Building Semantic Web Portals with WebML

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Current conceptual models and methodologies for Web applications concentrate on content, navigation, and service modeling. Although some of them are meant to address semantic web applications too, they do not fully exploit the whole potential deriving from interaction with ontological data sources and and from Semantic annotations. This paper proposes an extension to Web application conceptual models toward Semantic Web. We devise an extension of the WebML modeling framework that fulfills most of the design requirements emerging for the new area of Semantic Web. We generalize the development process to cover Semantic Web and we devise a set of new primitives for ontology importing and querying. Finally, an implementation prototype of the proposed concepts is proposed within the commercial tool WebRatio.

Building Semantic Web Portals with WebML Marco Brambilla and Federico M. Facca ICWE 2007 Como, 20th July 2007 http://home.dei.polimi.it/mbrambil http://twitter.com/MarcoBrambi http://www.slideshare.net/mbrambil

Agenda ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Introduction ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Introduction Requirements for metamodels of Semantic Web applications ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Extending WebML towards Semantic Web ,[object Object],+ Reuse of existing ontological data source + Specialized units for advanced queries over semantic data and annotation extraction

Extending WebML towards Semantic Web ,[object Object]

Extending WebML towards Semantic Web Evolving existing primitives ,[object Object],[object Object],instance uri class uri e.g. mf:Artist no input class uri e.g. vin:RedWine […] […] […] […]

Extending WebML towards Semantic Web New Advanced units for ontology querying Is x subproperty of y? Or: find subproperties/ find superproperties The list of URIs where property p has value v Or: find values/ find properties Is x property of y? Or: find the properties/ find the class Is x an instance of y? Or: find instances/ find classes Is x subclass of y? Or: find subclasses/ find superclasses

Extending WebML towards Semantic Web New Advanced units for ontology querying class uri instance uris instace uri classes uris instace & class uri boolean

Extending WebML towards Semantic Web Primitives for Ontology management ,[object Object],[object Object],[object Object]

Extending WebML towards Semantic Web Example of Usage of Advanced Units The value submitted in the form is passed to the HasPropertyValue unit that extracts a set of URIs of instances (albums or artists) with mm:soundsLike property equal to Val. The InstanceOf unit that checks if they are instances of the class Artist. The URIs are then shown in a list of Artists.

Implementation expirience ,[object Object],[object Object],[object Object]

Implementation expirience ,[object Object],[object Object],Design Time Descriptor Runtime Descriptor <SWINDEXUNIT class="mf:Track" id="swinu1" name="Tracks" ontology="onto1"> <DisplayedProperties property="mf:title"/> <DisplayedProperties property="mf:descripion"/> <SortProperties order="ascending" property="mf:title"/> <Filter boolean="or"> <FilterCondition id="fselector1" property="mf:playedBy" predicate="eq" name="Artist"/> </Filter> </SWINDEXUNIT> <descriptor service="org.webml.onto. SWIndexUnitService"> <onto>onto1</onto> ... <input-params> <input-param type="mm:Artist" name="swdau2.rdf:ID" /> </input-params> ... <query type="SELECT"> SELECT DISTINCT ?instance ?p1 ?p2 WHERE {?instance rdf:type mm:Track . ?instance mm:title ?p1 . ?instance mm:descriptor ?p2 . ?instance mm:playedBy ?fs1 . FILTER (?fs1 = $swdau2.rdf:ID$)} ORDER BY DESC(?p1) </query> </descriptor>

Conclusions & Future Works ,[object Object],[object Object],[object Object],[object Object],[object Object]

Thanks for the attention! ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],http://home.dei.polimi.it/mbrambil http://twitter.com/MarcoBrambi http://www.slideshare.net/mbrambil

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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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Building Semantic Web Portals with WebML

1. Building Semantic Web Portals with WebML Marco Brambilla and Federico M. Facca ICWE 2007 Como, 20th July 2007 http://home.dei.polimi.it/mbrambil http://twitter.com/MarcoBrambi http://www.slideshare.net/mbrambil

8. Extending WebML towards Semantic Web New Advanced units for ontology querying Is x subproperty of y? Or: find subproperties/ find superproperties The list of URIs where property p has value v Or: find values/ find properties Is x property of y? Or: find the properties/ find the class Is x an instance of y? Or: find instances/ find classes Is x subclass of y? Or: find subclasses/ find superclasses

9. Extending WebML towards Semantic Web New Advanced units for ontology querying class uri instance uris instace uri classes uris instace & class uri boolean

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11. Extending WebML towards Semantic Web Example of Usage of Advanced Units The value submitted in the form is passed to the HasPropertyValue unit that extracts a set of URIs of instances (albums or artists) with mm:soundsLike property equal to Val. The InstanceOf unit that checks if they are instances of the class Artist. The URIs are then shown in a list of Artists.

12. Case Study Example

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Building Semantic Web Portals with WebML

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