Linked Data Applications Research Articles

The Role of ISBD in the Linked Data Environment

The article discusses the use of International Standard for Bibliographic Description (ISBD) in linked data application profiles and mappings to other bibliographic element sets including UNIMARC (UNIversal MARC), MARC 21, and Resource Description and Access (RDA), establishing ISBD's support for hierarchical relationships between fine-grained properties for resource attributes and coarser-grained aggregations for end-user displays of data triples, and interoperability of metadata derived from different schema. Separation of ISBD punctuation from element properties allows its use in text-based displays while accommodating innovative ways of presenting record-level sets of linked data. The article concludes with a discussion of the issues facing ISBD in maintaining a role in the future library linked data environment.

Leveraging the web of data via linked widgets

Machine-readable datasets that have increasingly become available in open formats in recent years have great potential as a foundation for innovative applications and services. Linked Data in particular-a set of best practices for publishing and connecting structured data on the Web-has facilitated significant progress in evolving the Web of documents into a Web of Data. However, although this concept has opened up many opportunities for data sharing and collaboration, integrating data is still a challenging task that requires considerable technical expertise and a profound understanding of the underlying datasets. In this paper, we introduce a novel approach to provide knowledge workers with the necessary tools to leverage the fast growing Linked Data Cloud by creating semantic-aware dataflow processes. To this end, we introduce the “Linked Widget” concept as an enhancement of standard Web Widgets. These widgets are based on a semantic data model that facilitates powerful mechanisms for gathering, processing, integration, and visualization of data in a user-friendly Mashup environment. By allowing knowledge workers to easily create complex Linked Data applications in an adhoc manner, our approach should contribute towards reducing existing barriers of Linked Data adoption.

API-centric Linked Data integration: The Open PHACTS Discovery Platform case study

Data integration is a key challenge faced in pharmacology where there are numerous heterogeneous databases spanning multiple domains (e.g. chemistry and biology). To address this challenge, the Open PHACTS consortium has developed the Open PHACTS Discovery Platform that leverages Linked Data to provide integrated access to pharmacology databases. Between its launch in April 2013 and March 2014, the platform has been accessed over 13.5 million times and has multiple applications that integrate with it. In this work, we discuss how Application Programming Interfaces can extend the classical Linked Data Application Architecture to facilitate data integration. Additionally, we show how the Open PHACTS Discovery Platform implements this extended architecture.

Contextual information retrieval in research articles: Semantic publishing tools for the research community

In recent years, the dramatic increase in academic research publications has gained significant research attention. Research has been carried out exploring novel ways of providing information services using this research content. However, the task of extracting meaningful information from research documents remains a challenge. This paper presents our research work on developing intelligent information systems that exploit online article databases. We present in this paper, a linked data application which uses a new semantic publishing model for providing value added information services for the research community. The paper presents a conceptual framework for modelling contexts associated with sentences in research articles and discusses the Sentence Context Ontology, which is used to convert the information extracted from research documents into machine-understandable data. The paper reports supervised learning experiments carried out using conditional probabilistic models for achieving automatic context identification. The paper also describes a Semantic Web Application that provides various citation context based information services.

Api-Centric Linked Data Integration: The Open Phacts Discovery Platform Case Study

Data integration is a key challenge faced in pharmacology where there are numerous heterogenous databases spanning multiple domains (e.g. chemistry and biology). To address this challenge, the Open PHACTS consortium has developed the Open PHACTS Discovery Platform that leverages Linked Data to provide integrated access to pharmacology databases. Between its launch in April 2013 and March 2014, the platform has been accessed over 13.5 million times and has multiple applications that integrate with it. In this work, we discuss how Application Programming Interfaces can extend the classical Linked Data Application Architecture to facilitate data integration. Additionally, we show how the Open PHACTS Discovery Platform implements this extended architecture.

Pundit: augmenting web contents with semantics

Scholars are using the Web every day to search, read, collaborate, and ultimately do their research. While some of the basic activities that the scholars do, such as reading and writing papers, are already well supported in the digital world, some essential scholarly primitives, such as annotation, augmentation, contextualiza- tion, and externalization, do not yet have clear support in terms of software tools. What scholars ultimately do during their research activity is to iteratively and collaboratively create new knowledge. With the advent of the Digital Humanities, we now have the opportunity—and technology—to capture at least a part of this knowledge and make it available as machine-processable data so to be better explorable and discoverable. In this paper, we present and discuss Pundit: a novel semantic annotation tool that enables scholars to collect, annotate, and contextualize Web resources. Deep-linking is used in conjunction with an RDF- based data model to allow granular selection of content (e.g. text excerpts, image fragments). Pundit aims at enabling scholars to produce meaningful machine- readable data that captures the semantics of their annotations. By providing a customizable annotation environment, where domain specific vocabularies can be loaded, and easy ways of integrating with existing Web archives or libraries, Pundit enables users to publish their annotations and collaboratively build a semantic graph. Such a graph can be consumed via HTTP APIs and standard SPARQL, thus allowing existing Linked Data applications to easily work with the data and Web clients in general to build specific visualizations.

An information-centric and REST-based approach for EPC Information Services

Radio Frequency Identification (RFID) techniques are considered relevant building blocks for the Internet of Things. The interoperability across different RFID software and hardware infrastructures is a key requirement for achieving effective and wide-scale Internet of Thing deployments. In this context, the EPC Information Service (EPCIS) is a set of standard specifications for sharing RFID-related data (i.e., EPC events) both within and across enterprises. Although the EPCIS specifies a set of HTTP and Web Service interfaces for querying and adding EPC events, interoperability and easiness of use is hindered by the fact that client applications should be aware of the repositories that are authoritative for one or more given queries and links among related events are not explicitly represented in response messages. In this paper we argue that, by leveraging emerging REST and Linked Data paradigms, EPC events can be handled as a graph of globally-addressable information resources that can be navigated, queried, and aggregated through a uniform interface and seamlessly across organization domains. To validate this approach, we have developed a prototype that exposes the EPCIS interfaces as a set of REST APIs. The prototype implementation exploits the information modeling and management capabilities provided by a framework, called InterDataNet (IDN), that we conceived and developed to ease the realization of the Web of Data and Linked Data applications.

Distributed RDFS Reasoning Over Structured Overlay Networks

In this paper, we study the problem of distributed RDFS reasoning over structured overlay networks. Distributed RDFS reasoning is essential for providing the functionality that Semantic Web and Linked Data applications require. Our goal is to present various inference techniques for RDFS reasoning in a distributed environment, and analyze them both theoretically and experimentally. The reasoning methods we present are based on bottom-up and top-down techniques and have been implemented on top of the distributed hash table Bamboo. Our algorithms range from forward and backward chaining ones to rewriting algorithms based on magic sets. We formally prove the correctness of the algorithms and study the time-space trade-off they exhibit analytically and experimentally in a local cluster.

Exchanging Data amongst Linked Data applications

The goal of data exchange is to populate the data model of a target application using data that come from one or more source applications. It is common to address data exchange building on correspondences that are transformed into executable mappings. The problem that we address in this article is how to generate executable mappings in the context of Linked Data applications, that is, applications whose data models are semantic-web ontologies. In the literature, there are many proposals to generate executable mappings. Most of them focus on relational or nested-relational data models, which cannot be applied to our context; unfortunately, the few proposals that focus on ontologies have important drawbacks, namely: they solely work on a subset of taxonomies, they require the target data model to be pre-populated or they interpret correspondences in isolation, not to mention the proposals that actually require the user to handcraft the executable mappings. In this article, we present MostoDE, a new automated proposal to generate SPARQL executable mappings in the context of Linked Data applications. Its salient features are that it does not have any of the previous drawbacks, it is computationally tractable and it has been validated using a series of experiments that prove that it is very efficient and effective in practice.

Mapping subjectivity: performing people-centered vocabulary alignment

This paper describes a mapping of linked data vocabularies in the area of person-related information. Aligning vocabulary terms may help curb the problem of property proliferation that occurs in linked data environments. It also facilitates the process of choosing semantics for vocabulary extensions and integration in the context of linked data applications. Although a work in progress, this investigation would provide support for semantic integration and for knowledge sharing and reuse in the area of personal information representation. It also offers an opportunity to reflect on a new generation of knowledge organization systems such as linked data vocabularies that have started to populate the web and are converging with new representation models and discovery tools in libraries and other cultural heritage institutions.

Combining Linked Data and knowledge engineering best practices to design a lightweight role ontology

Defining roles of agents i.e., people, organisations, etc. is required in various Semantic Web applications, including access control, knowledge management and skill repository. So far, many theoretical discussions have taken place on the nature of roles and how to represent them. In this paper, we present how we implemented a lightweight OWL-DL ontology that allows to represent roles and their relations to agents. We especially focus on the various steps for choosing a well-founded model that is compatible with the general design principle of creating and consuming lightweight and easily re-usable ontology components for the Semantic Web. Our criteria to assess the “beauty” of an ontology component, in particular, are derived from practical requirements that are typical to Linked Data applications. Hence, our modeling proposal follows an original approach that bridges a gap between the Linked Data philosophy and more theoretical issues of ontology engineering. We also describe a use-case in which this ontology has been used, demonstrating in practice the benefits of our model for maintaining, browsing and querying Linked Data.

Non-functional Aspects of Information Integration and Research for the Web Science

Abstract Web Science is emerging as an interdisciplinary field that views the Web as a relevant source of information to be analysed for diverse scientific purposes. Semantic and linked data techniques and standards have been used to integrate existing Web information developing e-research e_orts. Web applications and sources have to publish enriched information and data models, which are then matched and aligned. Some aspects of this integration are related with the evolutionary tracking, trustiness and plurality of the information available for e-science research. These aspects need to be modeled independently of the information and data sources of the research discipline. Here we provide an integrative ontology that enables to model such non-functional, informational aspects, to integrate information sources from enriched linked data applications. Finally we describe an application case of information research in the e-culture field.