Diagrams can be an effective means of communicating complex ideas and can aid ontology engineering. Indeed, domain experts often do not have the expertise required to understand or create the complex logical statements of an ontology in description logic (DL). This paper presents a visualisation method, concept diagrams, geared toward expressing assertions and class expression axioms alongside providing support for literals, datatypes and data properties. Property diagrams are introduced, targeted at object property and data property expression axioms. We demonstrate that concept diagrams and property diagrams provide a large coverage of OWL 2 axioms and are, thus, closely aligned in expressive power.

Integrating and accessing data from the many existing formats is a key challenge for the Semantic Web. In particular, representing and understanding non-RDF/OWL data in terms of ontologies is important for reasoning about this data and its relationships to other data, and for extracting or accessing the data itself. This paper presents a declarative method for mapping and translating spreadsheet data to RDF/OWL. First, a declarative mapping language is presented. Then, for this syntax, the paper presents a declarative semantics in terms of matrix operations as abstractions over spreadsheets and the relations therein. The language supports arbitrary search and indexing functions over spreadsheet data and allows the generation of complex associations and aggregations in the RDF/OWL output. Imperative and functional implementations of the mapping and extraction technology are presented.

The syntax of both SROIQ and OWL 2 allow complex role inclusion axioms where the role composition occurs on the left of the subsumption relation, but not where the role composition occurs on the right. This paper proves that, despite the lack of syntax, SROIQ, and consequently OWL 2, can already express such complex role inclusions. This is shown by proving that complex role inclusion axioms where the role composition occurs on the right of the subsumption relation can already be expressed in terms of complex role inclusions on the left. The resulting syntactic restrictions are similar to those already present in SROIQ and OWL 2.

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a substantial acceleration of the growth rate in the future. It is also evident that the increasing number of IoT middleware solutions are developed in both research and commercial environments. However, sensor search and selection remain a critical requirement and a challenge. In this paper, we present CASSARAM, a context-aware sensor search, selection, and ranking model for Internet of Things to address the research challenges of selecting sensors when large numbers of sensors with overlapping and sometimes redundant functionality are available. CASSARAM proposes the search and selection of sensors based on user priorities. CASSARAM considers a broad range of characteristics of sensors for search such as reliability, accuracy, battery life just to name a few. Our approach utilises both semantic querying and quantitative reasoning techniques. User priority based weighted Euclidean distance comparison in multidimensional space technique is used to index and rank sensors. Our objectives are to highlight the importance of sensor search in IoT paradigm, identify important characteristics of both sensors and data acquisition processes which help to select sensors, understand how semantic and statistical reasoning can be combined together to address this problem in an efficient manner. We developed a tool called CASSARA to evaluate the proposed model in terms of resource consumption and response time.

The W3C Semantic Sensor Network Incubator group (the SSN-XG) produced an OWL 2 ontology to describe sensors and observations — the SSN ontology, available at http://purl.oclc.org/NET/ssnx/ssn. The SSN ontology can describe sensors in terms of capabilities, measurement processes, observations and deployments. This article describes the SSN ontology. It further gives an example and describes the use of the ontology in recent research projects.

Due to environmental and contextual changes, it is often required to configure and re-configure sensor network services. The burden of programming a sensor network, as a consequence of these changes, can be alleviated with a plug-and-play approach that allows dynamic adaptation of sensor network services. In this paper, we briefly present a semantics-based methodology to avail self-configuration of sensor services with minimal human intervention. We also provide a practical usage scenario and our preliminary work in this context.

This paper presents a study of equivalent rewritings for conjunctive queries and views: that is, queries and views expressed in terms of database predicates, but not built-in predicates. It analyses conjunctive queries and views with an exact, set semantics, corrects some errors in prior work and shows necessary and sufficient conditions on the query and views for an equivalent rewriting to exist, including showing when a view covers part of a query. The paper presents a sound and complete algorithm for finding equivalent rewritings.