RDF Vocabulary Research Articles

The W3C Data Catalog Vocabulary, Version 2: Rationale, Design Principles, and Uptake

ABSTRACT DCAT is an RDF vocabulary designed to facilitate interoperability between data catalogs published on the Web. Since its first release in 2014 as a W3C Recommendation, DCAT has seen a wide adoption across communities and domains, particularly in conjunction with implementing the FAIR data principles (for findable, accessible, interoperable and reusable data). These implementation experiences, besides demonstrating the fitness of DCAT to meet its intended purpose, helped identify existing issues and gaps. Moreover, over the last few years, additional requirements emerged in data catalogs, given the increasing practice of documenting not only datasets but also data services and APIs. This paper illustrates the new version of DCAT, explaining the rationale behind its main revisions and extensions, based on the collected use cases and requirements, and outlines the issues yet to be addressed in future versions of DCAT.

Indonesia COVID-19 cases report using Linked Open Data

Coronavirus disease is a worldwide pandemic. The need for accurate data and information become an important thing in this pandemic situation. In Indonesia, the government provides an official website for displaying COVID-19 spread statistics. However, the data provided does not follow the 5-star open data. As a result, the data is not reusable and integrated easily into another dataset and application. In this paper, we proposed an RDF vocabulary for presenting COVID-19 data in Indonesia. In addition, two queries are presented as an example for using our vocabulary and dataset as part of Linked Open data movement.

BimSPARQL: Domain-specific functional SPARQL extensions for querying RDF building data

In this paper, we propose to extend SPARQL functions for querying Industry Foundation Classes (IFC) building data. The official IFC documentation and BIM requirement checking use cases are used to drive the development of the proposed functionality. By extending these functions, we aim to (1) simplify writing queries and (2) retrieve useful information implied in 3D geometry data according to requirement checking use cases. Extended functions are modelled as RDF vocabularies and classified into groups for further extensions. We combine declarative rules with procedural programming to implement extended functions. Realistic requirement checking scenarios are used to evaluate and demonstrate the effectiveness of this approach and indicate query performance. Compared with query techniques developed in the conventional Building Information Modeling domain, we show the added value of such approach by providing an application example of querying building and regulatory data, where spatial and logic reasoning can be applied and data from multiple sources are required. Based on the implementation and evaluation work, we discuss the advantages and applicability of this approach, current issues and future challenges.

EXTENSION AND CONTEXTUALISATION FOR LINKED SEMANTIC 3D GEODATA

Abstract. The application of the linked data principles provide a simple and effective way to publish and share data on the Web. The publication of geodata on the Web bas been studied and developed for a long time, leading to the creation of geo vocabularies and ontologies as well as geographic query languages. This is also true for 3D geodata, for which multiple RDF vocabularies and OWL ontologies exist (at the building, city, or territory level). In this paper we show that at least two issues remain to be addressed to reach a satisfactory publication framework for 3D linked geodata. First, the semantic model interconnection issue is not magically solved by the creation of ontologies, it requires the careful design of interconnection and extension schemes and their management. Second, the representation of additional dimensions, such as time, level of detail, confidence level, provenance, etc. cannot be directly handled in RDF. For these two issues we propose methodologies and design patterns and show how they can actually be used to create a semantically rich representation of 3D or nD linked geodata.

TEMPORAL GIS AND SPATIOTEMPORAL DATA SOURCES

The recent technological advances in geospatial data collection have created massive data sets with better spatial and temporal resolution than ever. To properly deal with these data sets, geographical information systems (GIS) must evolve to represent, access, analyze and visualize big spatiotemporal data in an efficient and integrated way. In this paper, we highlight challenges in temporal GIS development and present a proposal to overcome one of them: how to access spatiotemporal data sets from distinct kinds of data sources. Our approach uses Semantic Web techniques and is based on a data model that takes observations as basic units to represent spatiotemporal information from different application domains. We define a RDF vocabulary for describing data sources that store or provide spatiotemporal observations.

RDF dataset profiling – a survey of features, methods, vocabularies and applications

The Web of Data, and in particular Linked Data, has seen tremendous growth over the past years. However, reuse and take-up of these rich data sources is often limited and focused on a few well-known and established RDF datasets. This can be partially attributed to the lack of reliable and up-to-dat e information about the characteristics of available datasets. While RDF datasets vary heavily with respect to the features related to quality, provenance, interlinking, licenses, statistics and dynamics, reliable information about such features is essential to enable dataset discovery and selection in tasks such as entity linking, distributed query, search or question answering. Even though there exists a wealth of works contributing to the task of dataset profiling in general, these works are spread across a wide range of communities. In this survey, we provide a first comprehensive overview of the RDF dataset profiling features, methods, tools and vocabularies. We organize these building blocks of dataset profiling in a taxonomy and illustrate the links between the dataset profiling and feature extraction approaches and several application domains. This survey is aimed towards data practitioners, data providers and scientists, spanning a large range of communities and drawing from different fields such as dataset profiling, assessment, summarization and characterization. Ultimately, this work is intended to facilitate the reader to identify the relevant features for building a dataset profile for intended applications together with the methods and tools capable of extracting these features from the datasets as well as vocabularies to describe the extracted features and make them available.

Designing an Ontology to Describe Ecological Cycling Routes within the Province of Tungurahua

Tourism, a significant industry worldwide, has allowed for economic, social, and cultural development in rural areas because of all the advantages it offers to tourists. Ecuador is a country that presents a wide range of alternatives in the tourist field allowing a massive tourist influx to many of its destinations such as indigenous communities, natural reserves, and tourist, ecological, and volcanic routes. Most importantly, Ecuador encourages the conservation of the diversity resulting from such influx. The objective of this research is to design an ontology which facilitates a description of the bicycle tourist routes in the province of Tungurahua, and specifically in the city of Ambato. Apart from route descriptions, this ontology gives information about the flora and fauna and places of interest such as inns, hotels, and restaurants that can be found along this route. This ontology was developed based on the application and enforcement of semantic web technologies. That being said, all the described information is attached to an RDF vocabulary and it can be accessed using SPARQL. Therefore, information that is semantically described in an organized and standardized manner is available in order to allow for interoperability with other existing data sources. As for the development of the ontology, the methodology used was an open code software known as “protégé”. The OWL (Ontology Web Language) was also used as marked language and RDFS for the description of the employed vocabulary.

SESLDS: An Extension Scheme for Linked Data Sources Based on Semantically Enhanced Annotation and Reasoning

In the era of Big Data, users prefer to get knowledge rather than pages from Web. Linked Data, a rather new form of knowledge representation and publishing described by RDF, can provide a more precise and comprehensible semantic structure to satisfy the aforementioned requirement. Besides, as the standard query language for RDF data, SPARQL has become the foundation protocol of Linked Data querying. The core idea of RDF Schema (RDFS) is to extend upon RDF vocabulary and allow attachment of semantics to user defined classes and properties. However, RDFS cannot fully utilize the potential of RDF since it cannot express the implicit semantics between linked entities in Linked Data sources. To fill this gap, in this paper, we design a new semantic annotating and reasoning approach that can extend more implicit semantics from different properties. We firstly establish a well-defined semantically enhanced annotation strategy for Linked Data sources. In particular, we present some new semantic properties for predicates in RDF triples and design a Semantic Matrix for Predicates (SMP). We then propose a novel general Semantically Extended Scheme for Linked Data Sources (SESLDS) to realize the semantic extension over the target Linked Data source through semantically enhanced reasoning. Lastly, based on the experimental analyses, we verify that our proposal has advantages over the initial Linked Data source and can return more valid results.

On the origin of annotations: A module-based approach to representing annotations in the Natural Language Processing Interchange Format (NIF)

Representing provenance information for data is of crucial importance for data reuse. This is in particular the case for language resources such as annotated corpora. NIF has been proposed as an RDF vocabulary to support the representation of text data together with annotations. However, NIF suffers from severe shortcomings with respect to its ability to represent provenance information. As a remedy to this, we present MOND, a new glue ontology that implements an interface between NIF and the PROV-O ontology to support the inclusion of provenance information into NIF annotated datasets. We first present an approach that reifies annotations and allows the attachment of any provenance metadata to annotations at arbitrary granularity. We show that this approach has an important drawback as it roughly doubles the size of the data. Building on this observation, we design the MOND glue ontology that implements a modular approach in which annotation metadata is not attached to single annotations but to modules that represent collections of annotations of the same type and origin. This yields a moderate increase in data size, while maintaining all the benefits of the first approach. We validate our approach on three use cases that represent prototypical needs in corpus work.

Darwin-SW: Darwin Core-based terms for expressing biodiversity data as RDF

Darwin-SW (DSW) is an RDF vocabulary designed to complement the Biodiversity Information Standards (TDWG) Darwin Core Standard. DSW is based on a model derived from a community discussion about the relationships among the main Darwin Core classes. DSW creates a new class to accommodate an important aspect of its model that is not currently part of Darwin Core: a class of Tokens, which are forms of evidence. DSW uses Web Ontology Language (OWL) to make assertions about the classes in its model and to define object properties that are used to link instances of those classes. A goal in the creation of DSW was to facilitate consistent markup of biodiversity data so that RDF graphs created by different providers could be easily merged. Accordingly, DSW provides a mechanism for testing whether its terms are being used in a manner consistent with its model. Two transitive object properties enable the creation of simple SPARQL queries that can be used to discover new information about linked resources whose metadata are generated by different providers. The Organism class enables semantic linking of biodiversity resources to vocabularies outside of TDWG that deal with observations and ecological phenomena.

Timestamp Embedding Query Stream Processing Engine

Background/Objectives: To improve the performance of the streaming data through RDF vocabulary and multi query optimization. Methods/Statistical Analysis: The scalability and performance of the query processor is improved with the use of native timestamp embedding query processor with the help of semantic approach. This offers vibrant, scalable services for continuous query processing. Continuous data is controlled through dynamic sliding window for incremental evaluation of streaming data. Static queries are processed continuously and all processing is done within main memory. Semantic sensor web is used to processor sensor data semantically by query processing engine and metadata will be stored as triple stores. Findings: The continuous stream of queries is properly handled by the dynamic sliding window and sent to the query optimizer for optimization. The triple formatted outcomes are warehoused into OWL, which stores and adopt the relational database format. The data conversion will be done by the data transformer and finally results will be realized as stream of data. In this proposed model, the RDF vocabulary has been redesigned by adding timestamps along with incoming triples. The classes and properties are depicted in terms of the triples (Subject S, Object O and Predicate P) and are designed as OWL. Data sets are split into smaller parts for continuous updates and collect them into massive data sets so as to obtain faster insertion rates. It takes less time to process temporal, complex and multi queries in proposed system. Since timestamp is attached as one of the object in the triples, it is easy to retrieve and execute timestamp embedding queries. The proposed system is appropriate for all types of queries and proves efficiency in execution time. Application/Improvement: Temporal, complex and multi join queries are executed and evaluated for weather monitoring system.

Exposing vocabularies for soil as Linked Open Data

Standards to describe soil properties are well established, with many ISO specifications and a few international thesauri available for specific applications. Besides, in recent years, the European directive on “Infrastructure for Spatial Information in the European Community (INSPIRE)” has brought together most of the existing standards into a well defined model. However, the adoption of these standards so far has not reached the level of semantic interoperability, defined in the paper, which would facilitate the building of data services that reuse and combine data from different sources.This paper reviews standards for describing soil data and reports on the work done within the EC funded agINFRA project to apply Linked Data technologies to existing standards and data in order to improve the interoperability of soil datasets. The main result of this work is twofold. First, an RDF vocabulary for soil concepts based on the UML INSPIRE model was published. Second, a KOS (Knowledge Organization System) for soil data was published and mapped to existing relevant KOS, based on the analysis of the SISI database of the CREA of Italy. This work also has a methodological value, in that it proposes and applies a methodology to standardize metadata used in local scientific databases, a very common situation in the scientific domain. Finally, this work aims at contributing towards a wider adoption of the INSPIRE directive, by providing an RDF version of it.

A reusable ontology for primitive and complex HL7 FHIR data types.

HL7(®) FHIR(®) standard is a new standard aiming to offer more flexible interoperability mechanisms. We present a stand-alone RDF vocabulary as an OWL ontology that defines the primitive and complex data types of the FHIR framework, alongside their validation rules. We address the non-trivial questions of representing FHIR data types as RDF/OWL constructs in a coherent and complete manner. The proposed ontology can be used as a basic framework, where the complexity of a FHIR-based EHR is not required, while still maintaining semantic cohesion with an industry-based standard. It can also be the base for a complete representation of FHIR model as an ontology.

Requirements for vocabulary preservation and governance

Purpose – The paper seeks to analyze the health of the vocabulary ecosystem in terms of requirements, addressing its various stakeholders such as maintainers of linked open vocabularies, linked data providers who use those vocabularies in their data and memory institutions which, it is hoped, will eventually provide for the long-term preservation of vocabularies. Design/methodology/approach – This paper builds on requirements formulated more tersely in the DCMI generic namespace policy for RDF vocabularies. The examination of requirements for linked open vocabularies focuses primarily on property-and-class vocabularies in RDFS or OWL (sometimes called metadata element sets), with some consideration of SKOS concept schemes and Dublin Core application profiles. It also discusses lessons learned through two years of development of the linked open vocabularies (LOV), of which main features and key findings are described. Findings – Key findings about the current practices of vocabulary managers regarding metadata, policy and versioning are presented, as well as how such practices can be improved to ensure better discoverability and usability of RDF vocabularies. The paper presents new ways to assess the links and dependencies between vocabularies. It also stresses the necessity and importance of a global governance of the ecosystem in which vocabulary managers, standard bodies, and memory institutions should engage. Research limitations/implications – The current paper is focused on requirements related to a single type of vocabulary but could and should be extended to other types such as thesauri, classifications, and other semantic assets. Practical implications – Practical technical guidelines and social good practices are proposed for promotion in the Vocabulary Ecosystem (for example, by vocabulary managers). Originality/value – This paper brings together the research and action of several important actors in the vocabulary management and governance field, and is intended to be the basis of a roadmap for action presented at the Dublin Core conference of September 2013 in Lisbon (DC 2013).

Navigating the Intersection of Library Bibliographic Data and Linked Music Information Sources: A Study of the Identification of Useful Metadata Elements for Interlinking

The Metadata Vocabulary Junction project is a research endeavor that aims to help libraries and archives enhance their data through the use of Linked Data (LD). This article reports on one of the subprojects of this research, which focused on how libraries can augment access to information sources via relevant linked datasets through their RDF vocabularies (in other words, the schemas those datasets have used). One of the key tasks of the project was to find linkable elements from library bibliographic data that would allow library data to be linked with those available music information sources. The research team mapped the fields, subfields, and relator codes of the MARC format to the classes and properties of the Music Ontology, a vocabulary that has come to serve as the basis for many other application profiles for music information sources. Relevant elements in MARC records were identified and tested using a representative sample of MARC records that encompasses various genres of music. The team also studied metadata structures used by 20 digital music collections and mapped them to those MARC fields. Key fields in MARC music records that contain resources with value for LD applications were identified. The paper reveals linkability's dependency on the suitable structured and semi structured data, as well as the impact of how data has been produced by the library community. The researchers also share the results of the alignment work to achieve the goal of incorporating LD music information sources into bibliographic records through the identification of some of the metadata elements showing the most promise for interlinking.

FP-Tree based Association Rule Mining in Academic Social Networks to Refine RDF Framework and FOAF

In order to analyze large scale social networks, different strategies are being implemented. The traditional methods of data mining are getting transformed to be suitable to the requirements of the web based information available in different structured and unstructured formats. The process of web mining, a versatile methodology of data mining, involves modified mining techniques applied on documents spread across the World Wide Web. In this proposed work, the process of association rule mining is applied to Academic Social Networks, an offshoot of Social networks. This technique involves processing of profile pages of members stored in FOAF format and retrieving the association rules from the data to identify the strength of relationship amongst researchers. The RDF vocabulary, a standard format of web based identity representation is the building block of this entire framework. Traditional applications of association rule mining is referred in the context of Market Basket analysis, and its application is projected to analyze dense network and derive association patterns amongst members of the academic social network.

Modeling Social Ties with an Object Oriented Approach

With the widely usage of online social networks, people come to realize the necessity of making the social network more semantic. However, the lack of definition of connections hinders the fully applications of online social networks and transform them towards more semantic way. So in this paper, we try to overcome this problem by modeling the social tie connection in online social networks with an object-oriented approach based on extended RDF vocabulary. In our method, the connections are modeled as object entity, with attributes describing their content, and operations defining the legal manipulation upon them. The connections have inheritance relationships between them and thus form an inheritance tree. We presented our consideration in designing the object-oriented model of connection; and developed a prototype to show its advantages over the traditional approach.

Semantically-enabled business process models discovery

Business process (BP) model discovery is a pillar technique for BP model reuse. Current discovery approaches cannot deal with the functional granularity gap that exists between BP models on the one hand, and BP queries on the other hand. In addition, they focus only on the structural dimension and do not consider functional and non-functional requirements. In this paper, we present an approach for BP model discovery which resolves the above problems. We present an RDF vocabulary which captures functional and non-functional aspects in addition to the control flow perspective. Having the functional and non-functional descriptions of basic activities, we use a set of algorithms to compute those of structured activities and therefore derive different representations of the same BP model at different granularity levels. Using a set of extraction rules, we build an RDF knowledge base that can be interrogated using SPARQL.

Towards the Functional Enhancement of 3GPP Networks with Reconfiguration Capacities

Over the last decade, several wireless access systems, such as broadband WLAN and WMAN (e.g., IEEE 802.11 and 802.16), broadcast systems (e.g., DAB, DVB-T) and short-range connectivity systems (e.g., Bluetooth, UWB), have emerged to complement existing second (2G) and third (3G) generation cellular systems. The common objective is to migrate to a flexible connectivity platform that will support the disparate requirements of mobile applications in the next-generation era, commonly referred to as 4G. To achieve a versatile multi-radio and multi-protocol access from mobile devices of limited resources in 4G, the original software-radio concept has evolved into across-the-board reconfiguration, which includes not only radio-specific functionalities but supports also the dynamic modification of the entire protocol stack. The present article clarifies the fundamental aspects of reconfiguration and points out the shortcomings of current standards for describing the reconfiguration capabilities (i.e., metadata about the feasible alternative configurations) of mobile network elements. An object-oriented model for reconfiguration metadata is introduced and isomorphically mapped to an RDF vocabulary, which is used to describe reconfigurable protocol stacks as defined for UMTS/WLAN mobile devices. The associated description languages and formats are presented and evaluated with regard to their applicability and suitability for this task and the criteria for choosing one are identified and detailed. Next, the article proposes a novel generic modular architecture for reconfiguration support in 4G mobile networks and elaborates on its functional components. We investigate the integration of our logical architecture in the 3GPP mobile network architecture and illustrate the allocation of its functional elements over the logical domains of 3GPP system Release 6 and onwards. Furthermore, we show the signaling between terminal-side and network-side architecture components for software download and protocol stack reconfiguration. Finally, we summarize our experience gained from a prototype implementation, evaluate the total signaling cost, and give directions for future work.

SPARQL queries to RDFS views of Topic Maps

Both Topic Maps and RDF are popular semantic web standards designed for machine processing of web documents. Since these representations were originally created for different purposes, they have differences both in their concepts and in their data models. The Topic Map data model can be seen as an ontology for building indices over web documents, whereas RDF is a language to define arbitrary properties of web resources. Ontologies can be defined using the RDF vocabulary description language RDF-Schema (RDFS) language. RDF(S) repositories can be searched using the query language SPARQL. To make Topic Maps exposed to RDF-based tools and searchable with SPARQL, our approach is to map Topic Maps to a view expressed in RDFS. The view can be queried using SPARQL. The problem concerning efficient query processing of SPARQL queries to the rather complex RDF view of Topic Maps has been studied in detail. Our approach has been applied on searching indices to e-government services.