Towards creating knowledge out of interlinked data

The term linked data is entering into common vocabulary and, as most interests us in this instance, into the specific terminology of library and information science. The concept is complex; we can summarize it as that set of best practices required for publishing and connecting structured data on the web for use by a machine. It is an expression used to describe a method of exposing, sharing and connecting data via Uniform Resource Identifiers (URIs) on the web. With linked data, in other words, we refer to data published on the web in a format readable, interpretable and, most of all, useable by machine, whose meaning is explicitly defined by a string of words and markers. In this way we constitute a linked data network (hence linked data) belonging to a domain (which constitutes the initial context), connected in turn to other external data sets (that is, those outside of the domain), in a context of increasingly extended relationships. Next is presented the Linked Open Data cloud (LOD), which collects the open data sets available on the web, and the paradigm of its exponential growth occurring in a very brief period of time which demonstrates the level of interest that linked data has garnered in organizations and institutions of different types.

A ‘Semantic Web’ Using Linked Data for day-to-day data transfer , 2009

The term Linked Data refers to a set of best practices for publishing and connecting structured data on the Web. These best practices have been adopted by an increasing number of data providers over the last three years, leading to the creation of a global data space containing billions of assertions - the Web of Data. In this article we present the concept and technical principles of Linked Data, and situate these within the broader context of related technological developments. We describe progress to date in publishing Linked Data on the Web, review applications that have been developed to exploit the Web of Data, and map out a research agenda for the Linked Data community as it moves forward.

RSTI - ISI - Revue des Sciences et Technologies de l'Information - Série ISI : Ingénierie des Systèmes d'Information, 2018

This paper is a survey of the research topics in the field of Semantic Web, Linked Data and Web of Data. This study looks at the contributions of this research community over its first twenty years of existence. Compiling several bibliographical sources and bibliometric indicators , we identify the main research trends and we reference some of their major publications to provide an overview of that initial period. We conclude with some perspectives for the future research challenges. RÉSUMÉ. Cet article est une étude des sujets de recherche dans le domaine du Web sémantique, des données liées et du Web des données. Cette étude se penche sur les contributions de cette communauté de recherche au cours de ses vingt premières années d'existence. En compilant plusieurs sources bibliographiques et indicateurs bibliométriques, nous identifions les princi-pales tendances de la recherche et nous référencons certaines de leurs publications majeures pour donner un aperçu de cette période initiale. Nous concluons avec une discussion sur les tendances et perspectives de recherche.

Visión Electrónica, 2019

Linked Data, as a strategy of the Semantic Web, is based on application of some basic principles that contribute to the growth of the Web, thus allowing the transit of the Web of Documents to the Web of Data. Developed process by Linked Data is supported in different scenarios, which interact in order to carry out the linking of resources on the Web. Some of these scenarios present a solid technological background, while others propose challenges when they are implemented. This paper aims to identify and expose a generic abstraction of Linked Data, in order to identify problem situations that restrict Linked Data process.

2010

The world is moving from a state where there is paucity of data to one of surfeit. These data, and datasets, are normally in different datastores and of different formats. Connecting these datasets together will increase their value and help discover interesting relationships amongst them. This paper describes our experience of using Linked Data to inter-operate these different datasets, the challenges we faced, and the solutions we devised. The paper concludes with apposite design principles for using linked data to inter-operate disparate datasets.

The Semantic Web–ISWC 2010, 2010

The Web of Linked Data is characterized by linking structured data from different sources using equivalence statements, such as owl:sameAs, as well as other types of linked properties. The ontologies behind these sources, however, remain unlinked. This paper describes an extensional approach to generate alignments between these ontologies. Specifically our algorithm produces equivalence and subsumption relationships between classes from ontologies of different Linked Data sources by exploring the space of hypotheses supported by the existing equivalence statements. We are also able to generate a complementary hierarchy of derived classes within an existing ontology or generate new classes for a second source where the ontology is not as refined as the first. We demonstrate empirically our approach using Linked Data sources from the geospatial, genetics, and zoology domains. Our algorithm discovered about 800 equivalences and 29,000 subset relationships in the alignment of five source pairs from these domains. Thus, we are able to model one Linked Data source in terms of another by aligning their ontologies and understand the semantic relationships between the two sources.

A fundamental prerequisite of the Semantic Web is the existence of large amounts of meaningfully interlinked RDF data on the Web. The W3C SWEO community project Linking Open Data has made various open datasets available on the Web as RDF, and developed automated mechanisms to interlink them with RDF statements. Collectively, the datasets currently consist of over one billion triples. We believe that large scale interlinking will demonstrate the value of the Semantic Web compared to more centralized approaches such as Google Base 5. This paper outlines the work to date and describes the accompanying demonstration. A functioning Semantic Web is predicated on the availability of large amounts of data as RDF; not in isolated islands but as a Web of interlinked datasets. To date this prerequisite has not been widely met, leading to criticism of the broader endeavour and hindering the progress of developers wishing to build Semantic Web applications. Thanks to the Open Data movement, a va...

PhD Thesis - University of Manchester, 2014

It is recognised that nowadays, users interact with large amounts of data that exist in disparate forms, and are stored under different settings. Moreover, it is true that the amount of structured and un-structured data outside a single well organised data management system is expanding rapidly. To address the recent challenges of managing large amounts of potentially distributed data, the vision of a dataspace was introduced. This data management paradigm aims at reducing the complexity behind the challenges of integrating heterogeneous data sources.Recently, efforts by the Linked Data (LD) community gave rise to a Web of Data (WoD) that interweaves with the current Web of documents in a way that it is useful for data consumption by both humans and computational agents. On the WoD, datasets are structured under a common data model and published as Web resources following a simple set of guidelines that enables them to be linked with other pieces of data, as well as, to be annotated with useful meta data that help determine their semantics. The WoD is an evolving open ecosystem including specialist publishers as well as community efforts aiming at re-publishing isolated databases as LD on the WoD, and annotating them with meta data.The WoD raises new opportunities and challenges. However, currently it mostly relies on manual efforts for integrating the large amounts of heterogeneous data sources on the WoD. This dissertation makes the case that several techniques from the dataspaces research area (aiming at on-demand integration of data sources in a pay-as-you-go fashion) can support the integration of heterogeneous WoD sources. In so doing, this dissertation explores the opportunities and identifies the challenges of adapting existing pay-as-you-go data integration techniques in the context of LD. More specifically, this dissertation makes the following contributions: (1) a case-study for identifying the challenges when existing pay-as-you-go data integration techniques are applied in a setting where data sources are LD; (2) a methodology that deals with the ''schema-less'' nature of LD sources by automatically inferring a conceptual structure from a given RDF graph thus enabling downstream tasks, such as the identification of matches and the derivation of mappings, which are, both, essential for the automatic bootstrapping of a dataspace; and (3) a well-defined, principled methodology that builds on a Bayesian inference technique for reasoning under uncertainty to improve pay-as-you-go integration. Although the developed methodology is generic in being able to reason with different hypothesis, its effectiveness has only been explored on reducing the uncertain decisions made by string-based matchers during the matching stage of a dataspace system.

Lecture Notes in Business Information Processing, 2009

The last decade of research in the Web field gave a great importance to the studies about the Semantic Web. The idea of a Web of Data is now becoming more and more popular also outside of the pure scientific community. The idea of linked data is thus gaining ground and demonstrating its advantages and its opportunities in the business world. Still a lot of research is there to come.

2011

Abstract By specifying that published datasets must link to other existing datasets, the 4th linked data principle ensures a Web of data and not just a set of unconnected data islands. The authors propose in this paper the term data linking to name the problem of finding equivalent resources on the Web of linked data. In order to perform data linking, many techniques were developed, finding their roots in statistics, database, natural language processing and graph theory.

This paper provides the reader from the base to the state of art in Linked Open Data (LOD), with issues and challenges. In addition, reader will be motivated by reading the projects analysed in the information space of five major computer science areas (Intelligence, Multimedia, Sensors, File System and Library), future trends and directions in LOD.

2011

Twenty years ago Tim Berners-Lee proposed a distributed hypertext system based on standard Internet protocols. The Web that resulted fundamentally changed the ways we share information and services, both on the public Internet and within organizations. That original proposal contained the seeds of another effort that has not yet fully blossomed: a Semantic Web designed to enable computer programs to share and understand structured and semi-structured information easily.

Proceedings of the 22nd Brazilian Symposium on Multimedia and the Web - Webmedia '16, 2016

For the vision of the Semantic Web to become a reality and its benefits harnessed, data available on the Web must also be published in the form of linked data. Moreover, the quality of the abstract conceptual models behind this data, i.e., their ontology, can also have a big influence in the adoption of linked data sets and their vocabularies. In this paper, we propose FrameWeb-LD, an approach for the integration of Web-based Information Systems on the Semantic Web, which uses well-founded languages and methods for the modeling of ontologies and aids developers in publishing their application's data and services on the Web of Data.

In this chapter, an overview of the current state of the art, future trends and conceptual underpinnings of Linked Data in the field of Architecture and Construction is provided. A short brief introduction to the fundamental concepts of Linked Data and the Semantic Web is followed by practical applications in the building sector that include the use of OpenBIM information exchange standards and the creation of dynamic model extensions with external vocabularies and data sets. An introduction into harnessing the Linked Data standards for domain-specific, federated multi-models and the use of well-established query and reasoning mechanisms to address industry challenges is introduced. The chapter is concluded by a discussion of current developments and future trends.

2016

Abstract. In this paper, we present a three-level mediator based framework for linked data integration. In our approach, the mediated schema is represented by a domain ontology, which provides a conceptual representation of the application. Each relevant data source is described by a source ontology, published on the Web according to the Linked Data principles, thereby becoming part of the Web of linked data. Each source ontology is rewritten as an application ontology, whose vocabulary is restricted to be a subset of the vocabulary of the domain ontology. The three-level architecture permits dividing the mapping definition in two stages: local mappings and mediated mappings. Due to this architecture the problem of query answering can also be broken into two steps. First, the query is decomposed, using the mediated mappings, into a set of elementary sub-queries expressed in terms of the application ontologies. Then, these sub-queries are rewritten, using the local mappings, in terms...