W3C Resource Description Framework Research Articles

OPAL: An extensible framework for ontology‐based program analysis

SummaryThe syntactic information of a program can be represented as resource description framework (RDF) triples called program triples. We propose an extensible static analysis framework, called OPAL—Ontology‐based Program AnaLysis. The framework enables formal representation of external knowledge, such as usage knowledge of libraries and domain knowledge. Utilizing this knowledge and the program triples, we compute the semantic information, called static trace of the program. It is generated through path‐sensitive intraprocedural traversal of the program. We approximate information in case of loops by unrolling them a fixed number of times. The main contribution of the framework is to store the static trace as RDF triples called semantic triples. They are described using the Program Analysis ontology proposed in this article. The program triples and the semantic triples are together called consolidated program triples. These triples are stored and used to accelerate the execution of client‐analyses specified by the end user. In the framework, a client‐analysis is specified by a set of conjunctive expressions that use SPARQL (W3C RDF query language) queries. The framework is effective for the client‐analyses that warrant sound and approximate information. The effectiveness is assessed first, using two source‐code‐analyses that require only the program triples, and then 10 intraprocedural path‐sensitive analyses that require the consolidated program triples. Using NPB and SPEC 2006 benchmarks, we achieve an improvement in the conciseness of analysis specifications. Also, the execution time using OPAL is competitive to LLVM's clang for individual analysis and outperforms clang over a series of analyses because of the reuse of consolidated program triples.

Semantic driven code generation for networking testbed experimentation

ABSTRACTThis paper investigates how semantic technologies can be used for automatic code generation with a goal to provide easier to use and more efficient working environment to users of large complex infrastructures such as networking testbeds. A new Semantic Driven Code Generation (SecGENE) approach is proposed in the light of a testbed-driven experimentation. The target use-case scenario focuses on heterogeneous telecommunication systems and optimal spectrum usage. The SecGENE approach is examined on the example of semantic coordination process in an environment containing coordinated as well as uncoordinated WiFi networks.Abbreviations: CLOnt – Command Line ontology; ExFOnt – Experiment Flow Ontology; MSAO – Meta System Architecture ontology; NVF – Network Virtualization Function; OEDL – OMF Experiment Description Language; OMN- Open-Multinet ontology; RDFO – A standard W3C Resource Description Framework ontology; SOEDL– Semantic OEDL

Disambiguating descriptions: Mapping digital special collections metadata into linked open data formats

Disambiguating descriptions: Mapping digital special collections metadata into linked open data formats

W3C Plans for Developing Standards for Open Markets of Services for the IoT

The Internet of Things (IoT) is being held back by divergent approaches that result in data silos, high costs, investment risks and reduced market opportunities. To realize the potential and unleash the network effect, W3C is focusing on the role of Web technologies for a platform of platforms as a basis for services spanning IoT platforms from microcontrollers to cloud-based server farms. Shared semantics are essential for discovery, interoperability, scaling and layering on top of existing protocols and platforms. For this purpose, metadata can be classified into: things, security, and communications, where things are considered to be virtual representations (software objects) for physical or abstract entities. Thing descriptions are modeled in terms of W3C's resource description framework (RDF). This includes the semantics for what kind of thing it is, and the data models for its events, properties and actions. The underlying protocols are free to use whichever communication patterns are appropriate to the context according to the constraints described by the given metadata. W3C is exploring the use of lightweight representations of metadata that are easy to author and process, even on resource constrained devices. The aim is to evolve the web from a web of pages to a "Web of Things."

Query-oriented summarization of RDF graphs

The Resource Description Framework (RDF) is a graph-based data model promoted by the W3C as the standard for Semantic Web applications. Its associated query language is SPARQL. RDF graphs are often large and varied , produced in a variety of contexts, e.g., scientific applications, social or online media, government data etc. They are heterogeneous , i.e., resources described in an RDF graph may have very different sets of properties. An RDF resource may have: no types, one or several types (which may or may not be related to each other). RDF Schema (RDFS) information may optionally be attached to an RDF graph, to enhance the description of its resources. Such statements also entail that in an RDF graph, some data is implicit. According to the W3C RDF and SPARQL specification, the semantics of an RDF graph comprises both its explicit and implicit data ; in particular, SPARQL query answers must be computed reflecting both the explicit and implicit data. These features make RDF graphs complex, both structurally and conceptually. It is intrinsically hard to get familiar with a new RDF dataset, especially if an RDF schema is sparse or not available at all.

The ToxBank Data Warehouse: Supporting the Replacement of In Vivo Repeated Dose Systemic Toxicity Testing.

The aim of the SEURAT-1 (Safety Evaluation Ultimately Replacing Animal Testing-1) research cluster, comprised of seven EU FP7 Health projects co-financed by Cosmetics Europe, is to generate a proof-of-concept to show how the latest technologies, systems toxicology and toxicogenomics can be combined to deliver a test replacement for repeated dose systemic toxicity testing on animals. The SEURAT-1 strategy is to adopt a mode-of-action framework to describe repeated dose toxicity, combining in vitro and in silico methods to derive predictions of in vivo toxicity responses. ToxBank is the cross-cluster infrastructure project whose activities include the development of a data warehouse to provide a web-accessible shared repository of research data and protocols, a physical compounds repository, reference or "gold compounds" for use across the cluster (available via wiki.toxbank.net), and a reference resource for biomaterials. Core technologies used in the data warehouse include the ISA-Tab universal data exchange format, REpresentational State Transfer (REST) web services, the W3C Resource Description Framework (RDF) and the OpenTox standards. We describe the design of the data warehouse based on cluster requirements, the implementation based on open standards, and finally the underlying concepts and initial results of a data analysis utilizing public data related to the gold compounds.

AMBIT RESTful web services: an implementation of the OpenTox application programming interface.

The AMBIT web services package is one of the several existing independent implementations of the OpenTox Application Programming Interface and is built according to the principles of the Representational State Transfer (REST) architecture. The Open Source Predictive Toxicology Framework, developed by the partners in the EC FP7 OpenTox project, aims at providing a unified access to toxicity data and predictive models, as well as validation procedures. This is achieved by i) an information model, based on a common OWL-DL ontology ii) links to related ontologies; iii) data and algorithms, available through a standardized REST web services interface, where every compound, data set or predictive method has a unique web address, used to retrieve its Resource Description Framework (RDF) representation, or initiate the associated calculations.The AMBIT web services package has been developed as an extension of AMBIT modules, adding the ability to create (Quantitative) Structure-Activity Relationship (QSAR) models and providing an OpenTox API compliant interface. The representation of data and processing resources in W3C Resource Description Framework facilitates integrating the resources as Linked Data. By uploading datasets with chemical structures and arbitrary set of properties, they become automatically available online in several formats. The services provide unified interfaces to several descriptor calculation, machine learning and similarity searching algorithms, as well as to applicability domain and toxicity prediction models. All Toxtree modules for predicting the toxicological hazard of chemical compounds are also integrated within this package. The complexity and diversity of the processing is reduced to the simple paradigm "read data from a web address, perform processing, write to a web address". The online service allows to easily run predictions, without installing any software, as well to share online datasets and models. The downloadable web application allows researchers to setup an arbitrary number of service instances for specific purposes and at suitable locations. These services could be used as a distributed framework for processing of resource-intensive tasks and data sharing or in a fully independent way, according to the specific needs. The advantage of exposing the functionality via the OpenTox API is seamless interoperability, not only within a single web application, but also in a network of distributed services. Last, but not least, the services provide a basis for building web mashups, end user applications with friendly GUIs, as well as embedding the functionalities in existing workflow systems.

Collaborative learning utilizing a domain-based shared data repository to enhance learning outcomes

The objective of this study was to determine whether there was a quantifiable improvement in learning outcomes by integrating course materials in a 4-year baccalaureate program, utilizing a knowledge repository with a conceptual map that spans a discipline. Two new models were developed to provide the framework for this knowledge repository. A design artifact, Constructivist Unifying Baccalaureate Epistemology (CUBE), was developed and tested and incorporates these models. This CUBE artifact incorporates a Semantic Web ontology and a W3C Resource Description Framework to create a concept space that offers a unified view of the discipline. The Knowledge Repository was modeled as an organic structure with the ability to evolve over time by incorporating a ranking/voting feature which enables students and faculty to add content to the knowledge base and collectively evaluate the relative weights of conceptual threads. Conceptual Clustering was used to create a concept map for traversing the Knowledge Repository. In order to evaluate the effectiveness of the Knowledge Repository, a triangulated research approach was used, which cross checked results with multiple data sources and utilized qualitative and quantitative methods to validate the test instruments. The analyses included: focus groups, semistructured interviews, a questionnaire, and a quantitative exam that measured knowledge spanning multiple courses. Four classes participated during two semesters with four faculty members, using control and treatment groups. The research contrasted conventional single course instruction versus an Integrated Knowledge Repository (IKR) approach to learning. There was an average increase of 25 points in scores on a comprehensive exam for students who used the Knowledge Repository. The results supported our main hypothesis, that “Students utilizing the IKR will develop a more complex understanding of the interconnected nature of the materials linking a discipline than those students who take conventional single topic courses”.

Cooperative Online Resource Catalog (CORC)

Abstract In January 1999, OCLC embarked on a rapid prototyping project known as CORC, Cooperative Online Resource Catalog. It aims to develop a web resource catalog based on Dublin Core (DC), a metadata standard, which complies with W3C's Resource Description Framework (RDF), SML, and HTML. Washtenaw Community College Learning Resource Center is the only community college library joining eighty-four other research participants in this eighteen-month collaborative project. Creating DC metadata records of websites selected for seventy-five academic disciplines, Washtenaw investigates the use-ability of Dublin Core and the CORC system, as well as their implication for the future of Internet searching.