Semantic Web: – Interoperability,Usability,Applicability

This editorial summarizes the content of the Special Issue on Quality Management of Semantic Web Assets (Data, Services and Systems) part of the Semantic Web Journal.

One of the key value propositions for knowledge graphs and semantic web technologies is fostering semantic interoperability, i.e., integrating data across different themes and domains. But why do we aim at interoperability in the first place? A common answer to this question is that each individual data source only contains partial information about some phenomenon of interest. Consequently, combining multiple diverse datasets provides a more holistic perspective and enables us to answer more complex questions, e.g., those that span between the physical sciences and the social sciences. Interestingly, while these arguments are well established and go by different names, e.g., variety in the realm of big data, we seem less clear about whether the same arguments apply on the level of schemata. Put differently, we want diverse data, but do we also want diverse schemata or a single one to rule them all?

Linked Data promises to serve as a disruptor of traditional approaches to data management and use, promoting the push from the traditional Web of documents to a Web of data. The ability for data consumers to adopt a follow your nose approach, traversing links defined within a dataset or across independently-curated datasets, is an essential feature of this new Web of Data, enabling richer knowledge retrieval thanks to synthesis across multiple sources of, and views on, inter-related datasets. But for the Web of Data to be successful, we must design novel ways of interacting with the corresponding very large amounts of complex, interlinked, multi-dimensional data throughout its management cycle. The design of user interfaces for Linked Data, and more specifically interfaces that represent the data visually, play a central role in this respect. Contributions to this special issue on Linked Data visualisation investigate different approaches to harnessing visualisation as a tool for exploratory discovery and basic-to-advanced analysis. The papers in this volume illustrate the design and construction of intuitive means for end-users to obtain new insight and gather more knowledge, as they follow links defined across datasets over the Web of Data.

Knowledge graphs are often constructed from heterogeneous data sources, using declarative rules that map them to a target ontology and materializing them into RDF. When these data sources are large, the materialization of the entire knowledge graph may be computationally expensive and not suitable for those cases where a rapid materialization is required. In this work, we propose an approach to overcome this limitation, based on the novel concept of mapping partitions. Mapping partitions are defined as groups of mapping rules that generate disjoint subsets of the knowledge graph. Each of these groups can be processed separately, reducing the total amount of memory and execution time required by the materialization process. We have included this optimization in our materialization engine Morph-KGC, and we have evaluated it over three different benchmarks. Our experimental results show that, compared with state-of-the-art techniques, the use of mapping partitions in Morph-KGC presents the following advantages: (i) it decreases significantly the time required for materialization, (ii) it reduces the maximum peak of memory used, and (iii) it scales to data sizes that other engines are not capable of processing currently.

This paper describes the Ontology of units of Measure and related concepts (OM), an OWL ontology of the domain of quantities and units of measure. OM supports making quantitative research data more explicit, so that the data can be integrated, verified and reproduced. The various options for modeling the domain are discussed. For example, physical quantities can be modeled either as classes, instances or properties. The design choices made are based on use cases from our own projects and general experience in the field. The use cases have been implemented as tools and web services. OM is compared with QUDT, another active effort for an OWL model in this domain. We note possibilities for integration of these efforts. We also discuss the role OWL plays in our approach.

Perhaps the most fundamental notion underlying the desiderata for a successful Semantic Web is Semantic Interoperability. In this context, ontologies have been more and more recognized as one of the enabling technologies. This paper defends the view that an approach which neglects the role of ontologies as reference conceptual models cannot meet the requirements for full semantic interoperability. The paper starts by offering an engineering view on ontology engineering, discussing the relation between ontologies as conceptual models and ontologies as codification artifacts. Furthermore, it discusses the importance of foundational theories and principles to the design of ontology (conceptual) modeling languages and models, emphasizing the fundamental role played by true ontological notions in this process. Finally, it elaborates on the need for proper tools to handle the complexity of ontology engineering in industrial scenarios and complex domains. These tools include ontological design patterns as well as well-founded computational environments to support ontology creation, verification and validation (via model simulation).

With the increasing amount of Linked Data published on the Web, the community has recognised the importance of the quality of such data and a number of initiatives have been undertaken to specify and evaluate Linked Data quality. However, these initiatives are characterised by a high diversity in terms of the quality aspects that they address and measure. This leads to difficulties in comparing and benchmarking evaluation results, as well as in selecting the right data source according to certain quality needs. This paper presents a quality model for Linked Data, which provides a unique terminology and reference for Linked Data quality specification and evaluation. The mentioned quality model specifies a set of quality characteristics and quality measures related to Linked Data, together with formulas for the calculation of measures. Furthermore, this paper also presents an extension of the W3C Data Quality Vocabulary that can be used to capture quality information specific to Linked Data, a Linked Data representation of the Linked Data quality model, and a use case in which the benefits of the quality model proposed in this paper are presented in a tool for Linked Data evaluation.

This paper describes an experiment exploring the hypothesis that innovative application of the Functional Requirements for Bibliographic Records (FRBR) principles can complement traditional bibliographic resource discovery systems in order to improve the user experience. A specialized service was implemented that, when given a plain list of results from a regular online catalogue, was able to process, enrich and present that list in a more relevant way for the user. This service pre-processes the records of a traditional online catalogue in order to build a semantic structure following the FRBR model. The service also explores web search features that have been revolutionizing the way users conceptualize resource discovery, such as relevance ranking and metasearching. This work was developed in the context of the TELPlus project. We processed nearly one hundred thousand bibliographic and authority records, in multiple languages, and originating from twelve European national libraries. This paper describes the architecture of the service and the main challenges faced, especially concerning the extraction and linking of the relevant FRBR entities from the bibliographic metadata produced by the libraries. The service was evaluated by end users, who filled out a questionnaire after using a traditional online catalogue and the new service, both with the same bibliographic collection. The analysis of the results supports the hypothesis that FRBR can be implemented for resource discovery in a non-intrusive way, reusing the data of any existing traditional bibliographic system.

Alignments represent correspondences between entities of two ontologies. They are produced from the ontologies by ontology matchers. In order for matchers to exchange alignments and for applications to manipulate matchers and alignments, a minimal agreement is necessary. The Alignment API provides abstractions for the notions of network of ontologies, alignments and correspondences as well as building blocks for manipulating them such as matchers, evaluators, renderers and parsers. We recall the building blocks of this API and present here the version 4 of the Alignment API through some of its new features: ontology proxys, the expressive alignment language EDOAL and evaluation primitives.

Over the past few years Semantic Web technologies have brought significant changes in the way structured data is published, shared and consumed on the Web. Emerging online applications based on the Web of Objects or Linked Open Data can use the Web as a platform to exchange and reason over semantically rich data covering any topic. Yet two-thirds of the world population is deprived of Web access and is thus deprived from applications that could have a critical impact on their life. There is a need to adapt Semantic Web technologies to put them to work “for all” in challenging contexts. This special issue describes progress made towards reaching that goal.