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Event Processing and Stream Reasoning with ETALIS

Author: Darko Aničić

Publisher: Sudwestdeutscher Verlag Fur Hochschulschriften AG

Published: 2012

Total Pages: 248

ISBN-13: 9783838131733

We face today a paradigm shift toward the real time information processing, and Event Processing (EP) has therefore spawned significant attention in science and technology. Due to omnipresence of events, EP is becoming a central aspect of new distributed systems such as cloud computing and smart grid systems, mobile and sensor-based systems, as well as of a number of application areas including financial services, business intelligence, social and collaborative networking, click stream analysis and others. However in many applications to process only events is insufficient. Detection of complex situations very often involves evaluation of background knowledge too. This knowledge captures the domain of interest (context). This book presents the ETALIS Language for Events (ELE), which is a declarative rule-based language for processing events in the context of background (domain) knowledge. The book explores how stream reasoning capabilities together with EP capabilities of ELE have the potential to provide powerful real time intelligence. Finally, to demonstrate usefulness of ETALIS approach, the book presents a few scenarios with an existing open source implementation.

Web-oriented Event Processing

Author: Stuehmer, Roland

Publisher: KIT Scientific Publishing

Published: 2015-01-13

Total Pages: 186

ISBN-13: 3731502658

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How can the Web be made situation-aware? Event processing is a suitable technology for gaining the necessary real-time results. The Web, however, has many users and many application domains. Thus, we developed multi-schema friendly data models allowing the re-use and mix from diverse users and application domains. Furthermore, our methods describe protocols to exchange events on the Web, algorithms to execute the language and to calculate access rights.

Robust Stream Reasoning Under Uncertainty

Author: Daniel de Leng

Publisher: Linköping University Electronic Press

Published: 2019-11-08

Total Pages: 234

ISBN-13: 9176850137

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Vast amounts of data are continually being generated by a wide variety of data producers. This data ranges from quantitative sensor observations produced by robot systems to complex unstructured human-generated texts on social media. With data being so abundant, the ability to make sense of these streams of data through reasoning is of great importance. Reasoning over streams is particularly relevant for autonomous robotic systems that operate in physical environments. They commonly observe this environment through incremental observations, gradually refining information about their surroundings. This makes robust management of streaming data and their refinement an important problem. Many contemporary approaches to stream reasoning focus on the issue of querying data streams in order to generate higher-level information by relying on well-known database approaches. Other approaches apply logic-based reasoning techniques, which rarely consider the provenance of their symbolic interpretations. In this work, we integrate techniques for logic-based stream reasoning with the adaptive generation of the state streams needed to do the reasoning over. This combination deals with both the challenge of reasoning over uncertain streaming data and the problem of robustly managing streaming data and their refinement. The main contributions of this work are (1) a logic-based temporal reasoning technique based on path checking under uncertainty that combines temporal reasoning with qualitative spatial reasoning; (2) an adaptive reconfiguration procedure for generating and maintaining a data stream required to perform spatio-temporal stream reasoning over; and (3) integration of these two techniques into a stream reasoning framework. The proposed spatio-temporal stream reasoning technique is able to reason with intertemporal spatial relations by leveraging landmarks. Adaptive state stream generation allows the framework to adapt to situations in which the set of available streaming resources changes. Management of streaming resources is formalised in the DyKnow model, which introduces a configuration life-cycle to adaptively generate state streams. The DyKnow-ROS stream reasoning framework is a concrete realisation of this model that extends the Robot Operating System (ROS). DyKnow-ROS has been deployed on the SoftBank Robotics NAO platform to demonstrate the system's capabilities in a case study on run-time adaptive reconfiguration. The results show that the proposed system - by combining reasoning over and reasoning about streams - can robustly perform stream reasoning, even when the availability of streaming resources changes.

Linked Data Management

Author: Andreas Harth

Publisher: CRC Press

Published: 2016-04-19

Total Pages: 566

ISBN-13: 1466582413

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Linked Data Management presents techniques for querying and managing Linked Data that is available on today's Web. The book shows how the abundance of Linked Data can serve as fertile ground for research and commercial applications.The text focuses on aspects of managing large-scale collections of Linked Data. It offers a detailed introduction to L

Towards Semantically Enabled Complex Event Processing

Author: Robin Keskisärkkä

Publisher: Linköping University Electronic Press

Published: 2017-10-30

Total Pages: 149

ISBN-13: 9176854795

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The Semantic Web provides a framework for semantically annotating data on the web, and the Resource Description Framework (RDF) supports the integration of structured data represented in heterogeneous formats. Traditionally, the Semantic Web has focused primarily on more or less static data, but information on the web today is becoming increasingly dynamic. RDF Stream Processing (RSP) systems address this issue by adding support for streaming data and continuous query processing. To some extent, RSP systems can be used to perform complex event processing (CEP), where meaningful high-level events are generated based on low-level events from multiple sources; however, there are several challenges with respect to using RSP in this context. Event models designed to represent static event information lack several features required for CEP, and are typically not well suited for stream reasoning. The dynamic nature of streaming data also greatly complicates the development and validation of RSP queries. Therefore, reusing queries that have been prepared ahead of time is important to be able to support real-time decision-making. Additionally, there are limitations in existing RSP implementations in terms of both scalability and expressiveness, where some features required in CEP are not supported by any of the current systems. The goal of this thesis work has been to address some of these challenges and the main contributions of the thesis are: (1) an event model ontology targeted at supporting CEP; (2) a model for representing parameterized RSP queries as reusable templates; and (3) an architecture that allows RSP systems to be integrated for use in CEP. The proposed event model tackles issues specifically related to event modeling in CEP that have not been sufficiently covered by other event models, includes support for event encapsulation and event payloads, and can easily be extended to fit specific use-cases. The model for representing RSP query templates was designed as an extension to SPIN, a vocabulary that supports modeling of SPARQL queries as RDF. The extended model supports the current version of the RSP Query Language (RSP-QL) developed by the RDF Stream Processing Community Group, along with some of the most popular RSP query languages. Finally, the proposed architecture views RSP queries as individual event processing agents in a more general CEP framework. Additional event processing components can be integrated to provide support for operations that are not supported in RSP, or to provide more efficient processing for specific tasks. We demonstrate the architecture in implementations for scenarios related to traffic-incident monitoring, criminal-activity monitoring, and electronic healthcare monitoring.

Reasoning Web. Web Logic Rules

Author: Wolfgang Faber

Publisher: Springer

Published: 2015-07-17

Total Pages: 342

ISBN-13: 3319217682

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This volume contains the lecture notes of the 11th Reasoning Web Summer School 2015, held in Berlin, Germany, in July/August 2015. In 2015, the theme of the school was Web Logic Rules. This Summer School is devoted to this perspective, and provides insight into the semantic Web, linked data, ontologies, rules, and logic.

Web Reasoning and Rule Systems

Author: Wolfgang Faber

Publisher: Springer

Published: 2013-07-15

Total Pages: 284

ISBN-13: 3642396666

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This book constitutes the refereed proceedings of the 7th International Conference on Web Reasoning and Rule Systems, RR 2013, held in Manheim, Germany in July 2013. The 19 revised research papers and 4 technical communications presented together with 2 invited talks and 1 tutorial talk were carefully reviewed and selected from 34 submissions. The scope of conference is decision making, planning, and intelligent agents, reasoning, machine learning, knowledge extraction and IR technologies, large-scale data management and reasoning on the web of data, data integration, dataspaces and ontology-based data access, non-standard reasoning, algorithms for distributed, parallelized, and scalable reasoning, and system descriptions and experimentation.

The Semantic Web: Trends and Challenges

Author: Valentina Presutti

Publisher: Springer

Published: 2014-05-09

Total Pages: 926

ISBN-13: 3319074431

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This book constitutes the refereed proceedings of the 11th Extended Semantic Web Conference, ESWC 2014, held in Anissaras, Crete, Greece France, in May 2014. The 50 revised full papers presented together with three invited talks were carefully reviewed and selected from 204 submissions. They are organized in topical sections on mobile, sensor and semantic streams; services, processes and cloud computing; social web and web science; data management; natural language processing; reasoning; machine learning, linked open data; cognition and semantic web; vocabularies, schemas, ontologies. The book also includes 11 papers presented at the PhD Symposium.

Business Process Management Workshops

Author: Marcello La Rosa

Publisher: Springer

Published: 2013-01-26

Total Pages: 837

ISBN-13: 3642362850

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This book constitutes the refereed proceedings of 12 international workshops held in Tallinn, Estonia, in conjunction with the 10th International Conference on Business Process Management, BPM 2012, in September 2012. The 12 workshops comprised Adaptive Case Management and Other Non-Workflow Approaches to BPM (ACM 2012), Business Process Design (BPD 2012), Business Process Intelligence (BPI 2012), Business Process Management and Social Software (BPMS2 2012), Data- and Artifact-Centric BPM (DAB 2012), Event-Driven Business Process Management (edBPM 2012), Empirical Research in Business Process Management (ER-BPM 2012), Process Model Collections (PMC 2012), Process-Aware Logistics Systems (PALS 2012), Reuse in Business Process Management (rBPM 2012), Security in Business Processes (SBP 2012), and Theory and Applications of Process Visualization (TAProViz 2012). The 56 revised full papers presented were carefully reviewed and selected from 141 submissions.

Reasoning in Event-Based Distributed Systems

Author: Sven Helmer

Publisher: Springer Science & Business Media

Published: 2011-06-17

Total Pages: 318

ISBN-13: 364219723X

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With the rapid expansion of the Internet over the last 20 years, event-based distributed systems are playing an increasingly important role in a broad range of application domains, including enterprise management, environmental monitoring, information dissemination, finance, pervasive systems, autonomic computing, collaborative working and learning, and geo-spatial systems. Many different architectures, languages and technologies are being used for implementing event-based distributed systems, and much of the development has been undertaken independently by different communities. However, a common factor is an ever-increasing complexity. Users and developers expect that such systems are able not only to handle large volumes of simple events but also to detect complex patterns of events that may be spatially distributed and may span significant periods of time. Intelligent and logic-based approaches provide sound foundations for addressing many of the research challenges faced and this book covers a broad range of recent advances, contributed by leading experts in the field. It presents a comprehensive view of reasoning in event-based distributed systems, bringing together reviews of the state-of-the art, new research contributions, and an extensive set of references. It will serve as a valuable resource for students, faculty and researchers as well as industry practitioners responsible for new systems development.