Semantic Data Integration Approaches for E-Governance

Al-Sudairy, Mohammed T.; Vasista, T. G. K.

doi:10.5121/ijwest.2011.2101

Cited by 14 publications

(4 citation statements)

References 26 publications

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“…Therefore, an integrated approach is required to overcome the aforementioned issue. This resonates to the idea by Al-Sudairy and Vasista that creating an integrated information system or application has been a challenge in the development of technology that demands certain data and its resources must be heterogenic [22,23].…”

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confidence: 78%

Information system of Limboto Lake potential management

et al. 2019

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Limboto Lake is one of the lakes in Gorontalo Province; its water supply is generated from 23 small and large rivers. The lake holds potential in several sectors, e.g., tourism, fisheries, socio-economy and culture. However, such an advantage has no quality information system as it is found that there are no particular services that manage the information regarding Limboto Lake accurately. The objective of this research is to create an information system for the management of the potential area of the lake to provide quality services to access the information accurately and completely. The provided information is also updated timely. This research employed the System Development Life Cycle (SDLC) method in the development of the information system. Furthermore, the data were collected from interview, observation, and reviewing literature and document. This system is tested using white box and black box where it generated the expected outcome and is web-based. The output of this research is a system that eases the society to access the information regarding the management of the potential area in Limboto Lake.

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confidence: 78%

Information system of Limboto Lake potential management

et al. 2019

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“…Semantic enrichment is a process for horizontal data integration based on the use of ontologies to integrate and semantically enhance data models. Vasista, 2011). Semantic web technology can prove to be an excellent test bed for scalability of various approaches and a common ground for experimenting with hybrid approaches.…”

Section: Semantic (Big Data) Predictive Analysismentioning

confidence: 99%

Role of Electronic Customer Relationship Management in Demand Chain Management

Vasista

Alabdullatif

2017

International Journal of Information Systems and Supply Chain Management

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In 21st century, collaborative business supply chain environments are required to be proactive rather than reactive so that they can better deal with the uncertainty, growing competition, shorter cycle times, more demanding customers and pressure to cut costs. Demand chain management as a new business model requires investing in consumer insights and closer relationships in the supply chain to conduct predictive analysis of retail intelligent solutions. In this regard new kinds of methodologies are required to be discussed. However, at the execution level the limitations in terms of scalability, data integration and knowledge based decision support to providers or suppliers in terms of strategy building and in providing deductive inference capabilities are to be addressed. Therefore, it is required to describe how predictive analytics helps in constructing the knowledge base to conduct verification and validation in terms of semantic predictive analytic for the domain of demand chain management.

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“…The combination of RDF/OWL has been used in many specific scenarios for the construction of flexible data semantic models [5] [6] [7]. Interest in mapping relational data to RDF is increasing for the purpose of publishing linked data [8]. In this direction, SPARQL is the W3C recommended query language for information retrieving from RDF documents.…”

Section: Introductionmentioning

confidence: 99%

Ontology-based Dynamic Building of Relational Data Views

Ponce-Toste¹,

Pérez-Gort²,

Peña³

et al. 2013

Procedings of the Fourth International Workshop on Knowledge Discovery, Knowledge Management and Decision Support

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Traditionally, data views are seen as static, syntactically correct, data sets. The semantics of the data is not explicitly encoded in RDB (relational databases) but implicitly on the application level. However, the needs to create context-aware browsing methods in changing scenarios are demanding more flexible mechanisms. Data views need to be semantically enriched for capturing the real world changes. In this paper, we study how the semantics of RDB can be described and used in an ontology-based method for building dynamic data views. Our tests show that our approach increases the flexibility of information systems whilst decreases their maintenance costs.

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Semantic Data Integration Approaches for E-Governance

Abstract: ABSTRACT

Cited by 14 publications

References 26 publications

Information system of Limboto Lake potential management

Information system of Limboto Lake potential management

Role of Electronic Customer Relationship Management in Demand Chain Management

Ontology-based Dynamic Building of Relational Data Views

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