Prof. Dr.

Hauswirth, Manfred

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  • Publication
    RDF data storage and query processing schemes
    ( 2018)
    Wylot, Marcin
    ;
    Hauswirth, Manfred
    ;
    Cudré-Mauroux, Philippe
    ;
    Sakr, Sharif
    The Resource Description Framework (RDF) represents a main ingredient and data representation format for Linked Data and the Semantic Web. It supports a generic graph-based data model and data representation format for describing things, including their relationships with other things. As the size of RDF datasets is growing fast, RDF data management systems must be able to cope with growing amounts of data. Even though physically handling RDF data using a relational table is possible, querying a giant triple table becomes very expensive because of the multiple nested joins required for answering graph queries. In addition, the heterogeneity of RDF Data poses entirely new challenges to database systems. This article provides a comprehensive study of the state of the art in handling and querying RDF data. In particular, we focus on data storage techniques, indexing strategies, and query execution mechanisms. Moreover, we provide a classification of existing systems and approaches. We also provide an overview of the various benchmarking efforts in this context and discuss some of the open problems in this domain.
  • Publication
    Physical-Cyber-Social computing: Looking back, looking forward
    ( 2015)
    Barnaghi, Payam
    ;
    Sheth, Amit
    ;
    Singh, Vivek
    ;
    Hauswirth, Manfred
    Physical-cyber-social (PCS) computing involves a holistic treatment of data, information, and knowledge from the physical, cyber, and social worlds to integrate, understand, correlate, and provide contextually relevant abstractions to humans and the applications that serve them. PCS computing extends current progress in cyber-physical, socio-technical, and cyber-social systems. Here, the guest editors consider powerful ways to exploit data available through various Internet of Things (IoT), citizen and social sensing, Web, and open data sources that are seeing explosive growth. This special issue highlights a variety of PCS applications, such as smart firefighting, intelligent infrastructure, and user guidance in an airport.
  • Publication
    Scalable distributed indexing and query processing over Linked Data
    ( 2012)
    Karnstedt, Marcel
    ;
    Sattler, Kai-Uwe
    ;
    Hauswirth, Manfred
    Linked Data is becoming the core part of modern Web applications and thus efficient access to structured information expressed in RDF gains paramount importance. A number of efficient local RDF stores exist already, while distributed indexing and distributed query processing over Linked Data with similar efficiency and data management features as known from traditional database and data integration systems are only starting to develop. Distributed approaches will necessarily co-exist with centralized schemes, as data will be owned by different stakeholders who may not want to provide their complete data sets to a central place. Additionally, central/integrated storage may be prohibited for organizational or legal reasons in certain areas. To support decentralized schemes, only a few attempts in this direction exist so far, but they are limited in terms of capabilities and the degree of distribution vs. efficiency, query expressivity, and scalability. To remedy this situation, the approach and proof-of-concept prototype presented in this paper provides a solution for these open challenges. As we argue for widely distributed systems as a possible answer to scalability issues, we first identify and discuss the main challenges and based on this analysis, we propose an approach for efficient and scalable query processing over distributed Linked Data sources, taking into account the latest advances in database technology. Our system is based on a layered architecture that makes use of the advantages of decentralized indexing and query processing approaches, which have been researched and matured over the last decade. Our approach is based on a logical algebra for queries over RDF data and a related physical query algebra to enable optimization, both on the logical and physical layers in query processing. The introduced operators and strategies for processing complex query plans make excessive use of parallelism and other optimization paradigms of distributed query processing. Our query processing framework includes a sophisticated cost model to enable cost-efficient query planning and query execution. We extensively evaluate our approach through an experimental evaluation of a real proof-of-concept deployment, which demonstrates the efficiency, applicability, and correctness of the proposed concepts.
  • Publication
    The SSN ontology of the W3C semantic sensor network incubator group
    ( 2012)
    Compton, Michael
    ;
    Barnaghi, Payam
    ;
    Bermudez, Luis
    ;
    García-Castro, Raúl
    ;
    Corcho, Oscar
    ;
    Cox, Simon
    ;
    Graybeal, John
    ;
    Hauswirth, Manfred
    ;
    Henson, Cory
    ;
    Herzog, Arthur
    ;
    Huang, Vincent
    ;
    Janowicz, Krzysztof
    ;
    Kelsey, W.D.
    ;
    Le-Phuoc, Danh
    ;
    Lefort, Laurent
    ;
    Leggieri, Myriam
    ;
    Neuhaus, Holger
    ;
    Nikolov, Andriy
    ;
    Page, Kevin
    ;
    Passant, Alexandre
    ;
    Sheth, Amit
    ;
    Taylor, Kerry
    The W3C Semantic Sensor Network Incubator group (the SSN-XG) produced an OWL 2 ontology to describe sensors and observations - the SSN ontology, available at http://purl.oclc.org/NET/ssnx/ssn. The SSN ontology can describe sensors in terms of capabilities, measurement processes, observations and deployments. This article describes the SSN ontology. It further gives an example and describes the use of the ontology in recent research projects.
  • Publication
    A middleware framework for scalable management of linked streams
    ( 2012)
    Le-Phuoc, Danh
    ;
    Nguyen Mau Quoc, Hoan
    ;
    Parreira, Josiane Xavier
    ;
    Hauswirth, Manfred
    The Web has long exceeded its original purpose of a distributed hypertext system and has become a global, data sharing and processing platform. This development is confirmed by remarkable milestones such as the Semantic Web, Web services, social networks and mashups. In parallel with these developments on the Web, the Internet of Things (IoT), i.e., sensors and actuators, has matured and has become a major scientific and economic driver. Its potential impact cannot be overestimated-for example, in logistics, cities, electricity grids and in our daily life, in the form of sensor-laden mobile phones-and rivals that of the Web itself. While the Web provides ease of use of distributed resources and a sophisticated development and deployment infrastructure, the IoT excels in bringing real-time information from the physical world into the picture. Thus a combination of these players seems to be the natural next step in the development of even more sophisticated systems of systems. While only starting, there is already a significant amount of sensor-generated, or more generally dynamic information, available on the Web. However, this information is not easy to access and process, depends on specialised gateways and requires significant knowledge on the concrete deployments, for example, resource constraints and access protocols. To remedy these problems and draw on the advantages of both sides, we try to make dynamic, online sensor data of any form as easily accessible as resources and data on the Web, by applying well-established Web principles, access and processing methods, thus shielding users and developers from the underlying complexities. In this paper we describe our Linked Stream Middleware (LSM, http://lsm.deri.ie/), which makes it easy to integrate time-dependent data with other Linked Data sources, by enriching both sensor sources and sensor data streams with semantic descriptions, and enabling complex SPARQL-like queries across both dataset types through a novel query processing engine, along with means to mashup the data and process results. Most prominently, LSM provides (1) extensible means for real-time data collection and publishing using a cloud-based infrastructure, (2) a Web interface for data annotation and visualisation, and (3) a SPARQL endpoint for querying unified Linked Stream Data and Linked Data. We describe the system architecture behind LSM, provide details of how Linked Stream Data is generated, and demonstrate the benefits and efficiency of the platform by showcasing some experimental evaluations and the system's interface.
  • Publication
    Collaborative development of trusted mashups
    ( 2011)
    Fox, Ronan
    ;
    Cooley, James
    ;
    Hauswirth, Manfred
    Purpose - The purpose of this paper is to identify the gap that currently exists between enterprise and consumer‐focused mashup tools in terms of personalized, trusted collaboration. The authors describe how Sqwelch, a semantically enabled mashup maker, addresses this gap during the design of mashups and in their execution. Design/methodology/approach - Sqwelch enables the composition of mashups based on the concept of trust explicitly specified by users through a visual interface. Taxonomies are used to enable lightweight mediation of payloads delivered through a publish/subscribe mechanism. Findings - The authors demonstrate the use of Sqwelch as a proof of concept in the remote delivery of healthcare, and how Sqwelch has been used to address areas of trust and collaboration in the delivery of telehealth services. Originality/value - Integrating trust and collaboration across the boundaries of enterprises is required where sensitive data are transferred across those boundaries in the expectation of the delivery of a service. Across these boundaries, the authors find variations in users' skills, their expectations, and their responsibilities. The prototype described here enables users to discover, compose, share and collaborate in the day‐to‐day use of systems that match personalized requirements.