One promise of Semantic Web applications is to seamlessly deal with heterogeneous data. The Extensible Markup Language (XML) has become widely adopted as an almost ubiquitous interchange format for data, along with transformation languages like XSLT and XQuery to translate data from one XML format into another. However, the more recent Resource Description Framework (RDF) has become another popular standard for data representation and exchange, supported by its own query language SPAR-QL, that enables extraction and transformation of RDF data. Being able to work with XML and RDF using a common framework eliminates several unnecessary steps that are currently required when handling both formats side by side. In this paper we present the XSPARQL language that, by combining XQuery and SPARQL, allows to query XML and RDF data using the same framework and transform data from

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The purpose of this study is to characterise the environmental management systems (EMS) certification process (International Organization for Standardization (ISO) 14001) in Portuguese small and medium enterprises (SMEs) following quality management system (QMS) certification (ISO 9001). The study is based on a sample from Portuguese SMEs which characterise the local reality in terms of companies certified in accordance with ISO 14001 after ISO 9001 certification. Some Portuguese SMEs have the EMS implemented but not certified, mainly given the lack of investment support and because it is considered merely a form of marketing. As such, they do not feel motivated to certificate an EMS in the company since they consider that it is a form of advertising and not a way to protect the environment. Nonetheless, it is already evident form other Portuguese SMEs that gained EMS certification that gains supersede marketing benefits and allow for evermore enduring benefits such as prevention of environmental risks, environment protection, improved company image, compliance with legislation and efficient use of natural resources. This paper also presented the main difficulties in achieving an EMS certification, including high certification costs, human resources, motivation issues and difficulties in changing the company's culture.

We describe a generic framework for representing and reasoning with annotated Semantic Web data, a task becoming more important with the recent increased amount of inconsistent and non-reliable meta-data on the web. We formalise the annotated language, the corresponding deductive system and address the query answering problem. Previous contributions on specific RDF annotation domains are encompassed by our unified reasoning formalism as we show by instantiating it on (i) temporal, (ii) fuzzy, and (iii) provenance annotations. Moreover, we provide a generic method for combining multiple annotation domains allowing to represent, e.g., temporally-annotated fuzzy RDF. Furthermore, we address the development of a query language -AnQL -that is inspired by SPARQL, including several features of SPARQL 1.1 (subqueries, aggregates, assignment, solution modifiers) along with the formal definitions of their semantics.

International audienceWe describe a generic framework for representing and reasoning with annotated Semantic Web data, a task becoming more important with the recent increased amount of inconsistent and non-reliable meta-data on the Web. We formalise the annotated language, the corresponding deductive system and address the query answering problem. Previous contributions on specific RDF annotation domains are encompassed by our unified reasoning formalism as we show by instantiating it on (i) temporal, (ii) fuzzy, and (iii) provenance annotations. Moreover, we provide a generic method for combining multiple annotation domains allowing to represent, e.g., temporally-annotated fuzzy RDF. Furthermore, we address the development of a query language – AnQL – that is inspired by SPARQL, including several features of SPARQL 1.1 (subqueries, aggregates, assignment, solution modifiers) along with the formal definitions of their semantics