KNOWLEDGE REPRESENTATION Ontologies

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Communication Network Management Technologies. KNOWLEDGE REPRESENTATION Ontologies. Rashid Mijumbi Barcelona, April 2011. Data and Information Models Definition. A model is a representation of the entities in a managed environment. - PowerPoint PPT Presentation

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  • KNOWLEDGE REPRESENTATIONOntologiesCommunication Network Management TechnologiesRashid MijumbiBarcelona, April 2011

  • Data and Information ModelsDefinition A model is a representation of the entities in a managed environment.

    Provides a common terminology for representing management information, relationships, constraints, rules, and operations to specify data syntax for a chosen domain of discourse

    DM 1DM 3IM 1DM 2Conceptual/Abstract model for designers and operators High Level RepresentationConcrete model (for implementors) Low Level Representation More Details

  • Data Models (1)The Necessary EvilIPsec VPNMPLS VPNMPLS TE MPLS QoSSpecific Device ModelSpecific Device ModelSpecific Device ModelSpecific Device ModelSpecific Device #1Specific Device #2Specific Device #3Specific Device #4Translation LayerN Different TechnologiesAtleast N*M translations neededM DevicesHeterogeneity in systems makes different Data Models a necessity

  • Data Models (2)ProblemsData harmonisation problem in Data ModelsBilling ApplicationCustomer Name: rashid.mijumbiFault Management ApplicationCustomer Name: mrashidSecurity ApplicationCustomer Name: rmijumbi

  • Information Models (1)

    Abstraction, Data Harmonised (no Conflicts)Information ModelStandards Based Data ModelVendor Based Data Model1 : N1 : M

  • Information Models (2)Router Configuration ExampleCISCOJuniperRouter(config)# router bgp autonomous-systemRouter(config-router)# neighbor{ ip-address | peer-group-name} remote-as numberRouter(config-router)# neighbor ip-address activaterouting-instances { routing-instance-name {protocols { bgp {group group-name; { peer-as as-number;neighbor ip-address; } } } } }Different LanguagesDifferent SemanticsDifferent programming modelsDEFINING BGP PEERS

  • Ontologies (1)

  • Ontologies (2)Ontology refers to the shared understanding of some domain of interest which may be used as a unifying framework Uschold and Gruininger (1996)An ontology is an explicit specification of a conceptualisation. Gruber 1993Ontologies offer a formal mechanism for defining an understanding of dataOntological CommitmentsOntology Requirements: Clarity, Coherence, Extensibility, Minimal encoding bias, Minimal ontological commitment

  • Ontology Languages An ontology language is made up of three components syntax, semantics (model theory), proof theory. The syntax of an ontology language is itself divided into three areas Logic lexicon, non-logic lexicon and Grammar.By SyntaxCycL and KIF are examples of languages that support expressions in first-order logic.By StructureThese languages use a markup scheme to encode knowledge, most commonly XML.Ontology Inference Layer (OIL), OWL.

  • Ontology Tools Ontology development toolsOntology development tools can be further distinguished as: those that are independent of an ontology language, and those that are tightly dependent on one.Protg, Ontolingua.Ontology merging toolsPROMPT, Chimaera.

  • Semantic Web (1)User lives in Barcelona and wants to buy a car locally. He can afford up to 500. He wants a red car.

    Hospitalet400maroonOld bangerFord Escort

    UsedCars WebsiteUser A new form of web content that is meaningful to computers - Berners-Lee 2001This is because computers cannot process the semantics that are associated with web content

  • Semantic Web (2)Ontologies:Define relationships: relationship between, say, a postcode, a town, a suburb, etcMapping ServiceUserWordnetFord New CarsBCN CarsUsedCars Website

    *This includes definition of their attributes, operations and relationships. It is independent of any specific type of repository, software usage, or access protocol

    First, it simplifies information management by providing a common terminology for representing management information.

    Second, it unifies information both within and between enterprises. Third, it provides a bridge between different constituencies, such as business and network workers, by providing concepts, definitions, and terminology that are understandable by both constituencies. These benefits then enable business benefits relating to cost, quality, timeliness and adaptability of enterprise operations, allowing an enterprise to focus on value creation for their customers.*Translations, and No Abstractions ~~~

    This translation is especially important when an object containing multiple attributes is split into multiple datamodels, so that some of the objects attributes are in one data store and the rest of the objects attributesare in a different data store. An example of this is when the attributes of an end-user are split across BSSapplications, such as billing and customer care applications, and OSS applications, such as service provisioningand activation applications. Without this set of hierarchical relationships, data consistency andcoherency is lost, as there is no way to relate and synchronise the data between these two disparate typesof applications

    since almost all legacy applications do not use a standard information or data model, the informationin the legacy application data models exist as separate repositories. This results in approachessuch as that shown in Figure 3-5 (this figure is taken from [Strassner05a], Chapter 11, Figure 11-4), inwhich the capabilities of the device itself drive the applications that use it. Figure 3-5 reflects the relativelycommon practice to use multiple management systems from the same vendor to manage differentdevices manufactured by that vendor. This figure shows four applications for building Virtual PrivateNetworks (VPNs). Two applications are concerned with the type of transport used to supply the VPN, oneis focused on traffic engineering, and one is focused on Quality of Service (QoS). There are several problemswith the approach shown in this figure. First, a stovepipe design mentality is embedded in the approach looking at the first two translation layers (from IP security (IPsec) and Multi-Protocol LabelSwitching (MPLS) VPNs to different device models), the common abstraction of a VPN is missing.Hence, if a different type of VPN is later needed, this approach requires it to essentially be built fromscratch. Similarly, common abstractions for traffic engineering and QoS do not exist. Using heterogeneousdevices exacerbates this problem, since different languages and programming models are introducedwithout any abstraction services that the business needs at any given time. In other words, current networks are unaware of businessneeds in the first place.Even if the problems in Figure 3-5 are fixed by the use of a common information model, the knowledgedefined by information and data models are insufficient to solve the problem of data harmonisation that isdescribed above. This is because information and data models cannot: realise that the same object is named differently in two different applications (e.g., a billing applicationnames a Customer Strassner.John, whilst a fault management application names thesame Customer JohnS), and hence applications using that information or data model end uptreating what should be the same shared object as two different objects establish semantic relationships between disparate information (not just synonyms and antonyms,but other relationships that compare different entities, such as whether a set of commands fromone vendor will provide similar functionality to a different set of commands from another vendor)

    It is a modelling syntax aimed primarily at creating system modelsUML is the de facto standard for representing information modelsAllows: Re-using existing data, Modelling the State and Lifecycle of a Managed Entity and Modelling the Behaviour of a Managed Entity

    Syntax only - UML is just a language; it tells you what model elements and diagrams are available and the rules associated with them. It does not tell you what diagrams to create. Process-independent - the process by which the models are created is separate from the definition of the language. You will need a process in addition to the use of UML itself.

    Syntax only - UML is just a language; it tells you what model elements and diagrams are available and the rules associated with them. It does not tell you what diagrams to create. Process-independent - the process by which the models are created is separate from the definition of the language. You will need a process in addition to the use of UML itself.

    Abstraction is a fundamental principle of modelling. A system model is created at different levels, starting at the higher levels and adding more levels with more detail as more is understood about the system. When complete, the model can be viewed at several levels. So abstraction is about: Looking only at the information that is relevant at the time Hiding details so as not to confuse the bigger picture

    *Even if the problems in Figure 3-5 are fixed by the use of a common information model, the knowledgedefined by information and data models are insufficient to solve the problem of data harmonisation that isdescribed above. This is because information and data models cannot: realise that the same object is named differently in two different applications (e.g., a billing applicationnames a Customer Strassner.John, whilst a fault management application names thesame Customer JohnS), and hence applications using that information or data model end uptreating what should be the same shared object as two different objects establish semantic relationships between disparate information (not just synonyms and antonyms,but other relationships that compare different entities, such as whether a set of commands fromone vendor will provide similar functionality to a different set of commands from another vendor)

    The same object (Customer) has attributes in different ap

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