Quality Metrics for Evaluating Data Provenance

Author(s):  
Syed Ahsan ◽  
Abad Shah

With the proliferation of Web, a tremendous amount of data is available to researchers and scientists in computational sciences, business organizations and general public. This has resulted in an increased importance of data intensive domains such as Bioinformatics, which are increasingly using Web-based applications and service-oriented architecture which uses the data available on the Web sources. To trust the data available on Web and the results derived from it, a Data Provenance system must be devised to ensure authenticity and credibility of Web resources. In this paper we have discussed various domains which necessitate such data provenance systems. We propose a set of tangible parameters which affect the quality of data and define quality metrics to evaluate those parameters. The chapter concludes with a section on future directions in which we identify various research problems and possible applications of data provenance.

Author(s):  
Pethuru Raj Chelliah

Hydrology is an increasingly data-intensive discipline and the key contribution of existing and emerging information technologies for the hydrology ecosystem is to smartly transform the water-specific data to information and to knowledge that can be easily picked up and used by various stakeholders and automated decision engines in order to forecast and forewarn the things to unfold. Attaining actionable and realistic insights in real-time dynamically out of both flowing as well as persisting data mountain is the primary goal for the aquatic industry. There are several promising technologies, processes, and products for facilitating this grand yet challenging objective. Business intelligence (BI) is the mainstream IT discipline representing a staggering variety of data transformation and synchronization, information extraction and knowledge engineering techniques. Another paradigm shift is the overwhelming adoption of service oriented architecture (SOA), which is a simplifying mechanism for effectively designing complex and mission-critical enterprise systems. Incidentally there is a cool convergence between the BI and SOA concepts. This is the stimulating foundation for the influential emergence of service oriented business intelligence (SOBI) paradigm, which is aptly recognized as the next-generation BI method. These improvisations deriving out of technological convergence and cluster calmly pervade to the ever-shining water industry too. That is, the bubbling synergy between service orientation and aquatic intelligence empowers the aquatic ecosystem significantly in extracting actionable insights from distributed and diverse data sources in real time through a host of robust and resilient infrastructures and practices. The realisable inputs and information being drawn from water-related data heap contribute enormously in achieving more with less and to guarantee enhanced safety and security for total human society. Especially as the green movement is taking shape across the globe, there is a definite push from different quarters on water and ecology professionals to contribute their mite immensely and immediately in permanently arresting the ecological degradation. In this chapter, we have set the context by incorporating some case studies that detail how SOA has been a tangible enabler of hydroinformatics. Further down, we have proceeded by explaining how SOA-sponsored integration concepts contribute towards integrating different data for creating unified and synchronized views and to put the solid and stimulating base for quickly deriving incisive and decisive insights in the form of hidden patterns, predictions, trends, associations, tips, etc. from the integrated and composite data. This enables real-time planning of appropriate countermeasures, tactics as well as strategies to put the derived in faster activation and actuation modes. Finally the idea is to close this chapter with an overview of how SOA celebrates in establishing adaptive, on-demand and versatile SOHI platforms. SOA is insisted as the chief technique for developing and deploying agile, adaptive, and on-demand hydrology intelligence platforms as a collection of interoperable, reusable, composable, and granular hydrology and technical services. The final section illustrates the reference architecture for the proposed SOHI platform.


2014 ◽  
Vol 4 (1) ◽  
pp. 50-62 ◽  
Author(s):  
Sudhansu Shekhar Patra ◽  
R. K. Barik

Cloud computing has recently received considerable attention, as a promising approach for delivering Information and Communication Technologies (ICT) services as a utility. In the process of providing these services it is necessary to improve the utilization of data centre resources which are operating in most dynamic workload environments. Datacenters are integral parts of cloud computing. In the datacenter generally hundreds and thousands of virtual servers run at any instance of time, hosting many tasks and at the same time the cloud system keeps receiving the batches of task requests. It provides services and computing through the networks. Service Oriented Architecture (SOA) and agent frameworks renders tools for developing distributed and multi agent systems which can be used for the administration of cloud computing environments which supports the above characteristics. This paper presents a SOQM (Service Oriented QoS Assured and Multi Agent Cloud Computing) architecture which supports QoS assured cloud service provision and request. Biomedical and geospatial data on cloud can be analyzed through SOQM and has allowed the efficient management of the allocation of resources to the different system agents. It has proposed a finite heterogeneous multiple vm model which are dynamically allocated depending on the request from biomedical and geospatial stakeholders.


2011 ◽  
pp. 1610-1636
Author(s):  
Pethuru Raj Chelliah

Hydrology is an increasingly data-intensive discipline and the key contribution of existing and emerging information technologies for the hydrology ecosystem is to smartly transform the water-specific data to information and to knowledge that can be easily picked up and used by various stakeholders and automated decision engines in order to forecast and forewarn the things to unfold. Attaining actionable and realistic insights in real-time dynamically out of both flowing as well as persisting data mountain is the primary goal for the aquatic industry. There are several promising technologies, processes, and products for facilitating this grand yet challenging objective. Business intelligence (BI) is the mainstream IT discipline representing a staggering variety of data transformation and synchronization, information extraction and knowledge engineering techniques. Another paradigm shift is the overwhelming adoption of service oriented architecture (SOA), which is a simplifying mechanism for effectively designing complex and mission-critical enterprise systems. Incidentally there is a cool convergence between the BI and SOA concepts. This is the stimulating foundation for the influential emergence of service oriented business intelligence (SOBI) paradigm, which is aptly recognized as the next-generation BI method. These improvisations deriving out of technological convergence and cluster calmly pervade to the ever-shining water industry too. That is, the bubbling synergy between service orientation and aquatic intelligence empowers the aquatic ecosystem significantly in extracting actionable insights from distributed and diverse data sources in real time through a host of robust and resilient infrastructures and practices. The realisable inputs and information being drawn from water-related data heap contribute enormously in achieving more with less and to guarantee enhanced safety and security for total human society. Especially as the green movement is taking shape across the globe, there is a definite push from different quarters on water and ecology professionals to contribute their mite immensely and immediately in permanently arresting the ecological degradation. In this chapter, we have set the context by incorporating some case studies that detail how SOA has been a tangible enabler of hydroinformatics. Further down, we have proceeded by explaining how SOA-sponsored integration concepts contribute towards integrating different data for creating unified and synchronized views and to put the solid and stimulating base for quickly deriving incisive and decisive insights in the form of hidden patterns, predictions, trends, associations, tips, etc. from the integrated and composite data. This enables real-time planning of appropriate countermeasures, tactics as well as strategies to put the derived in faster activation and actuation modes. Finally the idea is to close this chapter with an overview of how SOA celebrates in establishing adaptive, on-demand and versatile SOHI platforms. SOA is insisted as the chief technique for developing and deploying agile, adaptive, and on-demand hydrology intelligence platforms as a collection of interoperable, reusable, composable, and granular hydrology and technical services. The final section illustrates the reference architecture for the proposed SOHI platform.


2015 ◽  
pp. 2262-2273 ◽  
Author(s):  
Sudhansu Shekhar Patra ◽  
R. K. Barik

Cloud computing has recently received considerable attention, as a promising approach for delivering Information and Communication Technologies (ICT) services as a utility. In the process of providing these services it is necessary to improve the utilization of data centre resources which are operating in most dynamic workload environments. Datacenters are integral parts of cloud computing. In the datacenter generally hundreds and thousands of virtual servers run at any instance of time, hosting many tasks and at the same time the cloud system keeps receiving the batches of task requests. It provides services and computing through the networks. Service Oriented Architecture (SOA) and agent frameworks renders tools for developing distributed and multi agent systems which can be used for the administration of cloud computing environments which supports the above characteristics. This paper presents a SOQM (Service Oriented QoS Assured and Multi Agent Cloud Computing) architecture which supports QoS assured cloud service provision and request. Biomedical and geospatial data on cloud can be analyzed through SOQM and has allowed the efficient management of the allocation of resources to the different system agents. It has proposed a finite heterogeneous multiple vm model which are dynamically allocated depending on the request from biomedical and geospatial stakeholders.


2014 ◽  
Vol 11 (1) ◽  
pp. 30-56
Author(s):  
Wenge Rong ◽  
Qinfen Wu ◽  
Yuanxin Ouyang ◽  
Kecheng Liu ◽  
Zhang Xiong

The convergence of information technology and diverse business requirements is making the organization information systems more complex. Quickly integrating existing systems and developing new applications to serve the requirement of flexible business environments have become a key factor for organizations to gain a competitive edge. To meet this challenge, the concept of Service Oriented Architecture (SOA) has been proposed and widely lauded as an innovative business oriented solution. To better utilize SOA's advantages, several research problems should be attached much importance among which service lifecycle management is a notable one, which is one of the critical mechanisms leading to higher service quality. A large number of service lifecycle models have been proposed in the literature while few of them clearly indicate the integration of the lifecycle processes with stakeholders. In this research, a conceptual stakeholder identification and analysis framework is proposed by which stakeholders are analyzed within different service lifecycle stages. It is believed that this method can offer the researchers in the community further insight into service lifecycle management from the stakeholder's perspective.


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