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This book is about a significant step forward in software
development. It brings state-of-the-art ontology reasoning into
mainstream software development and its languages. Ontology Driven
Software Development is the essential, comprehensive resource on
enabling technologies, consistency checking and process guidance
for ontology-driven software development (ODSD). It demonstrates
how to apply ontology reasoning in the lifecycle of software
development, using current and emerging standards and technologies.
You will learn new methodologies and infrastructures, additionally
illustrated using detailed industrial case studies. The book will
help you: Learn how ontology reasoning allows validations of
structure models and key tasks in behavior models. Understand how
to develop ODSD guidance engines for important software development
activities, such as requirement engineering, domain modeling and
process refinement. Become familiar with semantic standards, such
as the Web Ontology Language (OWL) and the SPARQL query language.
Make use of ontology reasoning, querying and justification
techniques to integrate software models and to offer guidance and
traceability supports. This book is helpful for undergraduate
students and professionals who are interested in studying how
ontologies and related semantic reasoning can be applied to the
software development process. In addition, itwill also be useful
for postgraduate students, professionals and researchers who are
going to embark on their research in areas related to ontology or
software engineering.
This book is about a significant step forward in software
development. It brings state-of-the-art ontology reasoning into
mainstream software development and its languages. Ontology Driven
Software Development is the essential, comprehensive resource on
enabling technologies, consistency checking and process guidance
for ontology-driven software development (ODSD). It demonstrates
how to apply ontology reasoning in the lifecycle of software
development, using current and emerging standards and technologies.
You will learn new methodologies and infrastructures, additionally
illustrated using detailed industrial case studies. The book will
help you: Learn how ontology reasoning allows validations of
structure models and key tasks in behavior models. Understand how
to develop ODSD guidance engines for important software development
activities, such as requirement engineering, domain modeling and
process refinement. Become familiar with semantic standards, such
as the Web Ontology Language (OWL) and the SPARQL query language.
Make use of ontology reasoning, querying and justification
techniques to integrate software models and to offer guidance and
traceability supports. This book is helpful for undergraduate
students and professionals who are interested in studying how
ontologies and related semantic reasoning can be applied to the
software development process. In addition, itwill also be useful
for postgraduate students, professionals and researchers who are
going to embark on their research in areas related to ontology or
software engineering.
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Reasoning Web: Logical Foundation of Knowledge Graph Construction and Query Answering - 12th International Summer School 2016, Aberdeen, UK, September 5-9, 2016, Tutorial Lectures (Paperback, 1st ed. 2017)
Jeff Z. Pan, Diego Calvanese, Thomas Eiter, Ian Horrocks, Michael Kifer, …
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R2,610
Discovery Miles 26 100
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Ships in 10 - 15 working days
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This volume contains some lecture notes of the 12th Reasoning Web
Summer School (RW 2016), held in Aberdeen, UK, in September 2016.
In 2016, the theme of the school was "Logical Foundation of
Knowledge Graph Construction and Query Answering". The notion of
knowledge graph has become popular since Google started to use it
to improve its search engine in 2012. Inspired by the success of
Google, knowledge graphs are gaining momentum in the World Wide Web
arena. Recent years have witnessed increasing industrial take-ups
by other Internet giants, including Facebook's Open Graph and
Microsoft's Satori. The aim of the lecture note is to provide a
logical foundation for constructing and querying knowledge graphs.
Our journey starts from the introduction of Knowledge Graph as well
as its history, and the construction of knowledge graphs by
considering both explicit and implicit author intentions. The book
will then cover various topics, including how to revise and reuse
ontologies (schema of knowledge graphs) in a safe way, how to
combine navigational queries with basic pattern matching queries
for knowledge graph, how to setup a environment to do experiments
on knowledge graphs, how to deal with inconsistencies and fuzziness
in ontologies and knowledge graphs, and how to combine machine
learning and machine reasoning for knowledge graphs.
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