Resource Description Framework Resources Research Articles

Assessing resolvability, parsability, and consistency of RDF resources: a use case in rare diseases

IntroductionHealthcare data and the knowledge gleaned from it play a key role in improving the health of current and future patients. These knowledge sources are regularly represented as ‘linked’ resources based on the Resource Description Framework (RDF). Making resources ‘linkable’ to facilitate their interoperability is especially important in the rare-disease domain, where health resources are scattered and scarce. However, to benefit from using RDF, resources need to be of good quality. Based on existing metrics, we aim to assess the quality of RDF resources related to rare diseases and provide recommendations for their improvement.MethodsSixteen resources of relevance for the rare-disease domain were selected: two schemas, three metadatasets, and eleven ontologies. These resources were tested on six objective metrics regarding resolvability, parsability, and consistency. Any URI that failed the test based on any of the six metrics was recorded as an error. The error count and percentage of each tested resource were recorded. The assessment results were represented in RDF, using the Data Quality Vocabulary schema.ResultsFor three out of the six metrics, the assessment revealed quality issues. Eleven resources have non-resolvable URIs with proportion to all URIs ranging from 0.1% (6/6,712) in the Anatomical Therapeutic Chemical Classification to 13.7% (17/124) in the WikiPathways Ontology; seven resources have undefined URIs; and two resources have incorrectly used properties of the ‘owl:ObjectProperty’ type. Individual errors were examined to generate suggestions for the development of high-quality RDF resources, including the tested resources.ConclusionWe assessed the resolvability, parsability, and consistency of RDF resources in the rare-disease domain, and determined the extent of these types of errors that potentially affect interoperability. The qualitative investigation on these errors reveals how they can be avoided. All findings serve as valuable input for the development of a guideline for creating high-quality RDF resources, thereby enhancing the interoperability of biomedical resources.

Development of an integrated and inferenceable RDF database of glycan, pathogen and disease resources

Glycans are known to play extremely important roles in infections by viruses and pathogens. In fact, the SARS-CoV-2 virus has been shown to have evolved due to a single change in glycosylation. However, data resources on glycans, pathogens and diseases are not well organized. To accurately obtain such information from these various resources, we have constructed a foundation for discovering glycan and virus interaction data using Semantic Web technologies to be able to semantically integrate such heterogeneous data. Here, we created an ontology to encapsulate the semantics of virus-glycan interactions, and used Resource Description Framework (RDF) to represent the data we obtained from non-RDF related databases and data associated with literature. These databases include PubChem, SugarBind, and PSICQUIC, which made it possible to refer to other RDF resources such as UniProt and GlyTouCan. We made these data publicly available as open data and provided a service that allows anyone to freely perform searches using SPARQL. In addition, the RDF resources created in this study are available at the GlyCosmos Portal.

Automated approach for quality assessment of RDF resources

IntroductionThe Semantic Web community provides a common Resource Description Framework (RDF) that allows representation of resources such that they can be linked. To maximize the potential of linked data - machine-actionable interlinked resources on the Web - a certain level of quality of RDF resources should be established, particularly in the biomedical domain in which concepts are complex and high-quality biomedical ontologies are in high demand. However, it is unclear which quality metrics for RDF resources exist that can be automated, which is required given the multitude of RDF resources. Therefore, we aim to determine these metrics and demonstrate an automated approach to assess such metrics of RDF resources.MethodsAn initial set of metrics are identified through literature, standards, and existing tooling. Of these, metrics are selected that fulfil these criteria: (1) objective; (2) automatable; and (3) foundational. Selected metrics are represented in RDF and semantically aligned to existing standards. These metrics are then implemented in an open-source tool. To demonstrate the tool, eight commonly used RDF resources were assessed, including data models in the healthcare domain (HL7 RIM, HL7 FHIR, CDISC CDASH), ontologies (DCT, SIO, FOAF, ORDO), and a metadata profile (GRDDL).ResultsSix objective metrics are identified in 3 categories: Resolvability (1), Parsability (1), and Consistency (4), and represented in RDF. The tool demonstrates that these metrics can be automated, and application in the healthcare domain shows non-resolvable URIs (ranging from 0.3% to 97%) among all eight resources and undefined URIs in HL7 RIM, and FHIR. In the tested resources no errors were found for parsability and the other three consistency metrics for correct usage of classes and properties.ConclusionWe extracted six objective and automatable metrics from literature, as the foundational quality requirements of RDF resources to maximize the potential of linked data. Automated tooling to assess resources has shown to be effective to identify quality issues that must be avoided. This approach can be expanded to incorporate more automatable metrics so as to reflect additional quality dimensions with the assessment tool implementing more metrics.

Stalking the Resources for Security in Linked Data Applications Using Resource Description Framework

Following the accessibility of Resource Description Framework (RDF) resources is a key capacity in the establishment of Linked Data frameworks. It replaces center around information reconciliation contrasted with work rate. Exceptional Connected Data that empowers applications to improve by changing over legacy information into RDF resources. This data contains bibliographic, geographic, government, arrangement, and alternate routes. Regardless, a large portion of them don't monitor the subtleties and execution of each sponsored resource. In such cases, it is vital for those applications to track, store and scatter provenance information that mirrors their source data and introduced tasks. We present the RDF information global positioning framework. Provenance information is followed during the progress cycle and oversaw multiple times. From that point, this data is appropriated utilizing of this concept URIs. The proposed design depends on the Harvard Library Database. The tests were performed on informational indexes with changes made to the qualities??In the RDF and the subtleties related with the provenance. The outcome has quieted the guarantee as in it pulls in record wholesalers to make significant realities that develop while taking almost no time and exertion.

ABCD 3.0 Ready to Use

The TDWG standard ABCD (Access to Biological Collections Data task group 2007) was aimed at harmonizing terminologies used for modelling biological collection information and is used as a comprehensive data format for transferring collection and observation data between software components. The project ABCD 3.0 (A community platform for the development and documentation of the ABCD standard for natural history collections) was financed by the German Research Council (DFG). It addressed the transformation of ABCD into a semantic web-compliant ontology by deconstructing the XML-schema into individually addressable RDF (Resource Description Framework) resources published via the TDWG Terms Wiki (https://terms.tdwg.org/wiki/ABCD_2). In a second step, informal properties and concept-relations described by the original ABCD-schema were transformed into a machine-readable ontology and revised (Güntsch et al. 2016). The project was successfully finished in January 2019. The ABCD 3 setup allows for the creation of standard-conforming application schemas. The XML variant of ABCD 3.0 was restructured, simplified and made more consistent in terms of element names and types as compared to version 2.x. The XML elements are connected to their semantic concepts using the W3C SAWSDL (Semantic Annotation for Web Services Description Language and XML Schema) standard. The creation of specialized applications schemas is encouraged, the first use case was the application schema for zoology. It will also be possible to generate application schemas that break the traditional unit-centric structure of ABCD. Further achievements of the project include creating a Wikibase instance as the editing platform, with related tools for maintenance queries, such as checking for inconsistencies in the ontology and automated export into RDF. This allows for fast iterations of new or updated versions, e.g. when additional mappings to other standards are done. The setup is agnostic to the data standard created, it can therefore also be used to create or model other standards. Mappings to other standards like Darwin Core (https://dwc.tdwg.org/) and Audubon Core (https://tdwg.github.io/ac/) are now machine readable as well. All XPaths (XML Paths) of ABCD 3.0 XML have been mapped to all variants of ABCD 2.06 and 2.1, which will ease transition to the new standard. The ABCD 3 Ontology will also be uploaded to the GFBio Terminology Server (Karam et al. 2016), where individual concepts can be easily searched or queried, allowing for better interactive modelling of ABCD concepts. ABCD documentation now adheres to TDWG’s Standards Documentation Standard (SDS, https://www.tdwg.org/standards/sds/) and is located at https://abcd.tdwg.org/. The new site is hosted on Github: https://github.com/tdwg/abcd/tree/gh-pages.

Skyline queries over possibilistic RDF data

Volume and veracity of data on the Web are two main issues in managing information. In this paper, we tackle these two issues, with a particular interest to Resource Description Framework (RDF) data. For veracity management, we rely on a powerful uncertainty theory, namely possibility theory. Therefore, we propose a model for representing and managing possibilistic RDF data. Alongside, to filter the massive amount of RDF data, we use the skyline operator to find out a small set of resources that satisfy predefined user preferences. To this aim, we also propose a skyline operator to extract possibilistic RDF resources that are possibly dominated by no other resources according to Pareto dominance definition. We introduce a dominance operator and a skyline model adopted to the aforementioned kind of data. In addition, we propose an efficient algorithm to compute the skyline with a reasonable performance. Experiments led on the skyline computation showed satisfying results.

サンプリングに基づく構造推定を用いたLOD視覚的分析支援システム

This paper proposes information visualization system for exploratory LOD (Linked Open Data) Analysis. The LOD is a framework to make data open to the public. Recently, it has been widely used to publish various kinds of data such as statistical data, geographical data, and academic data. The RDF (Resource Description Framework), which describes data as a set of triples consisting of subject, predicate and object, is commonly used to publish data as LOD. When we want to use LOD, it is necessary to understand its structure, such as graph structure of RDF data, used vocabularies and resources. Therefore, we often have to conduct exploratory analysis of LOD. In order to support the analysis, the proposed system analyzes the structure of LOD written with RDF, and visualizes the result of analysis. As most of currently available LOD have table structure, the proposed system identifies whether target dataset contains table structure or not using resource sampling with SPARQL queries. Graph structure of resources obtained by the resource sampling is visualized by assigning different colors to different tables. A user cannot only examine the visualized structure, but also conduct exploratory search by selecting a resource in the visualized result. Effectiveness of the proposed system is evaluated by applying it to several LOD resources. Experiments with test participants are also conducted, of which results show even users who are not familiar with RDF can perform exploratory analysis effectively.

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.

Fuzzy Knowledge Representation for Fuzzy Systems Based on Fuzzy Ontology on the Semantic Web

Ontology is adopted as a standard for knowledge representation on the Semantic Web, and Resource Description Framework (RDF) is used to add structure and meaning to Web applications. In order to incorporate fuzzy systems into the Semantic Web, this paper utilizes fuzzy ontology to represent formally the fuzzy linguistic variables, considering the semantic relationships between fuzzy concepts. Then fuzzy rule is described as a RDF resource with properties: “IF” and “THEN”, and rule's antecedent and consequent is represented in RDF statement. Taking the fuzzy control system of industrial washing machine for example, the fuzzy system with ontology and RDF is built, which shows that this research enables distributed fuzzy applications on the Semantic Web.

Building biomedical web communities using a semantically aware content management system

Web-based biomedical communities are becoming an increasingly popular vehicle for sharing information amongst researchers and are fast gaining an online presence. However, information organization and exchange in such communities is usually unstructured, rendering interoperability between communities difficult. Furthermore, specialized software to create such communities at low cost-targeted at the specific common information requirements of biomedical researchers-has been largely lacking. At the same time, a growing number of biological knowledge bases and biomedical resources are being structured for the Semantic Web. Several groups are creating reference ontologies for the biomedical domain, actively publishing controlled vocabularies and making data available in Resource Description Framework (RDF) language. We have developed the Science Collaboration Framework (SCF) as a reusable platform for advanced structured online collaboration in biomedical research that leverages these ontologies and RDF resources. SCF supports structured 'Web 2.0' style community discourse amongst researchers, makes heterogeneous data resources available to the collaborating scientist, captures the semantics of the relationship among the resources and structures discourse around the resources. The first instance of the SCF framework is being used to create an open-access online community for stem cell research-StemBook (http://www.stembook.org). We believe that such a framework is required to achieve optimal productivity and leveraging of resources in interdisciplinary scientific research. We expect it to be particularly beneficial in highly interdisciplinary areas, such as neurodegenerative disease and neurorepair research, as well as having broad utility across the natural sciences.

Using social networking and semantic web technology in software engineering – Use cases, patterns, and a case study

We present an approach that uses social networking and semantic web technology to share knowledge within the software engineering community. We propose to use existing Web 2.0 services such as social bookmarking and blogs as the infrastructure to share knowledge artefacts. Due to the openness of these services, it is crucial to provide support to establish the trustworthiness of knowledge artefacts. The solution proposed is designed following the original semantic web stack architecture and uses existing and emerging W3C semantic web standards such as the Resource Description Framework (RDF), the Web Ontology Language (OWL), and the Semantic Web Rule Language (SWRL). The WebOfPatterns project is presented as a case study, which includes an Eclipse plug-in that can be used to discover design pattern definitions in social networks, to define and publish patterns, to rate patterns, to establish the trustworthiness of patterns found, and finally to scan Java projects for instances of discovered patterns. We also propose the ContributedProperties design pattern that can be used to bridge the conceptual gap between RDF resources and objects in an object-oriented programming language.

Statistical search on the Semantic Web

Statistical analysis of links on the Semantic Web is important for various evaluation purposes such as quantifying an individual's scientific research output based on citation links. SPARQL has been proposed as a standardized query language for the Semantic Web and is intuitively understandable; however, it does not adequately support statistical evaluation of semantic links. We have extended SPARQL to a novel Resource Description Framework (RDF) query language termed General and Rapid Association Study Query Language (GRASQL) to generate inferences connecting semantic Boolean-based deduction and statistical evaluation of RDF resources. We have verified the descriptive capability of GRASQL by writing GRASQL queries for practical biomedical search patterns including in silico positional cloning studies and for ranking researchers in a specific domain of expertise by introducing k index, the number of papers containing specific keywords that are published in a fixed period by a researcher. We have also developed a search engine termed General and Rapid Association Study Engine (GRASE), which executes a restricted variety of GRASQL queries by requesting a dynamic and comprehensive evaluation of statistical significance of intersections between each group of documents assigned to URIs and those documents matching user-specified keywords and omics conditions. By performing practical in silico positional cloning searches with GRASE, we show the relevance of our approach on the Semantic Web for biomedical knowledge discovery problem solving. GRASE is used as the search engine for the Positional Medline (PosMed) service and Researcher Finder service at http://omicspace.riken.jp/.

A Graphical RDF-Based Meta-Model Management Tool

We propose a tool to manage several sorts of relationships among RDF (Resource Description Framework) and RDFS (RDF Schema). Our tool consists of three main functions: graphical editing of RDF descriptions, graphical editing of RDFS descriptions, and meta-model management facilities. In this paper, we focus on the meta-model management, a key concept which is defined as the appropriate management of the correspondence between a model and its meta-model: especially, the class and property in the meta-model, and the type of RDF resource and property in the model. The above facilities are implemented based on the plug-in system. We provide basic plug-in modules for checking the consistency of RDFS classes and properties. The prototyping tool, called MR3 (Meta-Model Management based on RDFs Revision Reflection), is implemented by Java language. Through an experiment using MR3, we show how MR3 contributes to the Semantic Web paradigm from the standpoint of RDFs description management.