Semantic-based transaction model for web service

Li, Shing‐Han; Huang, Shi‐Ming; Yen, David C.; Sun, Jui-Chang

doi:10.1007/s10796-013-9409-x

Cited by 9 publications

(2 citation statements)

References 27 publications

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“…The authors of the next paper (Li et al 2013) proposed a new transaction model based on semantic, to monitor and evaluate the efficiency of heterogeneous Web services usage. The model is claimed to be useful in cloud environment, which is typically formed by heterogeneous software systems most of which are implemented using Web service technologies.…”

Section: Semantic-based Transaction Modelmentioning

confidence: 99%

Special issue on Semantic Information Management guest editorial

Kotsis

Khalil

2013

Inf Syst Front

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Barely more than 10 years after the birth of the World Wide Web, the Global Information Infrastructure is daily reality. In spite of the many applications in all domains of our societies: e-business, e-commerce, e-learning, e-science, and e-government, for instance, and in spite of the tremendous advances by engineers and scientists, the seamless integration of information and services remains a major challenge. The current shared vision for the future is one of semantically rich information and service oriented architecture for global information systems. This vision is at the convergence of progress in technologies such as XML, Web services, RDF, OWL, of multimedia, multimodal, and multilingual information retrieval, and of distributed, mobile and ubiquitous computing.Semantic Information Management (SIM) can be identified as the discipline that studies the integration and management of multi-modal information from distributed, heterogeneous, and autonomous sources based on their meaning. SIM is deemed necessary since there is an increasing tendency of inter-business and inter-applications sharing of data. The data can be written and stored using different standard and format. Hence, we need a platform to manage the data so that it can be universally understood. SIM as a research has variety research challenges. The first challenge is the identification of suitable meta-model that can ensure the quality of the integrated data. The next challenge is the adoption of ever-increasing number of standards used by enterprises. To comply with standards, enterprises have to represent their data uniquely and thus, the challenge to integrate them with data from other enterprises increases. XML has become a standard data format widely used in many organizations, thus leading to a growing need for exchanging and integrating multiple XML data sources across different application systems. XML has been regarded as a de-facto standard for data exchanges in enterprises. Integrating these sources requires an integration of their schemas. The main challenge is schema integration where the semantic is maintained.Aligning with the previous challenge, many enterprises these days have to comply with various government and professional regulations in managing their data. It makes the integration of data from multi-discipline enterprises and cross-regulated regions even more difficult. Another challenge is the ability to trace back the integrated information to its original source and format. The issue of forward and backward compatibility is far more complex than in traditional data integration research domain. The issue becomes more complex in a social network setting. Social networks consist mainly of groups of inter-connected people. This has played an important role in changing the way people interact with each other. Social networks analysis focuses on studying patterns of communication and exchange of information between people, which may influence not only on the individuals who adopt them, but also on the societies and organiz...

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Section: Semantic-based Transaction Modelmentioning

confidence: 99%

Special issue on Semantic Information Management guest editorial

Kotsis

Khalil

2013

Inf Syst Front

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“…Las auditorías de información, permiten una mayor comprensión de la organización y sus capacidades (Pantry and Griffiths, 2004), están orientadas hacia los activos explícitos existentes, como registros y documentos en repositorios electrónicos o no, bases de datos y colecciones e identifican si existe redundancia, duplicación, inconsistencia, incompatibilidad en el sistema de GI (Ponjuán Dante, 2004). Es una evaluación sobre las competencias informacionales de sus integrantes (Reißland, 2013) sobre la calidad y uso de los servicios de información en ambiente web (Li et al 2013) y sobre las capacidades de generación, protección y gestión del capital intelectual (Kankanala, 2012). Permiten comprobar informaciones asimétricas en empresas de un mismo perfil (Chen & Liu, 2013;Ho & Wang, 2013), e identificar las barreras que impiden el intercambio de información y conocimiento (Jackson et al, 2012).…”

Section: Introductionunclassified

Auditoría integrada de Información + Conocimiento: aplicación en un caso de estudio

2016

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, conformada por siete etapas con un enfoque híbrido dirigida a revisar la estrategia y la política de gestión de información y conocimiento, identificar e inventariar y mapear los recursos de I+C y sus flujos, y valorar los procesos asociados a su gestión. La alta dirección de este centro, sus especialistas e investigadores manifestaron la efectividad de la metodología aplicada cuyos resultados propiciaron reajustar la proyección estratégica en relación con la gestión de la I+C, rediseñar los flujos informativos de los procesos claves, disponer de un directorio de sus expertos por áreas y planificar el futuro aprendizaje y desarrollo profesional. Palabras clave: Auditoría de información; auditoría de conocimiento; gestión del conocimiento; gestión de información; auditoría de I+C.

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