Leveraging Semantic Web Technologies for Managing Resources in a Multi-Domain Infrastructure-as-a-Service Environment

This paper reports on experience with using semantically-enabled network resource models to construct an operational multi-domain networked infrastructure-as-a-service (NIaaS) testbed called ExoGENI, recently funded through NSF's GENI project. A defining property of NIaaS is the deep integration of network provisioning functions alongside the more common storage and computation provisioning functions. Resource provider topologies and user requests can be described using network resource models with common base classes for fundamental cyber-resources (links, nodes, interfaces) specialized via virtualization and adaptations between networking layers to specific technologies. This problem space gives rise to a number of application areas where semantic web technologies become highly useful - common information models and resource class hierarchies simplify resource descriptions from multiple providers, pathfinding and topology embedding algorithms rely on query abstractions as building blocks. The paper describes how the semantic resource description models enable ExoGENI to autonomously instantiate on-demand virtual topologies of virtual machines provisioned from cloud providers and are linked by on-demand virtual connections acquired from multiple autonomous network providers to serve a variety of applications ranging from distributed system experiments to high-performance computing

vSPARQL: A View Definition Language for the Semantic Web

Translational medicine applications would like to leverage the biological and biomedical ontologies, vocabularies, and data sets available on the semantic web. We present a general solution for RDF information set reuse inspired by database views. Our view definition language, vSPARQL, allows applications to specify the exact content that they are interested in and how that content should be restructured or modified. Applications can access relevant content by querying against these view definitions. We evaluate the expressivity of our approach by defining views for practical use cases and comparing our view definition language to existing query languages

On semantic annotation of decision models

The growth of service sector in recent years has led to renewed research interests in the design and management of service systems. Decision support systems (DSS) play an important role in supporting this endeavor, through management of organizational resources such as models and data, thus forming the “back stage” of service systems. In this article, we identify the requirements for semantically annotating decision models and propose a model representation scheme, termed Semantically Annotated Structure Modeling Markup Language (SA-SMML) that extends Structure Modeling Markup Language (SMML) by incorporating mechanisms for linking semantic models such as ontologies that represent problem domain knowledge concepts. This model representation format is also amenable to a scalable Service-Oriented Architecture (SOA) for managing models in distributed environments. The proposed model representation technique leverages recent advances in the areas of semantic web, and semantic web services. Along with design considerations, we demonstrate the utility of this representation format with an illustrative usage scenarios with a particular emphasis on model discovery and composition in a distributed environment

Ontologies and the Semantic Web for Digital Investigation Tool Selection

The nascent field of digital forensics is heavily influenced by practice. Much digital forensics research involves the use, evaluation, and categorization of the multitude of tools available to researchers and practitioners. As technology evolves at an increasingly rapid pace, the digital forensics field must constantly adapt by creating and evaluating new tools and techniques to perform forensic analysis on many disparate systems such as desktops, notebook computers, mobile devices, cloud, and personal wearable sensor devices, among many others. While researchers have attempted to use ontologies to classify the digital forensics domain on various dimensions, no ontology of digital forensic tools has been developed that defines the capabilities and relationships among the various digital forensic tools. To address this gap, this work develops an ontology using Resource Description Framework (RDF) and Ontology Web Language (OWL) which is searchable via SP ARQL ( an RDF query language) and catalogues common digital forensic tools. Following the concept of ontology design patterns, our ontology has a modular design to promote integration with existing ontologies. Furthermore, we progress to a semantic web application that employs reasoning in order to aid digital investigators with selecting an appropriate tool. This work serves as an important step towards building the knowledge of digital forensics tools. Additionally, this research sets the preliminary stage to bringing semantic web technology to the digital forensics domain as well as facilitates expanding the developed ontology to other tools and features, relationships, and forensic techniques

Knowledge Transformation using a Hypergraph Data Model

In the Semantic Web, knowledge integration is frequently performed between heterogeneous knowledge bases. Such knowledge integration often requires the schema expressed in one knowledge modelling language be translated into an equivalent schema in another knowledge modelling language. This paper defines how schemas expressed in OWL-DL (the Web Ontology Language using Description Logic) can be translated into equivalent schemas in the Hypergraph Data Model (HDM). The HDM is used in the AutoMed data integration (DI) system. It allows constraints found in data modelling languages to be represented by a small set of primitive constraint operators. By mapping into the AutoMed HDM language, we are then able to further map the OWL-DL schemas into any of the existing modelling languages supported by AutoMed. We show how previously defined transformation rules between relational and HDM schemas, and our newly defined rules between OWL-DL and HDM schemas, can be composed to give a bidirectional mapping between OWL-DL and relational schemas through the use of the both-as-view approach in AutoMed

Semantic metrics

In the context of the Semantic Web, many ontology-related operations, e.g. ontology ranking, segmentation, alignment, articulation, reuse, evaluation, can be boiled down to one fundamental operation: computing the similarity and?or dissimilarity among ontological entities, and in some cases among ontologies themselves. In this paper, we review standard metrics for computing distance measures and we propose a series of semantic metrics. We give a formal account of semantic metrics drawn from a variety of research disciplines, and enrich them with semantics based on standard Description Logic constructs. We argue that concept-based metrics can be aggregated to produce numeric distances at ontology-level and we speculate on the usability of our ideas through potential areas

Semantic Gateway as a Service architecture for IoT Interoperability

The Internet of Things (IoT) is set to occupy a substantial component of future Internet. The IoT connects sensors and devices that record physical observations to applications and services of the Internet. As a successor to technologies such as RFID and Wireless Sensor Networks (WSN), the IoT has stumbled into vertical silos of proprietary systems, providing little or no interoperability with similar systems. As the IoT represents future state of the Internet, an intelligent and scalable architecture is required to provide connectivity between these silos, enabling discovery of physical sensors and interpretation of messages between things. This paper proposes a gateway and Semantic Web enabled IoT architecture to provide interoperability between systems using established communication and data standards. The Semantic Gateway as Service (SGS) allows translation between messaging protocols such as XMPP, CoAP and MQTT via a multi-protocol proxy architecture. Utilization of broadly accepted specifications such as W3C's Semantic Sensor Network (SSN) ontology for semantic annotations of sensor data provide semantic interoperability between messages and support semantic reasoning to obtain higher-level actionable knowledge from low-level sensor data.Comment: 16 page

Building the Semantic Web of Things Through a Dynamic Ontology

The Web of Things (WoT) recently appeared as the latest evolution of the Internet of Things and, as the name suggests, requires that devices interoperate through the Internet using Web protocols and standards. Currently, only a few theoretical approaches have been presented by researchers and industry, to fight the fragmentation of the IoT world through the adoption of semantics. This further evolution is known as Semantic WoT and relies on a WoT implementation crafted on the technologies proposed by the Semantic Web stack. This article presents a working implementation of the WoT declined in its Semantic flavor through the adoption of a shared ontology for describing devices. In addition to that, the ontology includes patterns for dynamic interactions between devices, and therefore we define it as dynamic ontology. A practical example will give a proof of concept and overall evaluation, showing how the dynamic setup proposed can foster interoperability at information level allowing on the one hand smart discovery, enabling on the other hand orchestration and automatic interaction through the semantic information available