Survey over Existing Query and Transformation Languages

A widely acknowledged obstacle for realizing the vision of the Semantic Web is the inability of many current Semantic Web approaches to cope with data available in such diverging representation formalisms as XML, RDF, or Topic Maps. A common query language is the first step to allow transparent access to data in any of these formats. To further the understanding of the requirements and approaches proposed for query languages in the conventional as well as the Semantic Web, this report surveys a large number of query languages for accessing XML, RDF, or Topic Maps. This is the first systematic survey to consider query languages from all these areas. From the detailed survey of these query languages, a common classification scheme is derived that is useful for understanding and differentiating languages within and among all three areas

Will this work for Susan? Challenges for delivering usable and useful generic linked data browsers

While we witness an explosion of exploration tools for simple datasets on Web 2.0 designed for use by ordinary citizens, the goal of a usable interface for supporting navigation and sense-making over arbitrary linked data has remained elusive. The purpose of this paper is to analyse why - what makes exploring linked data so hard? Through a user-centered use case scenario, we work through requirements for sense making with data to extract functional requirements and to compare these against our tools to see what challenges emerge to deliver a useful, usable knowledge building experience with linked data. We present presentation layer and heterogeneous data integration challenges and offer practical considerations for moving forward to effective linked data sensemaking tools

The Model of Reading : Modelling principles, Definitions, Schema, Alignments

READ-IT Model of Reading -V2Executive Summary This technical report introduces the data model developed to address the systematic collection and use of reading experiences in READ-IT project. The model of reading presented in this document is meant to inform the development of the READ-IT database and tools. This document describes the methodological approach and design principles adopted in the development of the model of reading. Furthermore, this technical report describes the content of the first version of the data model of the reading experience, including a preliminary analysis of the alignments between READ-IT model of reading with CIDOC-CRM, FRBRoo, FoaF and Schema.org

The Model of Reading: Modelling principles, Definitions, Schema, Alignments

This technical report introduces the data model developed to address the systematic collection and use of reading experiences in READ-IT project. The model of reading presented in this document is meant to inform the development of the READ-IT database and tools. This document describes the methodological approach and design principles adopted in the development of the model of reading. Furthermore, this technical report describes the content of the first version of the data model of the reading experience, including a preliminary analysis of the alignments between READ-IT model of reading with CIDOC-CRM, FRBRoo, FoaF and Schema.org

Upper Tag Ontology (UTO) For Integrating Social Tagging Data

Data integration and mediation have become central concerns of information technology over the past few decades. With the advent of the Web and the rapid increases in the amount of data and the number of Web documents and users, researchers have focused on enhancing the interoperability of data through the development of metadata schemes. Other researchers have looked to the wealth of metadata generated by bookmarking sites on the Social Web. While several existing ontologies have capitalized on the semantics of metadata created by tagging activities, the Upper Tag Ontology (UTO) emphasizes the structure of tagging activities to facilitate modeling of tagging data and the integration of data from different bookmarking sites as well as the alignment of tagging ontologies. UTO is described and its utility in modeling, harvesting, integrating, searching, and analyzing data is demonstrated with metadata harvested from three major social tagging systems (Delicious, Flickr, and YouTube)

Four Lessons in Versatility or How Query Languages Adapt to the Web

Exposing not only human-centered information, but machine-processable data on the Web is one of the commonalities of recent Web trends. It has enabled a new kind of applications and businesses where the data is used in ways not foreseen by the data providers. Yet this exposition has fractured the Web into islands of data, each in different Web formats: Some providers choose XML, others RDF, again others JSON or OWL, for their data, even in similar domains. This fracturing stifles innovation as application builders have to cope not only with one Web stack (e.g., XML technology) but with several ones, each of considerable complexity. With Xcerpt we have developed a rule- and pattern based query language that aims to give shield application builders from much of this complexity: In a single query language XML and RDF data can be accessed, processed, combined, and re-published. Though the need for combined access to XML and RDF data has been recognized in previous work (including the W3C’s GRDDL), our approach differs in four main aspects: (1) We provide a single language (rather than two separate or embedded languages), thus minimizing the conceptual overhead of dealing with disparate data formats. (2) Both the declarative (logic-based) and the operational semantics are unified in that they apply for querying XML and RDF in the same way. (3) We show that the resulting query language can be implemented reusing traditional database technology, if desirable. Nevertheless, we also give a unified evaluation approach based on interval labelings of graphs that is at least as fast as existing approaches for tree-shaped XML data, yet provides linear time and space querying also for many RDF graphs. We believe that Web query languages are the right tool for declarative data access in Web applications and that Xcerpt is a significant step towards a more convenient, yet highly efficient data access in a “Web of Data”

Artifact-Centric Semantic Social-Collaboration Network in an Online Healthcare Context

The emergence of Web 2.0 technology and associated social networking system, brings many possibilities and features for online collaboration. Several reference models, frameworks, tools and infrastructures have been proposed to support seamless interaction and communication between human entities in an online social environment. A few studies indicated that social networks are not only constructed on social connections of people, but also mediated by shared objects, known as object-centred sociality. However, most of the developed social software system was centred around the concept of maintaining human-centric social relationships only. This may be because of the common issues of exploiting social network approach for online collaboration related to maintaining the social behaviour, interaction and communication between human and artifacts themselves. These resources or artifacts (i.e., physical objects, software entities, documents, etc.) are active elements in a way that they may coordinate, cooperate, and even trigger collaborative work in a social environment, which is difficult understand and implement. Thus, it is essential to concentrate on exploring the artifact-centric social relations in a new generation of social-collaboration network. This paper explores the concept and characteristics of the social software system and emphasise the importance and role of objects and artifact-centric sociality in a social-collaboration network. We also outline the benefits of semantic representation of social-collaborative network structure by extending existing social ontologies such as FOAF, SIOC, and DC that define additional concepts, properties and complex social relationship of humans, social objects and collaboration artifacts. Finally, we demonstrate the effectiveness of our proposed approach by applying it to a large-scale social-collaborative healthcare service called GRaCE-AGE within the United Kingdom