Linking and publishing data in the Linked Open Data format increases the interoperability and discoverability of resources over the Web. To accomplish this, the process comprises several design decisions, based on the Linked Data principles that, on one hand, recommend to use standards for the representation and the access to data on the Web, and on the other hand to set hyperlinks between data from different sources. Despite the efforts of the World Wide Web Consortium (W3C), being the main international standards organization for the World Wide Web, there is no one tailored formula for publishing data as Linked Data. In addition, the quality of the published Linked Open Data (LOD) is a fundamental issue, and it is yet to be thoroughly managed and considered. In this doctoral thesis, the main objective is to design and implement a novel framework for selecting, analyzing, converting, interlinking, and publishing data from diverse sources, simultaneously paying great attention to quality assessment throughout all steps and modules of the framework. The goal is to examine whether and to what extent are the Semantic Web technologies applicable for merging data from different sources and enabling end-users to obtain additional information that was not available in individual datasets, in addition to the integration into the Semantic Web community space. Additionally, the Ph.D. thesis intends to validate the applicability of the process in the specific and demanding use case, i.e. for creating and publishing an Arabic Linked Drug Dataset, based on open drug datasets from selected Arabic countries and to discuss the quality issues observed in the linked data life-cycle. To that end, in this doctoral thesis, a Semantic Data Lake was established in the pharmaceutical domain that allows further integration and developing different business services on top of the integrated data sources. Through data representation in an open machine-readable format, the approach offers an optimum solution for information and data dissemination for building domain-specific applications, and to enrich and gain value from the original dataset. This thesis showcases how the pharmaceutical domain benefits from the evolving research trends for building competitive advantages. However, as it is elaborated in this thesis, a better understanding of the specifics of the Arabic language is required to extend linked data technologies utilization in targeted Arabic organizations.

Digital technologies witnessed rapid advancements in many domains such as computing, programming, cloud computing, data storing, networking, satellite broadcasting, mobile technologies, but increasingly also in the natural sciences, such as medicine, biology, chemistry, pharmacy, etc. These advancements lead to a massive explosion in data volumes which expected to exceed 175ZB (175x1021 Byte) by end of the year 2025. When data size exceeds normal manageable storable sizes, it will be called “big data”. Organizing and analyzing this “big data” with appropriate tools would produce quite valuable results helping decisions and policymakers. Big data also can assist significantly improve the life quality of much of the world’s population. The United Nations, governments, non-profitable and other organizations are utilizing big data to assist achieving the UN’s Sustainable Development Goals (SDG), a set of 17 targets pertinent to protect the natural environment, fighting hunger and poverty, reducing inequality, improving health outcomes and other things that will make life better around the world. Big data analysis could be used in many ways to enhance the understanding of the progress towards the SDGs, specify how best to meet SDGs targets, and ensure accountability. The UN has set up a task team to explore how to use big data to help achieve the SDGs. A survey by the task team found that big data projects most frequently focused on the “no poverty” goal, it was found that mobile phone data was the most common data source.

Abstract. The paper examines the process of creating and publishing an Arabic Linked Drug Dataset based on open drug datasets from selected Arabic countries and discusses quality issues considered in the linked data lifecycle when establishing a semantic Data Lake in the pharmaceutical domain. Through representation of the data in an open machine-readable format, the approach provides an optimum solution for information and dissemination of data and for building specialized applications. Authors contribute to opening the drug datasets from Arabic countries, interlinking the data with diverse repositories such as DrugBank, and DBpedia, and publishing it in a standard open manner that allows further integration and building different business services on top of the integrated data. This paper showcases how drug industry can take full advantage of the emerging trends for building competitive advantages. However, as is elaborated in this paper, better understanding of the specifics of the Arabic language is needed in order to extend the usage of linked data technologies in Arabic companies.

Linked Open Data illustrates the concept that provides an optimum solution for information and dissemination of data, through the representation of the

data in an open machine readable format and to interlink it from diverse repositories to enable diverse usage scenarios for both humans and machines.

The pharmaceutical/drug industry was among the first that validated the applicability of the approach for interlinking and publishing open linked data. Yet, open issues arose clearly when trying to apply the approach to datasets coded in languages other than English, for instance, in Arabic languages. Author’s objective is to examine in detail the requirements specification process for building Linked Data application taking into consideration the possibility of reusing recently published datasets and tools. Main conclusions derived from this study are that making drug datasets accessible and publish it in an open manner in linkable format adds great value by integration to other notable datasets. Author’s main contribution is the enhancement of Arabic knowledge graph based on drug data from selected Arabic countries and the novel methodology for building Linked Data applications.

Abstract. Linked Open Data illustrates the concept that provides an optimum solution for information and dissemination of data, through the representation of the data in an open machine-readable format and to interlink it from diverse repositories to enable diverse usage scenarios for both humans and machines. The pharmaceutical/drug industry was among the first that validated the ap-plicability of the approach for interlinking and publishing open linked data. This paper examines in detail the process of building Linked Data application taking into consideration the possibility of reusing recently published datasets and tools. Main conclusions derived from this study are that making drug da-tasets accessible and publish it in an open manner in linkable format adds great value by integration to other notable datasets. Yet, open issues arose clearly when trying to apply the approach to datasets coded in languages other than English, for instance, in Arabic languages.

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).