1. e-Science AHM, Nottingham. September 20 th, 2005. Glen Dobson: g.dobson@lancs.ac.uk An OWL Ontology for QoS Glen Dobson (Russell Lock, Ian Sommerville) Lancaster University g.dobson@lancs.ac.uk

2. e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk Overview QoSOnt is an OWL ontology for Quality of Service (QoS) I will attempt to answer: What is an ontology? What is OWL? What is QoS? Why is a QoS ontology needed? How should one go about designing such an ontology? What are the possible approaches? What are the difficulties?

3. e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk What is an ontology? Standard answer: A specification of a conceptualization (Gruber) Pragmatically: A description of the concepts and relationships which exist in some domain using a formal language. An ontology is an engineering artefact for machine understanding Its purpose is important. It should represent shared conceptualisations. A shared vocabulary is the fundamental component of an ontology Domain rules are also important

4. e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk What is OWL? OWL is the Web Ontology Language Supports sharing ontologies via the web Built on top of RDF (and XML in turn) Aim is to enable machine interpretation of terms and their relationships It is a Description Logic Primary constructs are Classes and their Properties A Class defines a set of Individuals by precisely stating a set of membership conditions. Main form of inference is subsumption i.e. is Class B a complete subset of Class A? + Classification: What Classes is Invidual I a member of?

5. e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk OWL in the Semantic Web OWL

6. e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk Class Definitions in OWL Classes can be described As named resources (as in RDF) As an enumeration By constraints on their Properties By combining other Classes using set operators Descriptions be combined to give a Class definition using OWLs: subClassOf equivalentClass disjointWith

7. e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk OWL and Inference A Dog could be asserted to be a Mammal. Or this classification could be inferred based upon the Class Dogs Properties (and Property restrictions) E.g. warm blooded, feeds young with milk, internal fertilisation, etc. Problem of maintaining a polyhierarchy manually a Dog is a Mammal, an Animal, a Pet, etc. Therefore assert a monohierarchy and have multiple classifications inferred

8. e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk What is your definition of QoS? Any non-functional aspect of a system that someone may use to judge quality Extends the definition in distributed multimedia where QoS is primarily concerned with the network (and performance in particular) In practice we have concentrated primarily on dependability – but the concepts apply beyond this. What QoS concepts are modelled? We are primarily concerned with the core concepts of QoS (e.g. attributes, metrics) Also some consideration to QoS requirements

9. e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk Why an ontology for QoS? To provide a shared vocabulary For use primarily by machines – but perhaps also in human-readable documents (e.g. requirements documents, SLAs). To embody machine interpretable knowledge e.g. QoS brokers may need to translate between terms/infer aggregate values/convert units, etc. Also the provision of QoS description and reasoning capabilities to the semantic web

10. e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk QoS Sub-Systems Service Discovery Service negotiation Service Mediation Service Monitoring Service Agreements Service Payment Service Operation Banking systems Service Differentiation Law Re-negotiation QoS Prediction Workflow Planning

11. e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk What added value could a QoS ontology provide? Translation based upon machine understanding Translation of units, computation of composite metrics, inference of aggregate QoS for workflows Leeway in syntax matching i.e. multiples terms can refer to the same thing An interlingua for translation between other QoS languages A means for agents to communicate

12. e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk QoSOnt Structure At the core of QoSOnt is a taxonomy of Attributes and Metrics i.e. two trees formed using the subClassOf construct An attribute is e.g. reliability, performance A metric is e.g. Probability of Failure on Demand, Transactional Throughput This becomes a (complex) directed graph once properties are considered e.g. The Property hasMetric (and its inverse isMetricOf) is the basic link between the attribute and metric trees

13. e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk Danger of Ontology Creep Should we provide a model to represent: Time Currently we do – but we should instead use the OWL- Time ontology. Ways of composing metrics, Mathematical constructs that dont exist in OWL This originally put us off and thus we have a separate XML language as well as the ontology. Ways of composing services We currently use a very shallow model – but perhaps this is all that is needed?

14. e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk QoSOnt High-Level Structure Time PerformanceDependabilityEtc …. Attribute Layer Low level conceptsBase concepts Metrics Metric Layer Underlying OWL Metric Instances

15. e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk IFIP 10.4 Dependability Taxonomy Our example of an attribute layer ontology Familiar Fault-Error-Failure model Main point of linkage is DependabilityAttribute is a subclass of QoSAttribute Shows how a detailed model of certain attributes can help E.g. without the definition of Failure, Failure Domain it is impossible to be specific about what a Probability of Failure On Demand refers to

16. e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk Overview of Metric Definition

17. e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk Representing QoS Requirements As OWL Classes using built-in OWL constructs Datatype support is poor No consistent way of using custom XML types Reasoning support for quantification over datatypes (e.g. allValuesFrom 0-100) is poor. Level of datatype support mandated by OWL spec is poor Using QoSOnt defined Classes, Properties, Restrictions, etc. As a separate (XML) language referencing the ontology

18. e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk SQRM Tool

19. e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk Requirements Matching in SQRM

20. e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk Evaluation/Future (1) An ontology is a good idea – but a large- scale standardisation effort is required Need external input in order to evolve Two interested parties are now involved Requirements representation and matching using built-in OWL features would be nice Need to wait for OWL to develop Need to look at SWRL (Semantic Web Rules Language) E.g. would provide a neater way to express unit conversions

21. e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk Evaluation/Future (2) Need to work on tools that make use of QoSOnt (and also enhance SQRM) Difficult to evaluate otherwise since the purpose is machine-machine understanding But are there really a lot of QoS semantics to model? Service Composition/Workflow Integrating existing work with ontology

22. e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk Questions For more information: http://digs.sourceforge.net