Linked Data Principles Research Articles

An integrated Linked Building Data system: AEC industry case

Environmental assessment is a critical activity for ensuring buildings are performing according to specified requirements, and efficient, seamless exchange of building information is crucial for environmental assessment. Therefore, all those involved in built environment issues should be able to access and share not only building information but also data about products, especially environmental assessment results for the products used in building projects. Of the several approaches that have been proposed to achieve efficient information exchange, semantic web technologies are amongst the most promising due to their capability to share data and enhance interoperability between the most heterogeneous systems. This study proposes an approach that can be used to make environmental data available in the early phases of the building lifecycle. It relies on Semantic Web techniques, especially Linked Data principles, while building on emerging Building Information Modelling (BIM) technology to propose an approach that facilitates information exchange to enhance the sustainability assessment of buildings. The paper ends with an illustration of how lifecycle inventory databases can be integrated, linked to BIM software and used in exchanging environmental building data.

SCALEUS-FD: A FAIR Data Tool for Biomedical Applications.

The Semantic Web and Linked Data concepts and technologies have empowered the scientific community with solutions to take full advantage of the increasingly available distributed and heterogeneous data in distinct silos. Additionally, FAIR Data principles established guidelines for data to be Findable, Accessible, Interoperable, and Reusable, and they are gaining traction in data stewardship. However, to explore their full potential, we must be able to transform legacy solutions smoothly into the FAIR Data ecosystem. In this paper, we introduce SCALEUS-FD, a FAIR Data extension of a legacy semantic web tool successfully used for data integration and semantic annotation and enrichment. The core functionalities of the solution follow the Semantic Web and Linked Data principles, offering a FAIR REST API for machine-to-machine operations. We applied a set of metrics to evaluate its “FAIRness” and created an application scenario in the rare diseases domain.

NaLa-Search: A multimodal, interaction-based architecture for faceted search on linked open data

Mobile devices are the technological basis of computational intelligent systems, yet traditional mobile application interfaces tend to rely only on the touch modality. That said, such interfaces could improve human–computer interaction by combining diverse interaction modalities, such as visual, auditory and touch. Also, a lot of information on the Web is published under the Linked Data principles to allow people and computers to share, use and/or reuse high-quality information; however, current tools for searching for, browsing and visualising this kind of data are not fully developed. The goal of this research is to propose a novel architecture called NaLa-Search to effectively explore the Linked Open Data cloud. We present a mobile application that combines voice commands and touch for browsing and searching for such semantic information through faceted search, which is a widely used interaction scheme for exploratory search that is faithful to its richness and practical for real-world use. NaLa-Search was evaluated by real users from the clinical pharmacology domain. In this evaluation, the users had to search and navigate among the DrugBank dataset through voice commands. The evaluation results show that faceted search combined with multiple interaction modalities (e.g. speech and touch) can enhance users’ interaction with semantic knowledge bases.

A Metadata Repository for Semantic Product Lifecycle Management

Abstract Current processes for highly interdisciplinary and complex smart products rely on the support of a big variety of IT systems. At the lowest level, authoring systems are used to create digital models and engineering data objects. A multitude of data management systems which in turn have to be integrated into comprehensive Product Lifecycle Management (PLM) and Enterprise Resource Planning (ERP) solutions enable the management of this product information and engineering processes (e.g. for engineering change and release management) along the entire product lifecycle. Engineers use these information management approaches for their daily work processes like engineering change or release management. In industrial environments, several heterogeneous IT systems coexist but cannot easily be connected and thus provide critical barriers for engineering collaboration. Being able to flexible access required engineering information from these IT systems supported by a platform that provides integrated metadata repository engineering could improve engineering workflows like change management dramatically. The approach introduced in this paper describes a Metadata Repository for Semantic Product Lifecycle Management (SP2IDER) which provides an additional information management layer that uses an IT architecture based on a minimalistic core to view and access data from a multitude of IT source systems. Instead of storing data from these source systems in SP2IDER, open web technologies like Linked Data principles and JSON-LD allow providing real-time access to the source systems.

Answering SPARQL queries on the web of data through zero-knowledge link traversal

Link traversal has emerged as a SPARQL query processing method that exploits the Linked Data principles to dynamically discover data relevant for answering a query by dereferencing online Web resources (URIs) at query execution time. While several approaches for such a lookup-based query evaluation method have been proposed, there exists no analysis of the types (patterns) of queries that can be directly answered on the Web of Data through a "zero-knowledge" approach, i.e., without accessing local or remote endpoints and without a-priori knowledge of available data sources. In this paper, we first provide a method for examining if a SPARQL query can be answered through zero-knowledge link traversal and analyse a large corpus of real SPARQL query logs for finding the frequency and distribution of answerable and non-answerable query patterns. Subsequently, we provide an algorithm for transforming answerable queries to SPARQL-LD queries that bypass the endpoints, as well as a method to estimate their evaluation cost which can be useful for deciding on the query execution strategy to follow. We report experimental results about the efficiency of the transformed queries and discuss the benefits and the limitations of this query evaluation method.

Implementation-independent function reuse

Functions are essential building blocks of information retrieval and information management. However, efforts implementing these functions are fragmented: one function has multiple implementations, within specific development contexts. This inhibits reuse: metadata of functions and associated implementations need to be found across various search interfaces, and implementation integration requires human interpretation and manual adjustments. An approach is needed, independent of development context and enabling description and exploration of functions and (automatic) instantiation of associated implementations. In this paper, after collecting scenarios and deriving corresponding requirements, we (i) propose an approach that facilitates functions’ description, publication, and exploration by modeling and publishing abstract function descriptions and their links to concrete implementations; and (ii) enable implementations’ automatic instantiation by exploiting those published descriptions. This way, we can link to existing implementations, and provide a uniform detailed search interface across development contexts. The proposed model (the Function Ontology) and the publication method following the Linked Data principles using standards, are deemed sufficient for this task, and are extensible to new development contexts. The proposed set of tools (the Function Hub and Function Handler) are shown to fulfill the collected requirements, and the user evaluation proves them being perceived as a valuable asset during software retrieval. Our work thus improves developer experience for function exploration and implementation instantiation.

The Future of Authority Control: Issues and Trends in the Linked Data Environment

Within the past few years, the calls for transforming library data into linked data have become more and more frequent. The purpose of this study is to discuss the future of authority control in the linked data environment. Even though we may not have answers to all the questions, but one thing is clear – the authority control concept and process as we know it in the MARC-based legacy environment will not meet the requirements of linked data. The future of authority control lies in following closely the linked data principles.

Large-scale Semantic Integration of Linked Data

A large number of published datasets (or sources) that follow Linked Data principles is currently available and this number grows rapidly. However, the major target of Linked Data, i.e., linking and integration, is not easy to achieve. In general, information integration is difficult, because (a) datasets are produced, kept, or managed by different organizations using different models, schemas, or formats, (b) the same real-world entities or relationships are referred with different URIs or names and in different natural languages,<?brk?>(c) datasets usually contain complementary information, (d) datasets can contain data that are erroneous, out-of-date, or conflicting, (e) datasets even about the same domain may follow different conceptualizations of the domain, (f) everything can change (e.g., schemas, data) as time passes. This article surveys the work that has been done in the area of Linked Data integration, it identifies the main actors and use cases, it analyzes and factorizes the integration process according to various dimensions, and it discusses the methods that are used in each step. Emphasis is given on methods that can be used for integrating several datasets. Based on this analysis, the article concludes with directions that are worth further research.

Supporting integrated care with a flexible data management framework built upon Linked Data, HL7 FHIR and ontologies.

In this paper we present the methodology and decisions behind an implementation of a telehealth data management framework, aiming to support integrated care services for chronic and multimorbid patients. The framework leverages an OWL ontology, built upon HL7 FHIR resources, to provide storage and representation of semantically enriched EHR data following Linked Data principles. This is presented along with the realization of the persistent storage solution and communication web services that allow the management of EHR data, ensuring the validity and integrity of the exchanged patient data as self-describing ontology instances. The framework concentrates on flexibility and reusability, which is addressed by regarding the aforementioned ontology as a single point of change. This solution has been implemented in the scope of the EU project WELCOME for managing data in a telemonitoring system for patients with COPD and co-morbidities and was also successfully deployed for the INLIFE EU project with minimal effort. The results of the two applications suggest it can be adopted and properly adapted in a series of integrated care scenarios with minimal effort.

Including widespread geometry schemas into Linked Data-based BIM applied to built heritage

A reliable data exchange – often including geometry-related data – between stakeholders is crucial in construction projects. In this regard, data exchange frameworks built on Linked Data principles are very promising for combining disparate data sets. However, existing proposals to combine geometry and Linked Data either demand dedicated applications or support only a limited number of common geometry schemas. If any existing geometry schema could be used in a Linked Data context, error-prone geometry conversions are avoided and stakeholders do not need to invest in new geometry engines. In this paper, the applicability of Resource Description Framework (RDF) literals for including a wide variety of existing geometry schemas is studied and applied in a built heritage context. The uniform linking pattern and related terminology of the Ontology for Managing Geometry are used to implement this approach. Subsequently, the File Ontology for Geometry formats and Geometry Metadata Ontology are developed to ease the reuse of linked geometry descriptions. The effectiveness of the entire data structure is demonstrated in a built heritage case study project. The receiving party is able to create successfully a coordinated view – using a demo web application – on shared, but disparate, RDF data sets containing geometry descriptions.

An Overview of the Current State of Linked and Open Data in Cataloging

Linked Open Data (LOD) is a core Semantic Web technology that makes knowledge and information spaces of different knowledge domains manageable, reusable, shareable, exchangeable, and interoperable. The LOD approach achieves this through the provision of services for describing, indexing, organizing, and retrievingknowledge artifacts and making them available for quick consumption and publication. Thisis also alignedwith the role and objective of traditional library cataloging. Owing to this link, majorlibraries of the world are transferring their bibliographic metadata to the LOD landscape. Some developments in this direction include the replacement of Anglo-American Cataloging Rules 2nd Edition by the Resource Description and Access (RDA) and the trend towards the wideradoption of BIBFRAME 2.0. An interestingand related development in this respect arethe discussions among knowledge resources managers and library community on the possibility of enriching bibliographic metadata with socially curated or user-generated content. The popularity of Linked Open Data and its benefit to librarians and knowledge management professionals warrant a comprehensive survey of the subject. Althoughseveral reviews and survey articles on the application of Linked Data principles to cataloging have appeared in literature, a generic yet holistic review of the current state of Linked and Open Data in cataloging is missing. To fill the gap, the authors have collected recent literature (2014–18) on the current state of Linked Open Data in cataloging to identify research trends, challenges, and opportunities in this area and, in addition, to understand the potential of socially curated metadata in cataloging mainlyin the realm of the Web of Data. To the best of the authors’ knowledge, this review article is the first of its kind that holistically treats the subject of cataloging in the Linked and Open Data environment. Some of the findings of the review are: Linked and Open Data is becoming the mainstream trend in library cataloging especially in the major libraries and research projects of the world; with the emergence of Linked Open Vocabularies (LOV), the bibliographic metadata is becoming more meaningful and reusable; and, finally, enriching bibliographic metadata with user-generated content is gaining momentum.Conclusions drawn from the study include the need for a focus on the quality of catalogued knowledge and the reduction of the barriers to the publication and consumption of such knowledge, and the attention on the part of library community to the learning from the successful adoption of LOD in other application domains and contributing collaboratively to the global scale activity of cataloging.

Integration of Web APIs and Linked Data Using SPARQL Micro-Services—Application to Biodiversity Use Cases

In recent years, Web APIs have become a de facto standard for exchanging machinereadable data on the Web. Despite this success, however, they often fail in making resource descriptions interoperable due to the fact that they rely on proprietary vocabularies that lack formal semantics. The Linked Data principles similarly seek the massive publication of data on the Web, yet with the specific goal of ensuring semantic interoperability. Given their complementary goals, it is commonly admitted that cross-fertilization could stem from the automatic combination of Linked Data and Web APIs. Towards this goal, in this paper we leverage the micro-service architectural principles to define a SPARQL Micro-Service architecture, aimed at querying Web APIs using SPARQL. A SPARQL micro-service is a lightweight SPARQL endpoint that provides access to a small, resource-centric, virtual graph. In this context, we argue that full SPARQL Query expressiveness can be supported efficiently without jeopardizing servers availability. Furthermore, we demonstrate how this architecture can be used to dynamically assign dereferenceable URIs to Web API resources that do not have URIs beforehand, thus literally “bringing” Web APIs into the Web of Data. We believe that the emergence of an ecosystem of SPARQL micro-services published by independent providers would enable Linked Data-based applications to easily glean pieces of data from a wealth of distributed, scalable, and reliable services. We describe a working prototype implementation and we finally illustrate the use of SPARQL micro-services in the context of two real-life use cases related to the biodiversity domain, developed in collaboration with the French National Museum of Natural History.

A linked open data representation of patents registered in the US from 2005\u20132017

Patents are widely used to protect intellectual property and a measure of innovation output. Each year, the USPTO grants over patents to individuals and companies all over the world. In fact, there were more than patent grants issued in the US in . However, accessing, searching and analyzing those patents is often still cumbersome and inefficient. To overcome those problems, Google indexes patents and converts them to Extensible Markup Language (XML) files using Optical Character Recognition (OCR) techniques. In this article, we take this idea one step further and provide semantically rich, machine-readable patents using the Linked Data principles. We have converted the data spanning years i.e. from XML to Resource Description Framework (RDF) format, conforming to the Linked Data principles and made them publicly available for re-use. This data can be integrated with other data sources in order to further simplify use cases such as trend analysis, structured patent search & exploration and societal progress measurements. We describe the conversion, publishing, interlinking process along with several use cases for the USPTO Linked Patent data.

Conversion of the English-Xhosa Dictionary for Nurses to a Linguistic Linked Data Framework

The English-Xhosa Dictionary for Nurses (EXDN) is a bilingual, unidirectional printed dictionary in the public domain, with English and isiXhosa as the language pair. By extending the digitisation efforts of EXDN from a human-readable digital object to a machine-readable state, using Resource Description Framework (RDF) as the data model, semantically interoperable structured data can be created, thus enabling EXDN’s data to be reused, aggregated and integrated with other language resources, where it can serve as a potential aid in the development of future language resources for isiXhosa, an under-resourced language in South Africa. The methodological guidelines for the construction of a Linguistic Linked Data framework (LLDF) for a lexicographic resource, as applied to EXDN, are described, where an LLDF can be defined as a framework: (1) which describes data in RDF, (2) using a model designed for the representation of linguistic information, (3) which adheres to Linked Data principles, and (4) which supports versioning, allowing for change. The result is a bidirectional lexicographic resource, previously bounded and static, now unbounded and evolving, with the ability to extend to multilingualism.

The Semantic Student: Using Knowledge Modeling Activities to Enhance Enquiry-Based Group Learning in Engineering Education.

This paper argues that training engineering students in basic knowledge modeling techniques, using linked data principles, and semantic Web tools - within an enquiry-based group learning environment - enables them to enhance their domain knowledge, and their meta-cognitive skills. Knowledge modeling skills are in keeping with the principles of Universal Design for instruction. Learners are empowered with the regulation of cognition as they become more aware of their own development. This semantic student approach was trialed with a group of 3rd year Computer Engineering Students taking a module on computer architecture. An enquiry-based group learning activity was developed to help learners meet selected module learning outcomes. Learners were required to use semantic feature analysis and linked data principles to create a visual model of their knowledge structure. Results show that overall student attainment was increased when knowledge modeling activities were included as part of the learning process. A recommendation for practice to incorporate knowledge modeling as a learning strategy within an overall engineering curriculum framework is described. This can be achieved using semantic Web technologies such as semantic wikis and linked data tools.

Ontology assessment based on linked data principles

PurposeThe purpose of this paper is to evaluate ontologies with respect to the linked data principles. This paper presents a concrete interpretation of the four linked data principles applied to ontologies, along with an implementation that automatically detects violations of these principles and fixes them (semi-automatically). The implementation is applied to a number of state-of-the-art ontologies.Design/methodology/approachBased on a precise and detailed interpretation of the linked data principles in the context of ontologies (to become as reusable as possible), the authors propose a set of algorithms to assess ontologies according to the four linked data principles along with means to implement them using a Java/Jena framework. All ontology elements are extracted and examined taking into account particular cases, such as blank nodes and literals. The authors also provide propositions to fix some of the detected anomalies.FindingsThe experimental results are consistent with the proven quality of popular ontologies of the linked data cloud because these ontologies obtained good scores from the linked data validator tool.Originality/valueThe proposed approach and its implementation takes into account the assessment of the four linked data principles and propose means to correct the detected anomalies in the assessed data sets, whereas most LD validator tools focus on the evaluation of principle 2 (URI dereferenceability) and principle 3 (RDF validation); additionally, they do not tackle the issue of fixing detected errors.

Land and nutrition data in the Land Portal and the Global Nutrition Report: a gap exploration report

GODAN Action supports data users, producers and intermediaries to effectively engage with open data and maximise its potential for impact in the agriculture and nutrition sectors. In particular, we work to strengthen capacity, to promote common standards and best practice, and to improve how we measure impact. This gap analysis report is the third in a series which has examined gaps in data standards. The first version of the report examined gaps in agriculture and food data (Pesce, Kayumbi, Tennison, Mey, and Zervas: 2016). A second version (Pesce, Tennison, Dodds and Zervas: 2017) examined the situation in the area of data standards for weather data (and closely related geospatial data), and particularly focused on weather data for use in farm management services. This third version focuses on data standardisation gaps in specific use cases of aggregation of land data and nutrition data around indicators: the Land Portal and the Global Nutrition Report. The report starts with a review of the relevant types of data for these use cases, then illustrates similarities between the two projects and similar standardisation gaps, and then moves to more specific challenges for the two individual projects. The Land Portal (LP) gathers information from a broad range of land-related data and information providers. It is organised and visualised in ways that are intuitive and usable for researchers, private sector actors and policy makers at global and local levels. The information provided can strengthen research, advocacy, and policy making efforts by enabling a better understanding of land governance issues affecting various countries and regions. The Global Nutrition Report (GNR) is a comprehensive narrative on global and country-level nutrition. GNR produces the Report annually and aggregates a wealth of nutrition and nutrition-related data from a wide range of sources. This data underpins the report itself as well as being used to produce a range of supplementary materials, including country, regional, and sub-regional profiles and data visualisation tools. The main conclusions drawn from the report are that The two use cases present many similarities. They both aggregate data from secondary sources, already partly normalised by global agencies; they both aggregate data around specific indicators; they aggregate from datasets with a similar structure (indicator, country, year, value). The identified gaps in data standardisation are very similar. The names of countries and regions in data sources are not standardised or they are standardised according to different conventions; the names of the variables do not follow any convention; indicators are represented by strings and may change over the years (both their names and the measurement methods). With reference to our data standard assessment criteria, the few standards used by the data sources (country naming conventions, value ranges, units of measurement) in both cases are not open and not very usable. The situation is different when it comes to the way the two projects re-publish the data: the GNR normalises values around some conventions, while the LP re-publishes everything according to Linked Data principles, and uses published vocabularies.

An Unsupervised Approach for Determining Link Specifications

This article describes how the Linked Open Data Cloud project allows data providers to publish structured data on the web according to the Linked Data principles. In this context, several link discovery frameworks have been developed for connecting entities contained in knowledge bases. In order to achieve a high effectiveness for the link discovery task, a suitable link configuration is required to specify the similarity conditions. Unfortunately, such configurations are specified manually; which makes the link discovery task tedious and more difficult for the users. In this article, the authors address this drawback by proposing a novel approach for the automatic determination of link specifications. The proposed approach is based on a neural network model to combine a set of existing metrics into a compound one. The authors evaluate the effectiveness of the proposed approach in three experiments using real data sets from the LOD Cloud. In addition, the proposed approach is compared against link specifications approaches to show that it outperforms them in most experiments.

Evaluating the quality of the LOD cloud: An empirical investigation

The increasing adoption of the Linked Data principles brought with it an unprecedented dimension to the Web, transforming the traditional Web of Documents to a vibrant information ecosystem, also known as the Web of Data. This transformation, however, does not come without any pain points. Similar to the Web of Documents, the Web of Data is heterogenous in terms of the various domains it covers. The diversity of the Web of Data is also reflected in its quality. Data quality impacts the fitness for use of the data for the application at hand, and choosing the right dataset is often a challenge for data consumers. In this quantitative empirical survey, we analyse 130 datasets (≈ 3.7 billion quads), extracted from the latest Linked Open Data Cloud using 27 Linked Data quality metrics, and provide insights into the current quality conformance. Furthermore, we publish the quality metadata for each assessed dataset as Linked Data, using the Dataset Quality Vocabulary (daQ). This metadata is then used by data consumers to search and filter possible datasets based on different quality criteria. Thereafter, based on our empirical study, we present an aggregated view of the Linked Data quality in general. Finally, using the results obtained from the quality assessment empirical study, we use the Principal Component Analysis (PCA) test in order to identify the key quality indicators that can give us sufficient information about a dataset’s quality.

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.