, and research issues.

• XML: http://www.w3.org/XML/

• RDF Primer: http://www.w3.org/TR/REC‐rdf‐syntax/

• OWL: http://www.w3.org/2004/OWL/


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Semantics Modeling and Representation Modeling and Representation Wendy Hui Wang ... • SMSN: Semantics‐based mobile social ... (SDM) Wendy Hui Wang