Web Modeling-based Approach to Automating Web Services Mediation, Choreography and Discovery

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Marco Brambilla

Web Modeling-based Approach to Automating Web Services Mediation, Choreography and Discovery SWS Challenge Stanford University, March, 8 2006 Marco Brambilla, Stefano Ceri, Dario Cerizza, Emanuele Della Valle, Federico Facca, Piero Fraternali, Christina Tziviskou

Summary ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Mediator modeling roadmap WebML framework

Mediator modeling roadmap BPM modeling ,[object Object],[object Object],[object Object],[object Object]

Mediator modeling roadmap WebML domain description modeling ,[object Object],ShipmentService where ShipmentService.shipTo not in ShipmentService . locatedIn Self TO Europe where Self.locatedIn isa Europe

Feature of OWL-DL in webML domain description WebML structural + (C i ≠  ; A ≠ T) + (A, C i ≠  , T) - + - - + + ( C i ≠  ) + ( C i ≠  ) +  (must identify R and R - with the same name) - - - + (domain(R 2 ), range(R 2 ) ≠ T) + (domain(R 2 ), range(R 2 ) ≠ T) + + - - + - - rhs rhs - - rhs rhs rhs rhs rhs rhs

Mediator modeling roadmap WebML Hyper-text Navigation models ,[object Object],[object Object],[object Object]

[object Object],[object Object],Mediator modeling roadmap WebML Service Navigation models

Mediator modeling roadmap From Business activity to Web Service ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Mediator modeling roadmap Activity modeling in the hypertext ,[object Object],[object Object],[object Object],[object Object],[object Object],Lowering Lifting

Demo of the mediator ,[object Object],[object Object],[object Object],[object Object],[object Object]

Demo RosettaNet System PO service ,[object Object],[object Object],[object Object],[object Object],[object Object]

Demo Moon Line Confirmation service ,[object Object],[object Object],[object Object]

Managing dynamics.. How to ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Managing dynamics Addressing Challenge Phase II

Managing dynamics GLUE as discovery engine ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],c 2 a c 5 c 1 c 2 c 3 c 4 a b b b c 2 REQUESTER PROVIDERS ggMediator (goal refinement) wgMediator (discovery) Class of WS C Class of Goals A Class of Goals B

Why Glue? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Conclusions and future works ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

[object Object],[object Object],Emanuele Della Valle CEFRIEL [email_address] Marco Brambilla Politecnico di Milano [email_address] Federico M. Facca Politecnico di Milano [email_address]

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The Web Science course focuses on the study of large-scale socio-technical systems associated with the World Wide Web. It considers the relationship between people and technology, the ways that society and technology complement one another and the way they impact on broader society. These analyses are inherently associated with Big Data management issues. The course is organised in four parts. 1. Syntax In the first part, the course introduces the basis of content analysis. If focuses on the syntactic aspects, covering the fundamentals of natural language processing and text mining. It describes the structure and typical characteristics of the different web sources, spanning search results, social media contents, social network structures, Web APIs, and so on. It also provides an overview of the basic Web analysis techniques applied in Web search and Web recommendation. 2. Semantics In the second part, the course presents semantic technologies. These technologies are very important nowadays because they allow to treat the "variety" dimension of Big Data, i.e., they enable integration of multiple and diverse sources of information, which is typical on the modern Web platform. Covered topics include: - RDF - a flexible data model to represent heterogeneous data - OWL - a flexible ontological language to model heterogeneous data sources - SPARQL - a query language for RDF. It shows how to put all the pieces together in order to achieve interoperability among heterogeneous information sources 3. Time The third part covers the realm of temporal-dependent data. The topics covered here allow to treat the "velocity" dimension of Big Data. It shows the importance for many Big Data analysis scenarios to process data stream, coming for instance from Internet of Things (IoT) and Social Media sources; and it describes how to apply semantic and syntactic techniques in the context of time-dependent information. For instance, it shows how to extend RDF to model RDF streams, how to extend SPARQL to continuously process RDF streams and how to reason on those RDF Streams 4. Applications In the fourth part, the course focuses on specific application scenarios and presents the typical settings and problems where the presented techniques can be applied. This part discusses settings such as: big data analysis for smart cities; data analytics for brand monitoring (marketing) and event monitoring; data analysis for trend detection and user engagement; and so on.

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1. Web Modeling-based Approach to Automating Web Services Mediation, Choreography and Discovery SWS Challenge Stanford University, March, 8 2006 Marco Brambilla, Stefano Ceri, Dario Cerizza, Emanuele Della Valle, Federico Facca, Piero Fraternali, Christina Tziviskou

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3. Mediator modeling roadmap WebML framework

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6. Feature of OWL-DL in webML domain description WebML structural + (C i ≠  ; A ≠ T) + (A, C i ≠  , T) - + - - + + ( C i ≠  ) + ( C i ≠  ) +  (must identify R and R - with the same name) - - - + (domain(R 2 ), range(R 2 ) ≠ T) + (domain(R 2 ), range(R 2 ) ≠ T) + + - - + - - rhs rhs - - rhs rhs rhs rhs rhs rhs

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15. Managing dynamics Addressing Challenge Phase II

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