Representing time and space for the semantic web

Representation of temporal and spatial information for the Semantic Web often involves qualitative defined information (i.e., information described using natural language terms such as "before" or "overlaps") since precise dates or coordinates are not always available. This work proposes several temporal representations for time points and intervals and spatial topological representations in ontologies by means of OWL properties and reasoning rules in SWRL. All representations are fully compliant with existing Semantic Web standards and W3C recommendations. Although qualitative representations for temporal interval and point relations and spatial topological relations exist, this is the first work proposing representations combining qualitative and quantitative information for the Semantic Web. In addition to this, several existing and proposed approaches are compared using different reasoners and experimental results are presented in detail. The proposed approach is applied to topological relations (RCC5 and RCC8) supporting both qualitative and quantitative (i.e., using coordinates) spatial relations. Experimental results illustrate that reasoning performance differs greatly between different representations and reasoners. To the best of our knowledge, this is the first such experimental evaluation of both qualitative and quantitative Semantic Web temporal and spatial representations. In addition to the above, querying performance using SPARQL is evaluated. Evaluation results demonstrate that extracting qualitative relations from quantitative representations using reasoning rules and querying qualitative relations instead of directly querying quantitative representations increases performance at query time

Integrating Semantic Web technologies and Multi-Agent Systems: a Semantic Description of Multi-Agent Organizations

http://ceur-ws.org/Vol-918/111110296.pdfInternational audienceDecentralization and openness are inherent properties of multi- agent systems (MAS). The technologies they provide are thus the right abstrac- tion for developing Web-oriented applications. Moreover, di erent works have been proposed to use Semantic Web technologies (SWT) for representing vari- ous dimensions of MAS (e.g., interaction protocols, norms, organizations). Given these facts, we think it is time to go a step further by integrating SWT and MAS in order to improve reusability of data, knowledge, coordination strategies, etc. on the Web and across systems. In this paper, we take a rst step in this direc- tion by proposing a semantic description of multi-agent organizations, showing the bene t regarding integration with Web ontologies

Exposing WikiPathways as Linked Open Data

Biology has become a data intensive science. Discovery of new biological facts increasingly relies on the ability to find and match appropriate biological data. For instance for functional annotation of genes of interest or for identification of pathways affected by over-expressed genes. Functional and pathway information about genes and proteins is typically distributed over a variety of databases and the literature.

Pathways are a convenient, easy to interpret way to describe known biological interactions. WikiPathways provides community curated pathways. WikiPathways users integrate their knowledge with facts from the literature and biological databases. The curated pathway is then reviewed and possibly corrected or enriched. Different tools (e.g. Pathvisio and Cytoscape) support the integration of WikiPathways-knowledge for additional tasks, such as the integration with personal data sets. 

Data from WikiPathways is increasingly also used for advanced analysis where it is integrated or compared with other data, Currently, integration with data from different biological sources is mostly done manually. This can be a very time consuming task because the curator often first needs to find the available resources, needs to learn about their specific content and qualities and often spends a lot of time to technically combine the two. 

Semantic web and Linked Data technologies eliminate the barriers between database silos by relying on a set of standards and best practices for representing and describing data. The architecture of the semantic web relies on the architecture of the web itself for integrating and mapping universal resource identifiers (URI), coupled with basic inference mechanisms to enable matching concepts and properties across data sources. Semantic Web and Linked Data technologies are increasingly being successfully applied as integration engines for linking biological elements. 

Exposing WikiPathways content as Linked Open Data to the Semantic Web, enables rapid, semi-automated integration with a the growing amount of biological resources available from the linked open data cloud, it also allows really fast queries of WikiPathways itself. 

We have harmonised WikiPathways content according to a selected set of vocabularies (Biopax, CHEMBL, etc), common to resources already available as Linked Open Data. 
WikiPathways content is now available as Linked Open Data for dynamic querying through a SPARQL endpoint: http://semantics.bigcat.unimaas.nl:8000/sparql

INFRASTRUCTURE FOR INTEROPERABILITY OF THE E-GOVERNMENT APPLICATIONS BASED ON SEMANTIC WEB SERVICES

The e-Government interoperability is the ability of ICT components/applications to work together, in other words it is the ability of two or more diverse government (ICT) systems or components to sharing and re-use of information-services, inter-linking of administrative tasks, within and between sectors are essential factors for the delivery of high quality, innovative, seamless and customer-centric e-services. The organizational interoperability refers to the cooperation way of the public administrations processes, by defining the communication interfaces between processes. This approach addresses the interoperability of e-government applications at organizational and semantic level, adopting Web services (WS) and Semantic Web Services (SWS) as technological solutions. The e-Government interoperability is becoming an increasingly crucial issue, especially for developing countries that have committed to the achievement of the Millennium Development Goals (MDGs) by 2015 . Enhanced government efficiency and effectiveness coupled with the delivery of basic public services to all citizens are essential components required to achieve such goals. In this context, most governments have finalized the design of national e-government strategies and are busy implementing priority programmes. Today the data needed by policy makers to make better decisions is available but inaccessible. Policy makers are faced not only with overlapping and uncoordinated data sources, but also with the absence of common terms of reference and means of representing these data. This results in the time consuming and complex cost of comparing data that is represented differently. Interoperability will allow data compiled by different agencies to be used together to make faster and better decisions. An important goal of governance is to enable the citizenry to have easier and faster access to government information and services. The seamless flow of data from one government office to another provides the policy maker with the information needed to draft sound policy and deliver better services. In this paper we present an approach, which addresses the interoperability of e-government applications at organizational and semantic level, adopting Web services (WS) and Semantic Web Services (SWS) as technological solutions. The main objective of this work consists in designing and developing a distributed network of semantic registries in order to publish, find and execute the Web services. The publishing in registries of the Web services consists in the execution of syntactic and semantic matching algorithms between the attributes of the registries and the attributes of Web services.e-government application, interoperability, semantic registries, WSDL standard

Spatial Reasoning for the Semantic Web -Use Cases and Technological Challenges

The goal of semantic web research is to turn the World-Wide Web into a Web of Data that can be processed automatically to a much larger extend than possible with traditional web technology. Important features of the solution currently being developed is the ability to link data from from different sources and to provide formal definitions of the intended meaning of the terminology used in different sources as a basis for deriving implicit information and for conflict detection. Both requires the ability to reason about the definition of terms. With the development of OWL as the standard language for representing terminological knowledge, reasoning in description logics has been determined as the major technique for performing this reasoning So far little attention has been paid to the problem of representing and reasoning about space and time on the semantic web. In particular, existing semantic web languages are not well suited for representing these aspects as they require to operate over metric spaces that behave fundamentally different from the abstract interpretation domains description logics are based on. Nevertheless, there is a strong need to integrate reasoning about space and time into existing semantic web technologies especially because more and more data available on the web has a references to space and time. Images taken by digital cameras are a good example of such data as they come with a time stamp and geographic coordinates. In this paper, we concentrate on spatial aspects and discuss different use case for reasoning about spatial aspects on the (semantic) web and possible technological solutions for these use cases. Based on these discussions we conclude that the actual open problem is not existing technologies for terminological or spatial reasoning, but the lack of an established mechanism for combining the two. The Case for Spatial Queries One of the most central functionality that should be supported by semantic web technology is query answering over web data. The primary language for this purpose i

Temporal Representation and Reasoning in OWL 2

The representation of temporal information has been in the center of intensive research activities over the years in the areas of knowledge representation, databases and more recently, the Semantic Web. The proposed approach extends the existing framework of representing temporal information in ontologies by allowing for representation of concepts evolving in time (referred to as “dynamic” information) and of their properties in terms of qualitative descriptions in addition to quantitative ones (i.e., dates, time instants and intervals). For this purpose, we advocate the use of natural language expressions, such as “before” or “after”, for temporal entities whose exact durations or starting and ending points in time are unknown. Reasoning over all types of temporal information (such as the above) is also an important research problem. The current work addresses all these issues as follows: The representation of dynamic concepts is achieved using the “4D-fluents” or, alternatively, the “N-ary relations” mechanism. Both mechanisms are thoroughly explored and are expanded for representing qualitative and quantitative temporal information in OWL. In turn, temporal information is expressed using either intervals or time instants. Qualitative temporal information representation in particular, is realized using sets of SWRL rules and OWL axioms leading to a sound, complete and tractable reasoning procedure based on path consistency applied on the existing relation sets. Building upon existing Semantic Web standards (OWL), tools and member submissions (SWRL), as well as integrating temporal reasoning support into the proposed representation, are important design features of our approach

Oveia: expanding the topic maps frontier

Ontology based websites are one possible implementation of the Semantic Web. There are several languages for ontology specification: RDF, OWL, Topic Maps. Topic Maps follow a structure formally specified what makes them a good choice for semantic website specification. The process of ontology development based in topic maps is complex, time consuming, and it requires a lot of human and financial resources, because they can have a lot of topics and associations, and the number of information resources can be very large. To overcome this problem a new environment is proposed, Oveia. Oveia is composed by four components which have relevant contributions to the Semantic Web area. This paper describes these components in detail. Two components representing a metadata extractor: heterogeneous data integration (through XSDS specifications) and an homogeneous intermediate data representation for the extracted metadata (datasets). The Ontology builder who builds an ontology from metadata stored in a set of datasets (construction rules are specified in a new domain specific language: XS4TM). The Ontology builder stores the result in XTM files or in relational databases according to the Topic Map structure. Finally, Ulisses, the navigational component, generates web interfaces through which is possible to move inside the topic map and among information resources

Template-based ontology population for Smart Environments configuration

Smart Environment is one of several domains in which Semantic Web technologies are applied nowadays. Ontologies, in particular, are used as core modeling languages for representing devices, systems and environments. Developing such ontologies, that typically involve several device descriptions (individuals) and related information, i.e., individuals of classes contributing to the device model, is often done by a manual, time consuming, and error-prone approach. Flexible and semi-automatic tools are therefore needed to enhance ontology population and to enable end-users to fruitfully configure their Smart Environments without the intervention of an ontology expert. This paper presents a template based approach, which increases accuracy, ease of use, and time-effectiveness of the ontology population process by reducing the amount of user-given information of about an order of magnitude, with respect to the fully manual approach. User-required information only pertains device features (e.g., name, location, etc.) and never implies knowledge of Semantic Web technologies, thus enabling end-user configuration of smart homes and buildings. Experimental results with a prototypical implementation confirm the viability of the approach on a real-world use cas

SEON: a pyramid of ontologies for software evolution and its applications

The Semantic Web provides a standardized, well-established framework to define and work with ontologies. It is especially apt for machine processing. However, researchers in the field of software evolution have not really taken advantage of that so far. In this paper, we address the potential of representing software evolution knowledge with ontologies and Semantic Web technology, such as Linked Data and automated reasoning. We present Seon, a pyramid of ontologies for software evolution, which describes stakeholders, their activities, artifacts they create, and the relations among all of them. We show the use of evolution-specific ontologies for establishing a shared taxonomy of software analysis services, for defining extensible meta-models, for explicitly describing relationships among artifacts, and for linking data such as code structures, issues (change requests), bugs, and basically any changes made to a system over time. For validation, we discuss three different approaches, which are backed by Seon and enable semantically enriched software evolution analysis. These techniques have been fully implemented as tools and cover software analysis with web services, a natural language query interface for developers, and large-scale software visualizatio

Uncertain Knowledge Reasoning Based on the Fuzzy Multi-Entity Bayesian Network

With the rapid development of the semantic web and the ever-growing size of uncertain data, representing and reasoning uncertain information has become a great challenge for the semantic web application developers. In this paper, we present a novel reasoning framework based on the representation of fuzzy PR-OWL. Firstly, the paper gives an overview of the previous research work on uncertainty knowledge representation and reasoning, incorporates Ontology into the fuzzy Multi Entity Bayesian Networks theory, and introduces fuzzy PR-OWL, an Ontology language based on OWL2. Fuzzy PR-OWL describes fuzzy semantics and uncertain relations and gives grammatical definition and semantic interpretation. Secondly, the paper explains the integration of the Fuzzy Probability theory and the Belief Propagation algorithm. The influencing factors of fuzzy rules are added to the belief that is propagated between the nodes to create a reasoning framework based on fuzzy PR-OWL. After that, the reasoning process, including the SSFBN structure algorithm, data fuzzification, reasoning of fuzzy rules, and fuzzy belief propagation, is scheduled. Finally, compared with the classical algorithm from the aspect of accuracy and time complexity, our uncertain data representation and reasoning method has higher accuracy without significantly increasing time complexity, which proves the feasibility and validity of our solution to represent and reason uncertain information