Semantic Web

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Semantic Web Peer-To-Peer HY566 Semantic
WebInstructor Grigoris Antoniou

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• S??????????? T?µ??
• ??????? 2003

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Issues of Research Work

• Semantic Web Vision
• Peer to Peer technologies
• The JXTA framework
• 2 Main directions Combining SW and P2P
• Projects overview
• InfoQuilt
• Edutella
• Elena project
• Neurogrid
• Swap
• Discovery Service based on Edutella
  infrastructure
• Hypercubes, Ontologies and efficient search on
  P2P networks

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Peer-To-Peer overview (Napster - Gnutella)

• Peer to peer systems have similar goals to
  facilitate the location and exchange of files
  (typically images ,audio, or video) among a large
  group of independent users connected through the
  Internet.
• In these systems, files are stored on the
  computers of the individual users or peers, and
  exchanged through a direct connection between the
  downloading and uploading peers, over an
  HTTP-style protocol.
• All peers in this system are symmetric they all
  have the ability to function both as a client and
  a server.
• This symmetry distinguishes peerto-peer systems
  from many conventional distributed system
  architectures.
• Though the process of exchanging files is similar
  in both systems, Napster and Gnutella differ
  substantially in how peers locate files

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Napster

• In Napster, a large cluster of dedicated central
  servers maintain an index of the files that are
  currently being shared by active peers.
• Each peer maintains a connection to one of the
  central servers, through which the file location
  queries are sent. The servers then cooperate to
  process the query and return a list of matching
  files and locations.
• On receiving the results, the peer may choose to
  initiate a file exchange directly from another
  peer.
• In addition to maintaining an index of shared
  files, the centralized servers also monitor the
  state of each peer
• in the system, keeping track of metadata such as
  the peers reported connection bandwidth and the
  duration that the peer has remained connected to
  the system.
• This metadata is returned with the results of a
  query, so that the initiating peer has some
  information to distinguish possible download
  sites.

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Gnutella

• There are no centralized servers in Gnutella,
  however. Instead, Gnutella peers form an overlay
  network by forging point-to-point connections
  with a set of neighbors.
• To locate a file, a peer initiates a controlled
  flood of the network by sending a query packet to
  all of its neighbors.
• Upon receiving a query packet, a peer checks if
  any locally stored files match the query.
• If so, the peer sends a query response packet
  back towards the query
• originator.
• Whether or not a file match is found, the peer
  continues to flood the query through the overlay.
• To help maintain the overlay as the users enter
  and leave the system, the Gnutella protocol
  includes ping and pong messages that help peers
  to discover other nodes.

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Gnutella vs. Napster architecture
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2 Main directions Combining SW and P2P

• The first research direction uses peer-to-peer
  networks as a basis infrastructure for the
  exchange of semantic information. The peers can
  create and maintain their own ontologies and
  definitions. In addition, they can create their
  own relationships between their ontologies, or
  use the ontologies of other peers to create inter
  relationships.
• The second research direction combines semantic
  web and peer-to-peer technology in order to
  support schema-based P2P networks. ?he general
  objective here is to extend conventional
  peer-to-peer networks by allowing different and
  extensible schemas to describe the peer content

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1st Direction InfoQuilt Overview

• Challenges we need to address in order to realize
  SW vision
• Info Quilt system
• Why are P2P desirable to be an infrastructure for
  knowledge sharing
• Systems Architecture - A multi agent information
  brokering system
• Knowledge space construction and navigation
• Semantic Search

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Semantic web vision

• The usage of programs that can understand the
  semantics of the data.
• Use of ontologies in order to
• Provide the context for capturing the meaning of
  data
• Capture the users intention in a query

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Challenges we need to address in order to realize
SW vision

• A way to advertise knowledge and ontologies of
  different information domains, which are
  maintained by different persons, groups and
  organizations on the Web.
• A semantic search mechanism is needed to find
  most relevant set ontologies using users context
  for information request and his profile.
• Once the ontologies are located there is a need
  for introducing some relationships across
  ontologies and supporting techniques for ontology
  interoperation
• users need tools that would allow them to define
  information requests

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Peer to peer Semantic Web (PSW)

• Consists of two basic components
• DAMLOIL provides a specification framework for
  independently
• creating
• maintaining and
• interoperating
• ontologies while preserving their semantics
• Peer To Peer (P2P) systems are used to provide a
  distributed architecture which can support
  sharing of independently created and maintained
  ontologies

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Info Quilt system

• A system developed at the university of Georgia
  which facilitates
• Distributed and autonomous creation and
  maintenance of local ontologies,
• Advertisement (i.e., registry) and search of
  (local) ontologies,
• Introducing inter-ontological relationships
  between relevant ontologies as-needed basis once
  they are located,
• Controlled sharing of knowledge base components
  among users in the network,
• Ontology-driven semantic search of concepts and
  services,
• Knowledge discovery and exploration of
  inter-ontological relationships.

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Why are P2P desirable to be an infrastructure for
knowledge sharing

• It encourages distributed architecture, and
  supports decentralization of control and access
  to information and services ? A way to harness
  the computing power and knowledge of millions of
  computers in the web.
• It provides access to semantic information
  published by several independent content
  providers,and enables creation of personalized
  semantic relationships.
• It supports for publishing peer definitions and
  relationships to other peers and software agents.
• It offers user-centered, data-centered and
  computing centered models, which provide
  suitable architectures for distributed content
  management.

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Knowledge Discovery

• system includes
• (a) language and tools to specify IScapes
  (i.e., semantic information requests), and
• (b) tools and algorithms to perform what-if
  analyses to search the information space of
  semantically related data.
• IScapes allow parameterized specification of
  information requests and correlation that
  utilizes the domain ontologies, inter-ontological
  relationships and user defined functions to
  accurately describe a users information need.
• IScapes are more than a traditional query in that
  they can understand users request by embedding
  semantic information

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Systems Architecture - A multi agent information
brokering system
2.Provides access and adds new Ontologies and
user-defined inter/intra ontological
relationships to the knowledge space
1.The ontologies define concepts ,their
properties and relations with other ontologies
3.Using keywords the peer searches for relevant
sets of ontologies at the knowledge space
Composed of local ontologies of independent peers
connected by inter-ontological relationships
4.Execution of IScape
6.The results are reranked based on the user
profile and other factors
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Knowledge space construction and navigation (1/3)

• When a person defines his own concept or notion
  based on a predefined or agreed upon concepts, it
  is marked up in the knowledge space by these
  references.
• One concept (ontology)that survives is the one
  that is most referenced, other definitions go by
  unnoticed.
• In using DAMLOIL, the only concepts everybody
  agrees upon are the basic classes like Thing
• When a new ontology is created, it is already
  hooked up in the knowledge space because of the
  use of imports and namespaces
• In order for the programs to access this
  knowledge space programmatically, a data
  structure is used

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Knowledge space construction and navigation (2/3)

• RDF statement in an ontology can define a class,
  its properties and its relationships with other
  classes. For example a statement would look like
• ltboygt ltdrinksgt ltcoffeegt.
• Now all of the triples, boy, drinks and coffee
  are qualified by use of URIs.
• The data structure stores subject (boy), the
  object (coffee) and the verb (drinks) that
  relates them.
• So the core components of the data structure are
• Concepts Concepts or KObjects contains
  information about each class. In the example, boy
  and coffee qualify to be KObjects.
• Links Links or relationships contain information
  about the predicate and the KObjects it relates.
• In our example drinks qualifies as a
  Link.

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Knowledge space construction and navigation (2/3)

• For each KObject, the pointers to the Links that
  has this KObject as a subject or object and the
  ontology it is defined along with the user
  information are maintained.
• In creation of the knowledge space the following
  steps are involved
• 1. Retrieve every RDF triple (subject, predicate,
  and object) from each source ontology,
• 2. For every assertion of a fact or a definition
  made in the ontology, recursively trace its link
  to the most general class of the knowledge space
  (Thing),
• 3. Repeat 1 and 2 untill all the ontologies are
  hooked into the knowledge space.
• For knowledge space navigation, we can start with
  the KObject Thing and then traverse through the
  Links in the KObject.

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Ontology registration

• The peers can create and maintain their own
  ontologies conforming to DAML OIL formalisms
• They have control as whether or not to share an
  ontology
• A peer who decides to share an ontology must
  upload it to the knowledge space (registration).
• New concepts (Kobjects) and relationships (Links)
  are created appropriately
• Once an ontology is uploaded, other peers can
  refer to its definitions
• In case a peer removes his ontology, all
  definitions and assertions that refer to these
  definitions become invalid in the knowledge space
• Tools like DAML validator can check for obsolete
  definitions and stale links

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Semantic Search (1/3)

• One of the key advantages of constructing a
  knowledge space is semantic search. In the IScape
  Builder, the user specifies the keywords (usually
  common nouns) used in the information request.
• The data structure representing the knowledge
  space is a collection of KObjects and Links.
• The input is a set of keywords and the output is
  a list of ontologies. The process of searching
  involves the following steps

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Semantic Search (2/3)

• 1. Take each keyword and run a basic keyword
  match on the subject, object and the predicate
  (in that particular order) in the entire
  knowledge space,
• 2. Retrieve the name of the ontologies that
  satisfy the above match along with the ownership
  details,
• 3. If the keywords result in a number of
  ontologies, compare the ontologies for common
  parents and eliminate the ontologies without any
  common links,
• 4. If there is more than one ontology describing
  the same keyword, perform search with more
  keywords or compare the resulting ontologies to
  help user select the ontology.

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Semantic Search (3/3)

• One other utility awhich uses the knowledge space
  is the ability to compare two ontologies. This
  involves the following steps
• 1. Identify the KObjects (concepts)
  used in each ontology in the knowledge space,
• 2. Find a common parent KObject that
  links two Objects that are defined in each of the
  compared ontologies
• in other words, find a connecting link
  (relationship) between the two ontologies and
  trace it for the user.

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Semantic Search - An example (1/5)

• Find all earthquakes with epicenter in a 5000
  mile radius of the location at latitude 60.790
  North and longitude 97.570 East and find all
  tsunamis that they might have caused.
• The keywords in the above information request are
  earthquake, epicenter, radius, location,
  latitude, longitude, and tsunamis.
• Let assume the following results for the keyword
  matches on the subject, object and the predicate
  of all the triples in the DAMLOIL ontologies

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Semantic Search - An example (2/5)
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Semantic Search - An example (3/5)

• After the above results are obtained, we have to
  arrive at the semantically relevant set of
  ontologies.
• This is done by comparing every KObject in the
  ontology with every other KObject in the other
  ontologies.
• If they have acommon KObject linked by both the
  KObjects, they are related (e.g., tsunamis and
  earthquakes are related because they have a
  common parent, i.e., a KObject, namely disaster).

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Semantic Search - An example (4/5)

• In addition, of these ontologies earthquake.daml,
  location.daml and
• tsunami.daml, are linked with KObjects latitude,
  longitude.
• So the relevant set of ontologies will be
• earthquake.daml
• location.daml
• tsunami.daml
• discarding damage.daml, weather.daml and
  circle.daml.
• The ontology weather.daml is discarded even
  though it has a reference to the definition of
  location because, although the definition of
  weather involves country, which is a sub-class of
  location it is not related in the sense it does
  not have a common parent with earthquake and
  tsunami.

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Semantic Search - An example (5/5)

• Thus, the system considers earthquake, tsunami,
  and location ontologies as relevant because this
  is the minimal set of ontologies with all keyword
  matches and has at least one common KObject
  linked.

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2nd Direction ?verview

• Introduction to the second main research area
• Problems of current P2P implementations
• Project Edutella
• JXTA Framework
• Overview Edutella Services
• Edutella Query Service
• Example O-Telos provider peer

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The 2nd research area Semantic Web Peer-to-Peer

• Combines semantic web and peer-to-peer technology
  in order to support schema-based P2P networks
• Aims to extend conventional peer-to-peer networks
  by allowing different and extensible schemas to
  describe the peer content
• Metadata for the WWW are important, but metadata
  for Peer-to-Peer networks are absolutely crucial

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Problems of P2P applications

• Information Resources in P2P networks are no
  longer organized in hypertext like structures
• Information resources are stored on numerous peer
  waiting to be queried
• If we know what we want to retrieve
• Which peer is able to provide that information
• Querying peers requires metadata describing the
  resources
• Easy for specialized cases like exchanging music
  files
• Non trivial for general applications like
  exchanging educational material

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Problems of P2P applications

• Current P2P implementations
• Concentrate on domain specific formats appear to
  be fragmenting into niche markets
• No unifying mechanisms for future P2P
  applications
• There is indeed a great danger that unifying
  interfaces and protocols introduced by the WWW
  get lost in the P2P arena

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Project Edutella

• Edutella Project addresses shortcomings of
  current P2P applications by building on W3C
  metadata standard RDF
• Edutella is a metadata-based P2P system
• Integrate heterogeneous peers (Different
  repositories, Query languages, Functionality)
• Different kinds of metadata schemas
• Common ground is an essential assumption
• All resources (metadata) maintained in the
  Edutella network can be described in RDF
• First applicationa P2P network for the exchange
  of education resources

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Background The JTXA P2P Framework

• Project JXTA (Sun Microsystems)
• An open source programming platform to enable P2P
  services and applications
• Interoperability, Platform Independence
• Layered Approach

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JXTA Edutella

• Edutella Services
• Complements the JXTA Service Layer
• Build upon the JXTA Core Layer
• Described in web service language like DAML-S,
  WSDL
• Edutella Peers
• Live on the JXTA Application layer
• Are using the functionality provided by the
  Edutella Services

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Edutella Services

• Query Services
• Standardized query and retrieval of RDF metadata
• Replication Services
• Providing data persistence/availability and
  workload balancing
• Mapping Service
• Translate between different metadata vocabularies
  to enable interoperability between different
  peers.
• Annotation Service
• Annotate materials stored anywhere in the
  Edutella Network.

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Edutella Query Services

• Peer register the queries they may be asked
  through the query service
• Specifying the supported metadata schema
• Peer provide metadata according to DCMI standards
• Specifying the individual properties
• Peer provides metadata of the form dc_title(X,Y)
• Queries are sent through the Edutella network to
  the subset of peers who have registered to be
  interested in this kind of query

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Edutella Working Scenario
Edutella Consumer
Edutella Provider
Edutella Provider
Registration
Query
Replication
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Query Exchange Architecture

• Edutella Common Data Model (ECDM)
• Provides the syntax and semantics for an overall
  standard query interface
• Edutella network uses the query language family
  RDF-QEL as a standardized query language format
• How to enable the peer to participate in the
  Edutella network?
• Edutella wrappers are used to translate queries
  and results from the Edutella query and result
  exchange format (ECDM) to the local format and
  vice versa
• There are several RDF-QEL-i exchange language
  levels describing which kind of queries a peer
  can handle

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Edutella Common Data Model (ECDM)
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RDF-QEL-i Language Levels

• RDF-QEL-1
• Simple and readable syntax following the QBE
  paradigm
• Query graph has exact the same structure as the
  answer graph
• Logical conjunctive formula
• RDF-QEL-2
• Extends the 1-level with disjunction
• Reified RDF statements are building blocks for
  each query
• Linked together by an AND-OR tree

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RDF-QEL-i Language Levels

• RDF-QEL-3
• Allows conjunction, disjunction and negation of
  literals
• RDF-QEL is essentially Datalog
• RDF-QEL-4
• Allows recursion to express transitive closure
• Compatible with SQL3
• Relational query engine with full conformance to
  the SQL3 standard will be able to support
  RDF-QEL-4

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Example Knowledge Base
Query Return all resources that are a book
having the title Artificial Intelligence or
that are an AI book
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Example Query RDF-QEL-1
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Example Query RDF/XML serialization

• lteduQEL1Query rdfID"AI_Query_1"gt
• lteduhasVariable rdfresource"X"/gt
• lt/eduQEL1Querygt
• lteduVariable rdfID"X" rdfslabel"X"gt
• ltrdftype rdfresource"http//www.lit.edu/typ
  esAIBook"/gt
• lt/eduVariablegt
• lteduQEL1Query rdfID"AI_Query_2"gt
• lteduhasVariable rdfresource"Y"/gt
• lt/eduQEL1Querygt
• lteduVariable rdfID"Y" rdfslabel"X"gt
• ltrdftype rdfresource"http//www.lit.edu/type
  sBook"/gt
• ltdctitlegtArtificial Intelligencelt/dctitlegt
• lt/eduVariablegt

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Standard Result Set

• Query results are represented as as set of tuples
  of variables and their bindings
• lteduResultSet rdfID"AI_Results"gt
• lteduhasResult rdfparseType"Resource"gt
• ltrdftype rdfresource"eduTupleResult"/gt
• lteduhasVariable rdfparseType"Resource"gt
• ltrdftype rdfresource"eduVariableBinding"/gt
• ltedubindsVariable rdfresource"X"/gt
• ltrdfvalue rdfresource"http//www.xyz.com/ai.htm
  l"/gt
• lt/eduhasVariablegt
• lt/eduhasResultgt
• lt/eduResultSetgt

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An O-Telos provider peer for the RDF-based
Edutella P2P network
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O-Telos Provider

• Describes a provider peer and its services for
  the Edutella network
• Provider-peer uses the ConceptBase as a
  repository for storing meta-data
• ConceptBase implements a meta language
  representation language O-Telos

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Provider Peer Two basic services

• Storage service designed to store RDF(S) data in
  the ConceptBase repository
• The data represented in RDF(S) are translated to
  O-Telos
• Query service the provider-peer serves as query
  interface to the RDF data stored in the
  ConceptBase
• Queries are formulated in RDF-QEL
• The peer translates the them into O-Telos queries
• O-Telos queries are answered by the ConceptBase
• The peer translates answers from O-Telos into RDF

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Schematic Representation of the architecture
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Questions ???
End!