Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
23
result(s) for
"Harth, Andreas"
Sort by:
Linked data management
\"With the growing popularity of the Semantic Web, more and more semantic data and data sources become available and accessible for everyone. By establishing semantic links between the data, answers to (complex) queries can be evaluated based on the data on multiple providers instead of just one. This book motivates, introduces, and details techniques for processing heterogeneous structured data on the Web by providing a comprehensive overview for database researchers and practitioners about this new publishing paradigm on the web, and show how the abundance of data published as Linked Data can serve as a fertile ground for database research and experimentation\"-- Provided by publisher.
Book
Linked Data Management
This book presents techniques for querying and managing Linked Data that is available on today's Web. It shows how the abundance of Linked Data can serve as fertile ground for research and commercial applications. While the book covers query processing extensively, the Linked Data abstraction furnishes more than a mechanism for collecting, integrating, and querying data from the open Web-the Linked Data technology stack also allows for controlled, sophisticated applications deployed in an enterprise environment.
eBook
Listeria Meningitis Complicating Alemtuzumab Treatment in Multiple Sclerosis—Report of Two Cases
Alemtuzumab, a humanized monoclonal antibody targeting the surface molecule CD52, leads to a rapid depletion of immune cells in the innate and adaptive immune system. In phase 2 and 3 trials in multiple sclerosis (MS), infections have been reported more frequently in alemtuzumab than in interferon beta treated patients. Here we report two patients treated with alemtuzumab for MS developing Listeria meningitis few days after the first infusion cycle. Both patients recovered completely after prompt diagnosis and adequate treatment. Physicians and patients should be aware of this serious, but treatable complication.
Journal Article
Foundational Components for B2B Data Sharing Using the Solid Protocol
This article introduces foundational components for decentralized B2B data sharing based on the solid protocol, emphasizing data sovereignty, security, and interoperability. These components are: (1) Authorization app (AuthApp) – facilitating granular control and compliance in access granting and revocation processes; (2) rights delegation proxy (RDP) – supporting controlled delegation of rights, enabling natural persons to act on behalf of organizations while ensuring privacy and traceability; (3) data provisioning proxy (DPP) – allowing seamless and secure data provisioning across organizations while masking the identity of upstream data sources to protect business interests. The components enable the creation of end-to-end, standards-based, flexible data value chains. We validate their applicability through a real-world financial services use case involving loan processing, which illustrates data sharing and protection challenges in B2B ecosystems.
Journal Article
Scalable Authoritative OWL Reasoning for the Web
In this article the authors discuss the challenges of performing reasoning on large scale RDF datasets from the Web. Using ter-Horst’s pD* fragment of OWL as a base, the authors compose a rule-based framework for application to web data: they argue their decisions using observations of undesirable examples taken directly from the Web. The authors further temper their OWL fragment through consideration of “authoritative sources” which counter-acts an observed behaviour which they term “ontology hijacking”: new ontologies published on the Web re-defining the semantics of existing entities resident in other ontologies. They then present their system for performing rule-based forward-chaining reasoning which they call SAOR: Scalable Authoritative OWL Reasoner. Based upon observed characteristics of web data and reasoning in general, they design their system to scale: the system is based upon a separation of terminological data from assertional data and comprises of a lightweight in-memory index, on-disk sorts and file-scans. The authors evaluate their methods on a dataset in the order of a hundred million statements collected from real-world Web sources and present scale-up experiments on a dataset in the order of a billion statements collected from the Web.
Journal Article
Volumetry as a Criterion for Suboccipital Craniectomy after Cerebellar Infarction
Objective: The aim of this study was to investigate the use of image-guided volumetry in cerebellar infarction during the decision-making process for surgery. Particular emphasis was placed on the ratio of the infarction volume to the cerebellar volume or cranial posterior fossa volume. Methods: A retrospective, multicenter, multidisciplinary study design was selected. Statistical methods such as regression analysis and ROC analysis included the volumetric data of the infarction, the posterior fossa and the cerebellum itself as new factors. Results: Thirty-eight patients (mean age 75 (SD: 13.93) years, 16 (42%) female patients) were included. The mean infarction volume was 37.79 (SD: 25.24) cm3. Patients treated surgically had a 2.05-fold larger infarction than those managed without surgery (p ≤ 0.001). Medical and surgical treatment revealed a significant difference in the ratio of the cranial posterior fossa volume to the infarction volume (medical 12.05, SD:9.09; surgical 5.14, SD: 5,65; p ≤ 0.001) and the ratio of the cerebellar volume to the infarction volume (medical 8.55, SD: 5.97; surgical 3.82, SD: 3.39; p ≤ 0.001). Subsequent multivariate regression analysis for surgical therapy showed significant results only for the posterior fossa volume to infarction volume ratio ≤/> 4:1 (OR: 1.162, CI: 1.007–1.341, p = 0.04). Younger (≤60 years) patients also had a significantly better outcome at discharge (p ≤ 0.017). A cut-off value for the infarction volume of 31.35 cm3 (sensitivity = 0.875, specificity = 0.2) was determined for the necessity of surgery. Conclusions: Volumetric data on the infarction, the posterior fossa and the cerebellum itself could be meaningful in decision-making towards surgery.
Journal Article
Scalable Authoritative OWL Reasoning for the Web
In this article the authors discuss the challenges of performing reasoning on large scale RDF datasets from the Web. Using ter-Horst's pD* fragment of OWL as a base, the authors compose a rule-based framework for application to web data: they argue their decisions using observations of undesirable examples taken directly from the Web. The authors further temper their OWL fragment through consideration of \"authoritative sources\" which counter-acts an observed behaviour which they term \"ontology hijacking\": new ontologies published on the Web re-defining the semantics of existing entities resident in other ontologies. They then present their system for performing rule-based forward-chaining reasoning which they call SAOR: Scalable Authoritative OWL Reasoner. Based upon observed characteristics of web data and reasoning in general, they design their system to scale: the system is based upon a separation of terminological data from assertional data and comprises of a lightweight in-memory index, on-disk sorts and file-scans. The authors evaluate their methods on a dataset in the order of a hundred million statements collected from real-world Web sources and present scale-up experiments on a dataset in the order of a billion statements collected from the Web.
Journal Article
Specifying, Monitoring, and Executing Workflows in Linked Data Environments
We present an ontology for representing workflows over components with Read-Write Linked Data interfaces and give an operational semantics to the ontology via a rule language. Workflow languages have been successfully applied for modelling behaviour in enterprise information systems, in which the data is often managed in a relational database. Linked Data interfaces have been widely deployed on the web to support data integration in very diverse domains, increasingly also in scenarios involving the Internet of Things, in which application behaviour is often specified using imperative programming languages. With our work we aim to combine workflow languages, which allow for the high-level specification of application behaviour by non-expert users, with Linked Data, which allows for decentralised data publication and integrated data access. We show that our ontology is expressive enough to cover the basic workflow patterns and demonstrate the applicability of our approach with a prototype system that observes pilots carrying out tasks in a mixed-reality aircraft cockpit. On a synthetic benchmark from the building automation domain, the runtime scales linearly with the size of the number of Internet of Things devices.
Paper
Stream Containers for Resource-oriented RDF Stream Processing
We introduce Stream Containers inspired by the Linked Data Platform as an alternative way to process RDF streams. A Stream Container represents a single RDF data stream that can be accessed in a resource-oriented way which allows for better interoperability with the existing Semantic Web infrastructure. Stream Containers are managed by webservers that are responsible for implementing the S2R operator, i.e. calculating the window for their clients. The clients on the other hand can use a standard SPARQL processor in combination with HTTP requests to do RDF processing. Query results can be converted back to an RDF stream (R2S operator) by posting the data to a Stream Container. Our approach of resource-oriented RDF stream processing can lead to a better distribution of load and thus to better worldwide scalability. We give a general overview of the proposed architecture as well as the formal semantics of the overall system.
Paper
BOLD: A Benchmark for Linked Data User Agents and a Simulation Framework for Dynamic Linked Data Environments
The paper presents the BOLD (Buildings on Linked Data) benchmark for Linked Data agents, next to the framework to simulate dynamic Linked Data environments, using which we built BOLD. The BOLD benchmark instantiates the BOLD framework by providing a read-write Linked Data interface to a smart building with simulated time, occupancy movement and sensors and actuators around lighting. On the Linked Data representation of this environment, agents carry out several specified tasks, such as controlling illumination. The simulation environment provides means to check for the correct execution of the tasks and to measure the performance of agents. We conduct measurements on Linked Data agents based on condition-action rules.
Paper