Marwan Sabbouh

Web mashup scripting language

The Web Mashup Scripting Language (WMSL) enables an end-user (you) working from his browser, e.g. not needing any other infrastructure, to quickly write mashups that integrate any two, or more, web services on the Web. The end-user accomplishes this by writing a web page that combines HTML, metadata in the form of mapping relations, and small piece of code, or script. The mapping relations enable not only the discovery and retrieval of the WMSL pages, but also affect a new programming paradigm that abstracts many programming complexities from the script writer. Furthermore, the WMSL Web pages or scripts that disparate end-users (you) write, can be harvested by Crawlers to automatically generate the concepts needed to build lightweight ontologies containing local semantics of a web service and its data model, to extend context ontologies or middle ontologies, and to develop links, or mappings, between these ontologies. This enables an open-source model of building ontologies based on the WMSL Web page or scripts that end users (you) write.

Using Data Semantics to Enable Automatic Composition of Web Services

This paper demonstrates the automatic creation of a Web service that chains together existing Web services to achieve a particular goal. The generated service implements the necessary workflows to convert an instance data of one system into an instance data of another. This paper further demonstrates the reconciliation of structural, syntactic, and representational mismatches between the input instance and the desired output instance

Semantic Information Integration in the Large: Adaptability, Extensibility, and Scalability of the Context Mediation Approach

There is pressing need for effectively integrating information from an ever increasing number of available sources both on the web and in other existing systems. A key difficulty of achieving this goal comes from the pervasive heterogeneities in all levels of information systems. Existing and emerging technologies, such as the Web, ODBC, XML, and Web Services, provide essential capabilities in resolving heterogeneities in the hardware and software platforms, but they do not address the semantic heterogeneity of the data itself. A robust solution to this problem needs to be adaptable, extensible, and scalable. In this paper, we identify the deficiencies of traditional approaches that address this problem using hand-coded programs or require complete data standardization. The COntext INterchange (COIN) approach overcomes these deficiencies by declaratively representing data semantics and using a mediator to create the necessary conversion programs using a small number of conversion rules. The capabilities of COIN is demonstrated using an intelligence information integration example consisting of 150 data sources, where COIN can automatically generate the over 22,000 conversion programs needed to enable semantic integration using only six pa

Using Mapping Relations to Semi Automatically Compose Web Services

This paper accomplishes the automatic composition of web services by leveraging semantics in XML Schemas, and by automatically generating aligned ontologies from mappings between XML schemas. Hence, we propose to encode the import of schemas and their mappings in HTML, which when combined with JavaScript libraries enable a web user to write mashups that hide coding and ontological complexities and achieve automated data mediation.

Framework for the Analysis of the Adaptability, Extensibility, and Scalability of Semantic Information Integration and the Context Mediation Approach

Technological advances such as Service Oriented Architecture (SOA) have increased the feasibility and importance of effectively integrating information from an ever widening number of systems within and across enterprises. A key difficulty of achieving this goal comes from the pervasive heterogeneity in all levels of information systems. A robust solution to this problem needs to be adaptable, extensible, and scalable. In this paper, we identify the deficiencies of traditional semantic integration approaches. The COntext INterchange (COIN) approach overcomes these deficiencies by declaratively representing data semantics and using a mediator to create the necessary conversion programs from a small number of conversion rules. The capabilities of COIN is demonstrated using an example with 150 data sources, where COIN can automatically generate the over 22,000 conversion programs needed to enable semantic interoperability using only six parametizable conversion rules. This paper presents a framework for evaluating adaptability, extensibility, and scalability of semantic integration approaches. The application of the framework is demonstrated with a systematic evaluation of COIN and other commonly practiced approaches.

Characterization Framework and Design Patterns for the Disadvantaged User

Many service oriented architecture (SOA) approaches in use today presume the consistent availability of reliable networks and limitless resources. For some department of defense (DoD) and other government users, operating at the tactical edge, who may be disadvantaged in terms of network and resource availability, the current methods of development may not provide them with reliable capability. In this paper, we propose a method for capturing design patterns for the disadvantaged user using the common vocabulary of a characterization framework. We also provide a set of design patterns that minimize technical constraints, and derive the infrastructure requirements needed to implement a selected design pattern.