Reasoning Techniques for the Web of Data

Reasoning Techniques for the Web of Data
Author: A. Hogan
Publisher: IOS Press
Total Pages: 344
Release: 2014-04-09
Genre: Computers
ISBN: 1614993831

Linked Data publishing has brought about a novel “Web of Data”: a wealth of diverse, interlinked, structured data published on the Web. These Linked Datasets are described using the Semantic Web standards and are openly available to all, produced by governments, businesses, communities and academia alike. However, the heterogeneity of such data – in terms of how resources are described and identified – poses major challenges to potential consumers. Herein, we examine use cases for pragmatic, lightweight reasoning techniques that leverage Web vocabularies (described in RDFS and OWL) to better integrate large scale, diverse, Linked Data corpora. We take a test corpus of 1.1 billion RDF statements collected from 4 million RDF Web documents and analyse the use of RDFS and OWL therein. We then detail and evaluate scalable and distributed techniques for applying rule-based materialisation to translate data between different vocabularies, and to resolve coreferent resources that talk about the same thing. We show how such techniques can be made robust in the face of noisy and often impudent Web data. We also examine a use case for incorporating a PagerRank-style algorithm to rank the trustworthiness of facts produced by reasoning, subsequently using those ranks to fix formal contradictions in the data. All of our methods are validated against our real world, large scale, open domain, Linked Data evaluation corpus.

Reasoning Web. Semantic Technologies for the Web of Data

Reasoning Web. Semantic Technologies for the Web of Data
Author: Axel Polleres
Publisher: Springer Science & Business Media
Total Pages: 544
Release: 2011-08-09
Genre: Computers
ISBN: 3642230318

The Semantic Web aims at enriching the existing Web with meta-data and processing methods so as to provide web-based systems with advanced capabilities, in particular with context awareness and decision support. The objective of this book is to provide a coherent introduction to semantic web methods and research issues with a particular emphasis on reasoning. The 7th reasoning web Summer School, held in August 2011, focused on the central topic of applications of reasoning for the emerging “Web of Data”. The 12 chapters in the present book provide excellent educational material as well as a number of references for further reading. The book not only addresses students working in the area, but also those seeking an entry point to various topics related to reasoning over Web data.

Applications and Practices in Ontology Design, Extraction, and Reasoning

Applications and Practices in Ontology Design, Extraction, and Reasoning
Author: G. Cota
Publisher: IOS Press
Total Pages: 244
Release: 2020-12-02
Genre: Computers
ISBN: 1643681435

Semantic Web technologies enable people to create data stores on the Web, build vocabularies, and write rules for handling data. They have been in use for several years now, and knowledge extraction and knowledge discovery are two key aspects investigated in a number of research fields which can potentially benefit from the application of semantic web technologies, and specifically from the development and reuse of ontologies. This book, Applications and Practices in Ontology Design, Extraction, and Reasoning, has as its main goal the provision of an overview of application fields for semantic web technologies. In particular, it investigates how state-of-the-art formal languages, models, methods, and applications of semantic web technologies reframe research questions and approaches in a number of research fields. The book also aims to showcase practical tools and background knowledge for the building and querying of ontologies. The first part of the book presents the state-of-the-art of ontology design, applications and practices in a number of communities, and in doing so it provides an overview of the latest approaches and techniques for building and reusing ontologies according to domain-dependent and independent requirements. Once the data is represented according to ontologies, it is important to be able to query and reason about them, also in the presence of uncertainty, vagueness and probabilities. The second part of the book covers some of the latest advances in the fields of ontology, semantics and reasoning, without losing sight of the book’s practical goals.

The Web of Data

The Web of Data
Author: Aidan Hogan
Publisher: Springer Nature
Total Pages: 689
Release: 2020-09-09
Genre: Computers
ISBN: 303051580X

This book’s main goals are to bring together in a concise way all the methodologies, standards and recommendations related to Data, Queries, Links, Semantics, Validation and other issues concerning machine-readable data on the Web, to describe them in detail, to provide examples of their use, and to discuss how they contribute to – and how they have been used thus far on – the “Web of Data”. As the content of the Web becomes increasingly machine readable, increasingly complex tasks can be automated, yielding more and more powerful Web applications that are capable of discovering, cross-referencing, filtering, and organizing data from numerous websites in a matter of seconds. The book is divided into nine chapters, the first of which introduces the topic by discussing the shortcomings of the current Web and illustrating the need for a Web of Data. Next, “Web of Data” provides an overview of the fundamental concepts involved, and discusses some current use-cases on the Web where such concepts are already being employed. “Resource Description Framework (RDF)” describes the graph-structured data model proposed by the Semantic Web community as a common data model for the Web. The chapter on “RDF Schema (RDFS) and Semantics” presents a lightweight ontology language used to define an initial semantics for terms used in RDF graphs. In turn, the chapter “Web Ontology Language (OWL)” elaborates on a more expressive ontology language built upon RDFS that offers much more powerful ontological features. In “SPARQL Query Language” a language for querying and updating RDF graphs is described, with examples of the features it supports, supplemented by a detailed definition of its semantics. “Shape Constraints and Expressions (SHACL/ShEx)” introduces two languages for describing the expected structure of – and expressing constraints on – RDF graphs for the purposes of validation. “Linked Data” discusses the principles and best practices proposed by the Linked Data community for publishing interlinked (RDF) data on the Web, and how these techniques have been adopted. The final chapter highlights open problems and rounds out the coverage with a more general discussion on the future of the Web of Data. The book is intended for students, researchers and advanced practitioners interested in learning more about the Web of Data, and about closely related topics such as the Semantic Web, Knowledge Graphs, Linked Data, Graph Databases, Ontologies, etc. Offering a range of accessible examples and exercises, it can be used as a textbook for students and other newcomers to the field. It can also serve as a reference handbook for researchers and developers, as it offers up-to-date details on key standards (RDF, RDFS, OWL, SPARQL, SHACL, ShEx, RDB2RDF, LDP), along with formal definitions and references to further literature. The associated website webofdatabook.org offers a wealth of complementary material, including solutions to the exercises, slides for classes, raw data for examples, and a section for comments and questions.

Reasoning Web. Declarative Artificial Intelligence

Reasoning Web. Declarative Artificial Intelligence
Author: Marco Manna
Publisher: Springer Nature
Total Pages: 255
Release: 2020-10-17
Genre: Computers
ISBN: 303060067X

This volume contains 8 lecture notes of the 16th Reasoning Web Summer School (RW 2020), held in Oslo, Norway, in June 2020. The Reasoning Web series of annual summer schools has become the prime educational event in the field of reasoning techniques on the Web, attracting both young and established researchers. The broad theme of this year's summer school was “Declarative Artificial Intelligence” and it covered various aspects of ontological reasoning and related issues that are of particular interest to Semantic Web and Linked Data applications. The following eight lectures have been presented during the school: Introduction to Probabilistic Ontologies, On the Complexity of Learning Description Logic Ontologies, Explanation via Machine Arguing, Stream Reasoning: From Theory to Practice, First-Order Rewritability of Temporal Ontology-Mediated Queries, An Introduction to Answer Set Programming and Some of Its Extensions, Declarative Data Analysis using Limit Datalog Programs, and Knowledge Graphs: Research Directions.

Reasoning with Data

Reasoning with Data
Author: Jeffrey M. Stanton
Publisher: Guilford Publications
Total Pages: 336
Release: 2017-05-22
Genre: Social Science
ISBN: 1462530265

Engaging and accessible, this book teaches readers how to use inferential statistical thinking to check their assumptions, assess evidence about their beliefs, and avoid overinterpreting results that may look more promising than they really are. It provides step-by-step guidance for using both classical (frequentist) and Bayesian approaches to inference. Statistical techniques covered side by side from both frequentist and Bayesian approaches include hypothesis testing, replication, analysis of variance, calculation of effect sizes, regression, time series analysis, and more. Students also get a complete introduction to the open-source R programming language and its key packages. Throughout the text, simple commands in R demonstrate essential data analysis skills using real-data examples. The companion website provides annotated R code for the book's examples, in-class exercises, supplemental reading lists, and links to online videos, interactive materials, and other resources. ÿ Pedagogical Features *Playful, conversational style and gradual approach; suitable for students without strong math backgrounds. *End-of-chapter exercises based on real data supplied in the free R package. *Technical explanation and equation/output boxes. *Appendices on how to install R and work with the sample datasets.ÿ

Web Reasoning and Rule Systems

Web Reasoning and Rule Systems
Author: Balder ten Cate
Publisher: Springer
Total Pages: 147
Release: 2015-07-21
Genre: Computers
ISBN: 3319220020

This book constitutes the refereed proceedings of the 9th International Conference on Web Reasoning and Rule Systems, RR 2015, held in Berlin, Germany, in August 2015. The 5 full papers, 4 technical communications presented together with 4 invited talks were carefully reviewed and selected from 16 submissions. The scale and the heterogenous nature of web data poses many challenges, and turns basic tasks such as query answering and data transformations into complex reasoning problems. Rule-based systems have found many applications in this area. The RR conference welcomes original research from all areas of Web Reasoning and Rule Systems. Topics of particular interest are: answer set programming, complex events, datalog, description logics, event-condition-action rules, information extraction, and logic programming.

Reasoning Web. Reasoning and the Web in the Big Data Era

Reasoning Web. Reasoning and the Web in the Big Data Era
Author: Manolis Koubarakis
Publisher: Springer
Total Pages: 397
Release: 2014-09-03
Genre: Computers
ISBN: 3319105876

This volume contains the lecture notes of the 10th Reasoning Web Summer School 2014, held in Athens, Greece, in September 2014. In 2014, the lecture program of the Reasoning Web introduces students to recent advances in big data aspects of semantic web and linked data, and the fundamentals of reasoning techniques that can be used to tackle big data applications.

Reasoning Web. Semantic Technologies for Intelligent Data Access

Reasoning Web. Semantic Technologies for Intelligent Data Access
Author: Sebastian Rudolph
Publisher: Springer
Total Pages: 293
Release: 2013-07-22
Genre: Computers
ISBN: 3642397840

This volume contains the lecture notes of the 9th Reasoning Web Summer School 2013, held in Mannheim, Germany, in July/August 2013. The 2013 summer school program covered diverse aspects of Web reasoning, ranging from scalable lightweight formalisms such as RDF to more expressive ontology languages based on description logics. It also featured foundational reasoning techniques used in answer set programming and ontology-based data access as well as emerging topics like geo-spatial information handling and reasoning-driven information extraction and integration.

Reasoning Techniques for the Web of Data

Reasoning Techniques for the Web of Data
Author: Aidan Hogan
Publisher:
Total Pages: 344
Release: 2014-01-01
Genre: Artificial intelligence
ISBN: 9781306902977

Linked Data publishing has brought about a novel Web of Data: a wealth of diverse, interlinked, structured data published on the Web. These Linked Datasets are described using the Semantic Web standards and are openly available to all, produced by governments, businesses, communities and academia alike. However, the heterogeneity of such data in terms of how resources are described and identified poses major challenges to potential consumers. Herein, we examine use cases for pragmatic, lightweight reasoning techniques that leverage Web vocabularies (described in RDFS and OWL) to better integrate large scale, diverse, Linked Data corpora. We take a test corpus of 1.1 billion RDF statements collected from 4 million RDF Web documents and analyse the use of RDFS and OWL therein. We then detail and evaluate scalable and distributed techniques for applying rule-based materialisation to translate data between different vocabularies, and to resolve coreferent resources that talk about the same thing. We show how such techniques can be made robust in the face of noisy and often impudent Web data. We also examine a use case for incorporating a PagerRank-style algorithm to rank the trustworthiness of facts produced by reasoning, subsequently using those ranks to fix formal contradictions in the data. All of our methods are validated against our real world, large scale, open domain, Linked Data evaluation corpus."