Dragan Gaševic - Böcker

According to the W3C Semantic Web Activity [1]: The Semantic Web provides a common framework that allows data to be shared and reused across appli- tion, enterprise, and community boundaries. This statement clearly explains that the Semantic Web is about data sharing. Currently, the Web uses hyperlinks to connect Web pages. The Semantic Web goes beyond that and focuses on data and envisions the creation of the web of data. On the Semantic Web, anyone can say anything about any resource on the Web. This is fully based on the concept of semantic - notations, where each resource on the Web can have an assigned meaning. This is done through the use of ontologies as a formal and explicit representation of domain concepts and their relationships [2]. Ontologies are formally based on description logics. This enables agents and applications to reason over the data when searching the Web, which has not previously been possible. Web 2. 0 has gradually evolved from letting the Web users play a more active role. Unlike the initial version of the Web, where the users mainly “consumed” content, users are now offered easy-to-use services for content production and publication. Mashups, blogs, wikis, feeds, interface remixes, and social networking/tagging s- tems are examples of these well-known services. The success and wide adoption of Web 2. 0 was in its reliance on social interactions as an inevitable characteristic of the use and life of the Web. In particular, Web 2.

Theory Informing and Arising from Learning Analytics delves into the dynamic intersection of learning theory and educational data analysis within the field of Learning Analytics (LA).

Defining a formal domain ontology is generally considered a useful, not to say necessary step in almost every software project. This is because software deals with ideas rather than with self-evident physical artefacts. However, this development step is hardly ever done, as ontologies rely on well-defined and semantically powerful AI concepts such as description logics or rule-based systems, and most software engineers are largely unfamiliar with these. Gaševic and his co-authors try to fill this gap by detailing how to use model-driven engineering for ontology development on the Semantic Web. Part I of their book describes existing technologies, tools, and standards like XML, RDF, OWL, MDA, and UML. Part II presents the first detailed description of OMG's new ODM (Ontology Definition Metamodel) initiative, a specification which is expected to be in the form of an OMG language like UML. Finally, Part III is dedicated to applications and practical aspects of developing ontologies using MDA-based languages. For this second edition, the descriptions of the related standards (like MOF, ODM, OCL, and OWL) have been revised and updated; new chapters introducing the basic principles of model-driven engineering, recent research results on metamodeling Semantic Web rule languages, an introduction to the Atlas Transformation Language (ATL) and its tool support, and, last but not least, many new examples have been added.

This book constitutes the thoroughly refereed post-conference proceedings of the First International Conference on Software Language Engineering, SLE 2008, held in Toulouse, France, in September 2008. The 16 revised full papers and 1 revised short paper presented together with 1 tool demonstration paper and 2 keynote lectures were carefully reviewed and selected from 106 initial submissions. The papers are organized in topical sections on language and tool analysis and evaluation, concrete and abstract syntax, language engineering techniques, language integration and transformation, language implementation and analysis, as well as language engineering pearls.

Defining a formal domain ontology is generally considered a useful, not to say necessary step in almost every software project. This is because software deals with ideas rather than with self-evident physical artefacts. However, this development step is hardly ever done, as ontologies rely on well-defined and semantically powerful AI concepts such as description logics or rule-based systems, and most software engineers are largely unfamiliar with these. Gaševic and his co-authors try to fill this gap by detailing how to use model-driven engineering for ontology development on the Semantic Web. Part I of their book describes existing technologies, tools, and standards like XML, RDF, OWL, MDA, and UML. Part II presents the first detailed description of OMG's new ODM (Ontology Definition Metamodel) initiative, a specification which is expected to be in the form of an OMG language like UML. Finally, Part III is dedicated to applications and practical aspects of developing ontologies using MDA-based languages. For this second edition, the descriptions of the related standards (like MOF, ODM, OCL, and OWL) have been revised and updated; new chapters introducing the basic principles of model-driven engineering, recent research results on metamodeling Semantic Web rule languages, an introduction to the Atlas Transformation Language (ATL) and its tool support, and, last but not least, many new examples have been added.

We are pleased to present the proceedings of the Second International Conf- ence on Software LanguageEngineering (SLE 2009). The conference was held in Denver, Colorado (USA) during October 5-6, 2009 and was co-located with the th 12 IEEE/ACM International Conference on Model-Driven Engineering L- th guages and Systems (MODELS 2009) and the 8 ACM International Conf- ence on Generative Programming and Component Engineering (GPCE 2009). TheSLEconferenceseriesisdevotedtoawiderangeoftopicsrelatedtoarti?cial languages in software engineering. SLE is an international research forum that brings together researchers and practitioners from both industry and academia to expand the frontiers of software language engineering. SLE'sforemostmissionis to encourageand organizecommunicationbetween communities that have traditionally looked at software languagesfrom di?erent, more specialized, and yet complementary perspectives. SLE emphasizes the f- damental notion of languages, as opposed to any realization in speci?c technical spaces. In this context, the term "software language" comprises all sorts of - ti?cial languages used in software development, including general-purpose p- gramming languages, domain-speci?c languages, modeling and meta-modeling languages, data models, and ontologies. Software language engineering is the application of a systematic, disciplined, quanti?able approach to the devel- ment,use,andmaintenanceoftheselanguages. TheSLEconferenceisconcerned with all phases of the lifecycle of software languages; these include the design, implementation, documentation, testing, deployment, evolution, recovery, and retirement of languages. Of special interest are tools, techniques, methods, and formalisms that support these activities. In particular, tools are often based on, or automatically generated from, a formal description of the language.