The development of Semantic Web technology has fueled the creation of a large amount of Linked Open Data. DBpedia is a good example of an open data repository extracted from the crowd sourced knowledge base, Wikipedia. Because of the way Wikipedia and DBpedia were created, the information available there is more vulnerable to grammatical errors, inconsistency, structures, and, data type problems. The introduction of the Arabic chapter of DBpedia created additional problems due to the nature of the language, when it comes to quality assessment issues. In this paper1, we focus on identifying challenges in quality assessment of Arabic DBpedia, as well as analysis of existing tools and methodologies used for Linked Data quality assessments.

Abstract — Big Data refers to data volumes in the range of Exabyte (1018) and beyond. Such volumes exceed the capacity of current on-line storage and processing systems. With characteristics like volume, velocity and variety big data throws challenges to the traditional IT establishments. Computer assisted innovation, real time data analytics, customer-centric business intelligence, industry wide decision making and transparency are possible advantages, to mention few, of Big Data. There are many issues with Big Data that warrant quality assessment methods. The issues are pertaining to storage and transport, management, and processing. This paper throws light into the present state of quality issues related to Big Data. It provides valuable insights that can be used to leverage Big Data science activities.

Keywords —Big Data, Quality assessment, stream processing, survey, Big Data frameworks.

With the integration of cloud computing, smart phones enormously improved in processing power, storage, communication efficiency, and reliability. The technical architecture of Cloud strongly supports the efficient delivery of services in mobile environment. Whereas the mobile cloud users can access all the resources as a service dynamically in elastic mode. Accessing Digital Intellectual Property as a Service (DIPaaS) on flexible economic basis is a major interest among the mobile users. DIP is the piece of work of human intellectual in digital form such as eBook, software program, e-painting, movie, song, computer game, and etc. The DIP services complex in nature, involves creator, manufacturer, distributor, licensing agencies, and service providers. However, the service limitations exist, shall be overcome with an understanding approach to Service Level Agreement (SLA). DIP applications consume a large of local resources and could not be implemented on standalone mobile phones. Therefore, we realize increasing demand for an efficient service-model which satisfies the mobile cloud users at large. We proposed the first service-model includes both technical and service architecture to encourage the stakeholders for DIP access in mobile cloud environment. Eventually we present an efficient access to Digital Intellectual Property as a Service in Mobile Cloud Environment (DIPaaSMCE).