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LOD bibliography

Vision/General idea

  1. Linked Data: Evolving the Web into a Global Data Space (1st edition). Synthesis Lectures on the Semantic Web: Theory and Technology, 1:1, 1-136, 2011. Morgan & Claypool. Tom Heath and Christian Bizer.
  2. STI's Semantiv Summit: Every two years STI International will hold a Semantic Summit organized by the STI Fellows for the STI Board and selected Junior STI members. STI Semantic Summits will be intellectually, socially, and geographically stimulating and will address a small number of open scientific and domain or industry challenges of strategic importance to STI and to the Semantic Technology Community. They will be forward looking and will attempt to better understand the challenges and to set directions for STI Members, STI, and the Semantic Technology Community. The 2011 STI Semantic Summit, our inaugural event, is limited to 50 invitation-only participants. It will take place over 3 days starting at noon July 6, 2011 and end at noon July 8, 2011 and will consist of highly interactive sessions that will engage all participants. With the exception of a small number of invited talks, sessions will be dominated by short presentations and animated discussions. The Summit will not be a conference or a presentation of research results. The STI Executive Board and the STI Fellows have initially selected the following themes:
    -Social Semantics
    -Linked Data: What Next? Or Future the Semantic Web
    -Processing Linked Data for Applications: Requirements and Scenarios
    -Strategic Future of LOD: making it work
    -Semantic Web and LOD applications
    -Services and semantics on mobile platforms
    -Linked data services and applications: E-Government, social networking, …
    -Computation, storage, and management aspects
    -Data management at scale: storage, search, inference, data integration, …
    -Reasoning / Problem Solving over LOD
    -Role of services and semantics in LOD applications
    -Semantics in Cloud Computing
  3. Linked Open Vocabularies
    Welcome to LOV, your entry point to the growing ecosystem of linked open vocabularies (RDFS or OWL ontologies) used in the Linked Data Cloud. Here you will find vocabularies listed and individually described by metadata, classified by vocabulary spaces, interlinked using the dedicated vocabulary VOAF.

LOD full-fledged systems/servers

See an overview here

  1. D2R Server – Publishing Relational Databases on the Semantic Web Poster
    Christian Bizer, Richard Cyganiaks
    Poster In ISWC '06
    Abstract. D2R Server is a tool for publishing the content of relational databases on the Semantic Web. Database content is mapped to RDF by a declarative mapping which specifies how resources are identified and how property values are generated from database content. Based on this mapping, D2R Server allowsWeb agents to retrieve RDF and XHTML representations of resources and to query non-RDF databases using the SPARQL query language over the SPARQL protocol. The generated representations are richly interlinked on RDF and XHTML level in order to enable browsers and crawlers to navigate database content.
  2. Virtuoso: an innovative enterprise grade multi-model data server for agile enterprises & individuals. It delivers an unrivaled platform agnostic solution for data management, access, and integration.
    The unique hybrid server architecture of Virtuoso enables it to offer traditionally distinct server functionality within a single product offering that covers the following areas: (a) Relational Data Management, (b) RDF Data Management, (c) XML Data Management, (d) Free Text Content Management & Full Text Indexing, (e) Document Web Server, (f) Linked Data Server, (g) Web Application Server, (h) Web Services Deployment (SOAP or REST).
    Check the relevant articles and white papers.
  3. Oracle: ORACLE FEATURE OVERVIEW, Oracle Database 11g Semantic Technologies, Semantic Technologies in Oracle
  4. Triplify – Light-Weight Linked Data Publication from Relational Databases
    Sören Auer, Sebastian Dietzold, Jens Lehmann,Sebastian Hellmann, David Aumueller
    In WWW '09
    Abstract. In this paper we present Triplify, a simplistic but e ective approach to publish Linked Data from relational databases. Triplify is based on mapping HTTP-URI requests onto relational database queries. Triplify transforms the resulting relations into RDF statements and publishes the data on the Web in various RDF serializations, in particular as Linked Data. The rationale for developing Triplify is that the largest part of information on the Web is already stored in structured form, often as data contained in relational databases, but usually published by Web applications only as HTML mixing structure, layout and content. In order to reveal the pure structured information behind the current Web, we have implemented Triplify as a lightweight software component, which can be easily integrated into and deployed by the numerous, widely installed Web applications. Our approach includes a method for publishing update logs to enable incremental crawling of linked data sources. Triplify is complemented by a library of con gurations for common relational schemata and a REST-enabled data source registry. Triplify con gurations containing mappings are provided for many popular Web applications, including osCommerce, WordPress, Drupal, Gallery, and phpBB. We will show that despite its light-weight architecture Triplify is usable to publish very large datasets, such as 160GB of geo data from the OpenStreetMap project.

Triple store benchmarking

  1. Triple Store Evaluation, Analysis Report
    Technical Report of Revelytix, Inc.
  2. Triple Store Evaluation, Performance Testing Methodology
    Technical Report of Revelytix, Inc.

SPARQL

  1. The Fundamentals of iSPARQL: A Virtual Triple Approach For Similarity-Based Semantic Web Tasks,
    Christoph Kiefer, Abraham Bernstein, and Markus Stocker.
    In ISWC'07.
    Abstract. This research explores three SPARQL-based techniques to solve Semantic Web tasks that often require similarity measures, such as semantic data integration, ontology mapping, and Semantic Web service matchmaking. Our aim is to see how far it is possible to integrate cus- tomized similarity functions (CSF) into SPARQL to achieve good results for these tasks. Our first approach exploits virtual triples calling property functions to establish virtual relations among resources under compari- son; the second approach uses extension functions to filter out resources that do not meet the requested similarity criteria; finally, our third tech- nique applies new solution modifiers to post-process a SPARQL solution sequence. The semantics of the three approaches are formally elaborated and discussed. We close the paper with a demonstration of the usefulness of our iSPARQL framework in the context of a data integration and an ontology mapping experiment.
  2. Virtuoso - SPARQL and Scalable Inference on Demand
    Abstract. This paper discusses integrating inference capabilities into OpenLink Virtuosos SPARQL implementation. Our goal is to do inference at run time and on demand wheneverpossible, instead of materializing entailed facts ahead of demand. In an open web scenario,facts are liable to change, to be retracted, to be contradictory and to be malicious. Therefore,heavy investment in materializing consequences for a very large body of likely questionable facts is in our view not advisable. In the same spirit, we support partial query evaluation, so as to return possibly incomplete results within a fixed response time window. We present Virtuoso’s run time implementation of owl:sameAs, inferred identity based on inverse functional properties, generic SPARQL extensions for arbitrary transitive subqueries and partial query evaluation. As future work, we suggest ways of generalizing these features for support of arbitrary backward and forward chaining rules.

Link discovery/co-reference tools

  1. A Framework for Semantic Link Discovery over Relational Data,
    Oktie Hassanzadeh, Anastasios Kementsietsidis, Lipyeow Lim, Renée J. Miller, Min Wang.
    In CIKM'09.
    Abstract. Discovering links between different data items in a single data source or across different data sources is a challenging problem faced by many information systems today. In particular, the recent Linking Open Data (LOD) community project has highlighted the paramount importance of establishing semantic links among web data sources. Currently, LOD sources provide billions of RDF triples, but only millions of links between data sources. Many of these data sources are published using tools that operate over relational data stored in a standard RDBMS. In this paper, we present a framework for discovery of semantic links from relational data. Our framework is based on declarative specification of linkage requirements by a user. We illustrate the use of our framework using several link dis- covery algorithms on a real world scenario. Our framework allows data publishers to easily find and publish high-quality links to other data sources, and therefore could significantly enhance the value of the data in the next generation of web.
  2. Discovering and Maintaining Links on the Web of Data, Julius Volz, Christian Bizer, Martin Gaedke, Georgi Kobilarov. International Semantic Web Conference (ISWC2009), Westfields, USA, October 2009.
    Abstract. The Web of Data is built upon two simple ideas: Employ the RDF data model to publish structured data on the Web and to create explicit data links between entities within different data sources. This pa- per presents the Silk – Linking Framework, a toolkit for discovering and maintaining data links between Web data sources. Silk consists of three components: 1. A link discovery engine, which computes links between data sources based on a declarative specification of the conditions that entities must fulfill in order to be interlinked; 2. A tool for evaluating the generated data links in order to fine-tune the linking specification; 3. A protocol for maintaining data links between continuously changing data sources. The protocol allows data sources to exchange both linksets as well as detailed change information and enables continuous link recom- putation. The interplay of all the components is demonstrated within a life science use case.

Experience papers on publishing LOD from already established data sources

  1. Data.dcs: converting legacy data into linked data, Matthew Rowe and Fabio Ciravegna. In Proceedings of Linked Data on the Web Workshop, World Wide Web Conference 2010, Raleigh, North Carolina, USA.
    *Abstract". Data.dcs is a project intended to produce Linked Data de- scribing the University of Sheffield’s Department of Com- puter Science. At present the department’s web site con- tains important legacy data describing people, publications and research groups. This data is distributed and is pro- vided in heterogeneous formats (e.g. HTML documents, RSS feeds), making it hard for machines to make sense of such data and query it. This paper presents an ap- proach to convert such legacy data from its current form into a machine-readable representation which is linked into the Web of Linked Data. The approach describes the triplifi- cation of legacy data, coreference resolution and interlinking with external linked datasets.
  2. Greek Open Data in the Age of Linked Data: A Demonstration of LOD Internationalization
    Charalampos Bratsas, Spyros Alexiou, Dimitris Kontokostas, Ioannis Parapontis, Ioannis Antoniou, George Metakides
    In WebSci'11.
    Abstract. This paper presents the first steps towards a Greek Linked Open Data (LOD) cloud, initially as a collection of exposed interlinked datasets and a Greek dbpedia core hub. It is a joint effort to become part of the wider, global linked data cloud and aims to contribute in the overall cloud informa- tional value. During the project and while forming and en- riching the cloud we actually addressed effectively the wider issue of non-Latin language characters both in resource nam- ing and in SPARQL queries. We propose a method to re-solve that issue which is applicable to all Languages with Non-Latin characters.
  1. Bringing Relational Databases into the Semantic Web: A Survey
    Dimitrios-Emmanuel Spanos, Periklis Stavrou and Nikolas Mitrou
    In Semantic Web Journal
    Abstract.Relational databases are considered one of the most popular storage solutions for various kinds of data and they have been recognized as a key factor in generating huge amounts of data for SemanticWeb applications. Ontologies, on the other hand,are one of the key concepts and main vehicle of knowledge in the Semantic Web research area. The problem of bridging the gap between relational databases and ontologies has attracted the interest of the SemanticWeb community, even from the early years of its existence and is commonly referred to as the database-to-ontology mapping problem. However, this term has been used interchangeably for referring to two distinct problems: namely, the creation of an ontology from an existing database instance and the discovery of mappings between an existing database instance and an existing ontology. In this paper, we clearly define these two problems and present the motivation, benefits, challenges and solutions for each one of them. We attempt to gather the most notable approaches proposed so far in the literature, present them concisely in tabular format and group them under a classification scheme. We finally explore the perspectives and future research steps for a seamless and meaningful integration of databases into the Semantic Web.

Evolution

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