The fast evolution of the World Wide Web has offered the possibility to publish a huge amount of linked documents. Each such document represents a valuable piece of information. Linked Data is the term used to describe a method of exposing and connecting such documents. Even if this method is still in an experimental phase, it is already hard to process all existing data sources and the most obvious solution is to try and index them. The study addresses questions on how to design an index that will be capable to operate with millions of such entries. It analyses the existing projects and describes an index that may fulfill the requirements. The prototype implementation and the provided test results offer additional information about the index structure and effectiveness.

By way of a case study this paper illustrates and evaluates the Bibliographic Framework (or BIBFRAME) as means for harvesting and sharing bibliographic metadata over the Web for libraries. BIBFRAME is an emerging framework developed by the Library of Congress for bibliographic description based on Linked Data. Much like Semantic Web, the goal of Linked Data is to make Web “data aware” and transform the existing Web of documents into a Web of data. Linked Data leverages the existing Web infrastructure and allows linking and sharing of structured data for human and machine consumption. The BIBFRAME model attempts to contextualize the Linked Data technology for libraries. Library applications and systems contain high-quality structured metadata but this data is generally static in its presentation and seldom integrated with other internal metadata sources or linked to external Web resources. With BIBFRAME existing disparate library metadata sources such as catalogs and digital collections can be harvested and integrated over the Web. In addition, bibliographic data enriched with Linked Data could offer richer navigational control and access points for users. With Linked Data principles, metadata from libraries could also become harvestable by search engines, transforming dormant catalogs and digital collections into active knowledge repositories. Thus experimenting with Linked Data using existing bibliographic metadata holds the potential to empower libraries to harness the reach of commercial search engines to continuously discover, navigate, and obtain new domain specific knowledge resources on the basis of their verified metadata. The initial part of the paper introduces BIBFRAME and discusses Linked Data in the context of libraries. The final part of this paper outlines a step-by-step process for implementing BIBFRAME with existing library metadata.

This thesis deals with the issue of open data. The aim is to introduce to reader the currently very popular topic. Linking these data together gives us more advantages and opportuni-ties, however a large number of open data datasets are published in the format that cannot be linked together. Therefore, the author put great emphasis into his work on Linked Data. Emphasis is not placed only on the emergence, current status and future development, but also on the technical aspect. First, readers will be familiar with theoretical concepts, principles of Linked Open Data, expansion of open government data in the Czech Republic and abroad. In the next chapter, the author aimed at the data formats RDF, SPARQL language, etc. In the last section, the author introduce to readers the tools to work with Linked Open Data and design sample application using the Linked Open Data. The benefit of the whole work is a comprehensive view of the Linked Open Data both from a theoretical and from a practical part. The main goal is to provide to readers quality introduction to the issue.

In recent years the Web has evolved from a collection of hyperlinked documents to a vast ecosystem of interconnected documents, devices, services, and agents. However, the open nature of the Web enables anyone or any thing to publish any content they choose. Therefore poor quality data can quickly propagate and an appropriate mechanism to assess the quality of such data is essential if agents are to identify reliable information for use in decision-making. Existing assessment frameworks investigate the context around data (additional information that describes the situation in which a datum was created). Such metadata can be made available by publishing information to the Web of Linked Data. However, there are situations in which examining context alone is not sufficient - such as when one must identify the agent responsible for data creation, or transformational processes applied to data. In these situations, examining data provenance is critical to identifying quality issues. Moreover, there will be situations in which an agent is unable to perform a quality assessment of their own. For example, if the original contextual metadata is no longer available. Here, it may be possible for agents to explore provenance of previous quality assessments and make decisions about quality result re-use. This thesis explores issues around quality assessment and provenance in the Web of Linked Data. It contributes a formal model of quality assessment designed to align with emerging standards for provenance on the Web. This model is then realised as an OWL ontology, which can be used as part of a software framework to perform data quality assessment. Through a number of real-world examples, spanning environmental sensing, invasive species monitoring, and passenger information domains, the thesis establishes the importance of examining provenance as part of quality assessment. Moreover, it demonstrates that by examining quality assessment provenance agents can make re-use decisions about existing quality assessment results. Included in these implementations are sets of example quality metrics that demonstrate how these can be encoded using the SPARQL Inferencing Notation (SPIN).

The goal of this master thesis is to create a "manual" to Linked Data technology. The first part of this thesis describes the Semantic Web and its relationship to Linked Data. Then follows a detailed explanation of Linked Data and so called "Linked Data principles" including involved technologies and tools. The second part of the thesis contains practical experiences with creation and using Linked Data. Firstly is described obtaining data on public procurement by web crawler developed for these purposes, followed by a description of transformation obtained (relational) data into Linked Data and their interlinking with external Linked Data sources. One part of this thesis is also an application consuming created Linked Data. This is compared with the traditional approach when the application consumes data from a relational database. This comparison is supplemented by a benchmark. Finally is presented a manual for the beginning developer which summarizes our experiences. The list of problems which are necessary to solve (from our point of view) for further development of Linked Data is also included.

The European General Data Protection Regulation (GDPR) brings new challenges for companies, who must demonstrate that their systems and business processes comply with usage constraints specified by data subjects. However, due to the lack of standards, tools, and best practices, many organizations struggle to adapt their infrastructure and processes to ensure and demonstrate that all data processing is in compliance with users' given consent. The SPECIAL EU H2020 project has developed vocabularies that can formally describe data subjects' given consent as well as methods that use this description to automatically determine whether processing of the data according to a given policy is compliant with the given consent. Whereas this makes it possible to determine whether processing was compliant or not, integration of the approach into existing line of business applications and ex-ante compliance checking remains an open challenge. In this short paper, we demonstrate how the SPECIAL consent and compliance framework can be integrated into Linked Widgets, a mashup platform, in order to support privacy-aware ad-hoc integration of personal data. The resulting environment makes it possible to create data integration and processing workflows out of components that inherently respect usage policies of the data that is being processed and are able to demonstrate compliance. We provide an overview of the necessary meta data and orchestration towards a privacy-aware linked data mashup platform that automatically respects subjects' given consents. The evaluation results show the potential of our approach for ex-ante usage policy compliance checking within the Linked Widgets Platforms and beyond.

The aim of this thesis is to identify key requirements for exploring Linked Data and design and implement a web application which serves as a Linked Data browser, including search and customization features. In comparison to existing approaches it will enable users to provide templates which define a visual style for presentation of particular types of Linked Data resources. Alternatively, the application can provide other means of altering the presentation of data or the appearance of the application. Powered by TCPDF (www.tcpdf.org)

The thesis describes several means of processing statistical data in the ambience of Linked Data and is in particular focused on the utilization of Data Cube Vocabulary metaformat. Its content offers a description of tools related to analysis and visualization of RDF data not only from the statistical view. An indivisible part of this work is the depiction of the Payola tool on whose development is the author still working on. The outcome of this thesis is mainly proposal and consequential implementation of the system that enables a conversion of RDF data in compliance with the DCV vocabularies. The designed system was implemented and integrated to the Payola application. Several other extensions of the system were also implemented by the author. Within the scope of the implementation process there are mentioned also limitations arising from the integration with Payola. In the conclusion the writer describes a few experiments where some of the chosen datasets were applied to the implemented system. Powered by TCPDF (www.tcpdf.org)

In this deliberately provocative position paper, we claim that ten years into Linked Data there are still (too?) many unresolved challenges towards arriving at a truly machine-readable and decentralized Web of data. We take a deeper look at the biomedical domain - currently, one of the most promising "adopters" of Linked Data - if we believe the ever-present "LOD cloud" diagram. Herein, we try to highlight and exemplify key technical and non-technical challenges to the success of LOD, and we outline potential solution strategies. We hope that this paper will serve as a discussion basis for a fresh start towards more actionable, truly decentralized Linked Data, and as a call to the community to join forces. / Series: Working Papers on Information Systems, Information Business and Operations

We claim that ten years into Linked Data there are still many unresolved challenges towards arriving at a truly machine-readable and decentralized Web of data. With a focus on the the biomedical domain, currently, one of the most promising adopters of Linked Data, we highlight and exemplify key technical and non-technical challenges to the success of Linked Data, and we outline potential solution strategies.