Benchmarking the Efficiency of RDF-Based Access for Blockchain
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Basic Querying with SPARQL
Basic Querying with SPARQL Andrew Weidner Metadata Services Coordinator SPARQL SPARQL SPARQL SPARQL SPARQL Protocol SPARQL SPARQL Protocol And SPARQL SPARQL Protocol And RDF SPARQL SPARQL Protocol And RDF Query SPARQL SPARQL Protocol And RDF Query Language SPARQL SPARQL Protocol And RDF Query Language SPARQL Query SPARQL Query Update SPARQL Query Update - Insert triples SPARQL Query Update - Insert triples - Delete triples SPARQL Query Update - Insert triples - Delete triples - Create graphs SPARQL Query Update - Insert triples - Delete triples - Create graphs - Drop graphs Query RDF Triples Query RDF Triples Triple Store Query RDF Triples Triple Store Data Dump Query RDF Triples Triple Store Data Dump Subject – Predicate – Object Query Subject – Predicate – Object ?s ?p ?o Query Dog HasName Cocoa Subject – Predicate – Object ?s ?p ?o Query Cocoa HasPhoto ------- Subject – Predicate – Object ?s ?p ?o Query HasURL http://bit.ly/1GYVyIX Subject – Predicate – Object ?s ?p ?o Query ?s ?p ?o Query SELECT ?s ?p ?o Query SELECT * ?s ?p ?o Query SELECT * WHERE ?s ?p ?o Query SELECT * WHERE { ?s ?p ?o } Query select * WhErE { ?spiderman ?plays ?oboe } http://deathbattle.wikia.com/wiki/Spider-Man http://www.mmimports.com/wp-content/uploads/2014/04/used-oboe.jpg Query SELECT * WHERE { ?s ?p ?o } Query SELECT * WHERE { ?s ?p ?o } Query SELECT * WHERE { ?s ?p ?o } Query SELECT * WHERE { ?s ?p ?o } LIMIT 10 SELECT * WHERE { ?s ?p ?o } LIMIT 10 http://dbpedia.org/snorql SELECT * WHERE { ?s ?p ?o } LIMIT 10 http://dbpedia.org/snorql SELECT * WHERE { ?s -
Mapping Spatiotemporal Data to RDF: a SPARQL Endpoint for Brussels
International Journal of Geo-Information Article Mapping Spatiotemporal Data to RDF: A SPARQL Endpoint for Brussels Alejandro Vaisman 1, * and Kevin Chentout 2 1 Instituto Tecnológico de Buenos Aires, Buenos Aires 1424, Argentina 2 Sopra Banking Software, Avenue de Tevuren 226, B-1150 Brussels, Belgium * Correspondence: [email protected]; Tel.: +54-11-3457-4864 Received: 20 June 2019; Accepted: 7 August 2019; Published: 10 August 2019 Abstract: This paper describes how a platform for publishing and querying linked open data for the Brussels Capital region in Belgium is built. Data are provided as relational tables or XML documents and are mapped into the RDF data model using R2RML, a standard language that allows defining customized mappings from relational databases to RDF datasets. In this work, data are spatiotemporal in nature; therefore, R2RML must be adapted to allow producing spatiotemporal Linked Open Data.Data generated in this way are used to populate a SPARQL endpoint, where queries are submitted and the result can be displayed on a map. This endpoint is implemented using Strabon, a spatiotemporal RDF triple store built by extending the RDF store Sesame. The first part of the paper describes how R2RML is adapted to allow producing spatial RDF data and to support XML data sources. These techniques are then used to map data about cultural events and public transport in Brussels into RDF. Spatial data are stored in the form of stRDF triples, the format required by Strabon. In addition, the endpoint is enriched with external data obtained from the Linked Open Data Cloud, from sites like DBpedia, Geonames, and LinkedGeoData, to provide context for analysis. -
Validating RDF Data Using Shapes
83 Validating RDF data using Shapes a Jose Emilio Labra Gayo a University of Oviedo, Spain Abstract RDF forms the keystone of the Semantic Web as it enables a simple and powerful knowledge representation graph based data model that can also facilitate integration between heterogeneous sources of information. RDF based applications are usually accompanied with SPARQL stores which enable to efficiently manage and query RDF data. In spite of its well known benefits, the adoption of RDF in practice by web programmers is still lacking and SPARQL stores are usually deployed without proper documentation and quality assurance. However, the producers of RDF data usually know the implicit schema of the data they are generating, but they don't do it traditionally. In the last years, two technologies have been developed to describe and validate RDF content using the term shape: Shape Expressions (ShEx) and Shapes Constraint Language (SHACL). We will present a motivation for their appearance and compare them, as well as some applications and tools that have been developed. Keywords RDF, ShEx, SHACL, Validating, Data quality, Semantic web 1. Introduction In the tutorial we will present an overview of both RDF is a flexible knowledge and describe some challenges and future work [4] representation language based of graphs which has been successfully adopted in semantic web 2. Acknowledgements applications. In this tutorial we will describe two languages that have recently been proposed for This work has been partially funded by the RDF validation: Shape Expressions (ShEx) and Spanish Ministry of Economy, Industry and Shapes Constraint Language (SHACL).ShEx was Competitiveness, project: TIN2017-88877-R proposed as a concise and intuitive language for describing RDF data in 2014 [1]. -
SAQE: Practical Privacy-Preserving Approximate Query Processing for Data Federations
SAQE: Practical Privacy-Preserving Approximate Query Processing for Data Federations Johes Bater Yongjoo Park Xi He Northwestern University University of Illinois (UIUC) University of Waterloo [email protected] [email protected] [email protected] Xiao Wang Jennie Rogers Northwestern University Northwestern University [email protected] [email protected] ABSTRACT 1. INTRODUCTION A private data federation enables clients to query the union of data Querying the union of multiple private data stores is challeng- from multiple data providers without revealing any extra private ing due to the need to compute over the combined datasets without information to the client or any other data providers. Unfortu- data providers disclosing their secret query inputs to anyone. Here, nately, this strong end-to-end privacy guarantee requires crypto- a client issues a query against the union of these private records graphic protocols that incur a significant performance overhead as and he or she receives the output of their query over this shared high as 1,000× compared to executing the same query in the clear. data. Presently, systems of this kind use a trusted third party to se- As a result, private data federations are impractical for common curely query the union of multiple private datastores. For example, database workloads. This gap reveals the following key challenge some large hospitals in the Chicago area offer services for a cer- in a private data federation: offering significantly fast and accurate tain percentage of the residents; if we can query the union of these query answers without compromising strong end-to-end privacy. databases, it may serve as invaluable resources for accurate diag- To address this challenge, we propose SAQE, the Secure Ap- nosis, informed immunization, timely epidemic control, and so on. -
Computational Integrity for Outsourced Execution of SPARQL Queries
Computational integrity for outsourced execution of SPARQL queries Serge Morel Student number: 01407289 Supervisors: Prof. dr. ir. Ruben Verborgh, Dr. ir. Miel Vander Sande Counsellors: Ir. Ruben Taelman, Joachim Van Herwegen Master's dissertation submitted in order to obtain the academic degree of Master of Science in Computer Science Engineering Academic year 2018-2019 Computational integrity for outsourced execution of SPARQL queries Serge Morel Student number: 01407289 Supervisors: Prof. dr. ir. Ruben Verborgh, Dr. ir. Miel Vander Sande Counsellors: Ir. Ruben Taelman, Joachim Van Herwegen Master's dissertation submitted in order to obtain the academic degree of Master of Science in Computer Science Engineering Academic year 2018-2019 iii c Ghent University The author(s) gives (give) permission to make this master dissertation available for consultation and to copy parts of this master dissertation for personal use. In the case of any other use, the copyright terms have to be respected, in particular with regard to the obligation to state expressly the source when quoting results from this master dissertation. August 16, 2019 Acknowledgements The topic of this thesis concerns a rather novel and academic concept. Its research area has incredibly talented people working on a very promising technology. Understanding the core principles behind proof systems proved to be quite difficult, but I am strongly convinced that it is a thing of the future. Just like the often highly-praised artificial intelligence technology, I feel that verifiable computation will become very useful in the future. I would like to thank Joachim Van Herwegen and Ruben Taelman for steering me in the right direction and reviewing my work quickly and intensively. -
Introduction Vocabulary an Excerpt of a Dbpedia Dataset
D2K Master Information Integration Université Paris Saclay Practical session (2): SPARQL Sources: http://liris.cnrs.fr/~pchampin/2015/udos/tuto/#id1 https://www.w3.org/TR/2013/REC-sparql11-query-20130321/ Introduction For this practical session, we will use the DBPedia SPARQL access point, and to access it, we will use the Yasgui online client. By default, Yasgui (http://yasgui.org/) is configured to query DBPedia (http://wiki.dbpedia.org/), which is appropriate for our tutorial, but keep in mind that: - Yasgui is not linked to DBpedia, it can be used with any SPARQL access point; - DBPedia is not related to Yasgui, it can be queried with any SPARQL compliant client (in fact any HTTP client that is not very configurable). Vocabulary An excerpt of a dbpedia dataset The vocabulary of DBPedia is very large, but in this tutorial we will only need the IRIs below. foaf:name Propriété Nom d’une personne (entre autre) dbo:birthDate Propriété Date de naissance d’une personne dbo:birthPlace Propriété Lieu de naissance d’une personne dbo:deathDate Propriété Date de décès d’une personne dbo:deathPlace Propriété Lieu de décès d’une personne dbo:country Propriété Pays auquel un lieu appartient dbo:mayor Propriété Maire d’une ville dbr:Digne-les-Bains Instance La ville de Digne les bains dbr:France Instance La France -1- /!\ Warning: IRIs are case-sensitive. Exercises 1. Display the IRIs of all Dignois of origin (people born in Digne-les-Bains) Graph Pattern Answer: PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> PREFIX owl: <http://www.w3.org/2002/07/owl#> PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> PREFIX foaf: <http://xmlns.com/foaf/0.1/> PREFIX skos: <http://www.w3.org/2004/02/skos/core#> PREFIX dc: <http://purl.org/dc/elements/1.1/> PREFIX dbo: <http://dbpedia.org/ontology/> PREFIX dbr: <http://dbpedia.org/resource/> PREFIX db: <http://dbpedia.org/> SELECT * WHERE { ?p dbo:birthPlace dbr:Digne-les-Bains . -
Supporting SPARQL Update Queries in RDF-XML Integration *
Supporting SPARQL Update Queries in RDF-XML Integration * Nikos Bikakis1 † Chrisa Tsinaraki2 Ioannis Stavrakantonakis3 4 Stavros Christodoulakis 1 NTU Athens & R.C. ATHENA, Greece 2 EU Joint Research Center, Italy 3 STI, University of Innsbruck, Austria 4 Technical University of Crete, Greece Abstract. The Web of Data encourages organizations and companies to publish their data according to the Linked Data practices and offer SPARQL endpoints. On the other hand, the dominant standard for information exchange is XML. The SPARQL2XQuery Framework focuses on the automatic translation of SPARQL queries in XQuery expressions in order to access XML data across the Web. In this paper, we outline our ongoing work on supporting update queries in the RDF–XML integration scenario. Keywords: SPARQL2XQuery, SPARQL to XQuery, XML Schema to OWL, SPARQL update, XQuery Update, SPARQL 1.1. 1 Introduction The SPARQL2XQuery Framework, that we have previously developed [6], aims to bridge the heterogeneity issues that arise in the consumption of XML-based sources within Semantic Web. In our working scenario, mappings between RDF/S–OWL and XML sources are automatically derived or manually specified. Using these mappings, the SPARQL queries are translated on the fly into XQuery expressions, which access the XML data. Therefore, the current version of SPARQL2XQuery provides read-only access to XML data. In this paper, we outline our ongoing work on extending the SPARQL2XQuery Framework towards supporting SPARQL update queries. Both SPARQL and XQuery have recently standardized their update operation seman- tics in the SPARQL 1.1 and XQuery Update Facility, respectively. We have studied the correspondences between the update operations of these query languages, and we de- scribe the extension of our mapping model and the SPARQL-to-XQuery translation algorithm towards supporting SPARQL update queries. -
WIN: an Efficient Data Placement Strategy for Parallel XML Databases
WIN : An Efficient Data Placement Strategy for Parallel XML Databases Nan Tang† Guoren Wang‡ Jeffrey Xu Yu† Kam-Fai Wong† Ge Yu‡ † Department of SE & EM, The Chinese University of Hong Kong, Hong Kong, China ‡ College of Information Science and Engineering, Northeastern University, Shenyang, China {ntang, yu, kfwong}se.cuhk.edu.hk {wanggr, yuge}@mail.neu.edu.cn Abstract graph-based. Distinct from them, XML employs a tree struc- The basic idea behind parallel database systems is to ture. Conventional data placement strategies in perform operations in parallel to reduce the response RDBMSs and OODBMSs cannot serve XML data well. time and improve the system throughput. Data place- Semistructured data involve nested structures; there ment is a key factor on the overall performance of are much intricacy and redundancy when represent- parallel systems. XML is semistructured data, tradi- ing XML as relations. Data placement strategies in tional data placement strategies cannot serve it well. RDBMSs cannot, therefore, well solve the data place- In this paper, we present the concept of intermediary ment problem of XML data. Although graph partition node INode, and propose a novel workload-aware data algorithms in OODBMSs can be applied to tree parti- placement WIN to effectively decluster XML data, to tion problems, the key relationships between tree nodes obtain high intra query parallelism. The extensive ex- such as ancestor-descendant or sibling cannot be clearly periments show that the speedup and scaleup perfor- denoted on graph. Hence data placement strategies mance of WIN outperforms the previous strategies. for OODBMSs cannot well adapt to XML data either. -
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(19) TZZ¥ ¥¥Z_T (11) EP 3 267 330 A1 (12) EUROPEAN PATENT APPLICATION (43) Date of publication: (51) Int Cl.: 10.01.2018 Bulletin 2018/02 G06F 17/30 (2006.01) (21) Application number: 16187202.3 (22) Date of filing: 05.09.2016 (84) Designated Contracting States: (72) Inventors: AL AT BE BG CH CY CZ DE DK EE ES FI FR GB • Abolhassani, Neda GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO Athens, GA Georgia 30605 (US) PL PT RO RS SE SI SK SM TR • Sheausan Tung, Teresa Designated Extension States: San Jose, CA California 95120 (US) BA ME • Gomadam, Karthik Designated Validation States: San Jose, CA California 95112 (US) MA MD (74) Representative: Müller-Boré & Partner (30) Priority: 07.07.2016 US 201662359547 P Patentanwälte PartG mbB 03.08.2016 US 201615227605 Friedenheimer Brücke 21 80639 München (DE) (71) Applicant: Accenture Global Solutions Limited Dublin 4 (IE) (54) QUERY REWRITING IN A RELATIONAL DATA HARMONIZATION FRAMEWORK (57) A query rewriting processor (processor) analyz- an SQL query). The processor may then pass the rela- es database semantic models (e.g., RDF knowledge tional database query to another system or process (e.g., graphs) that capture the interconnections (e.g., foreign a data virtualization layer) for execution against the indi- and primary key links to other tables) present in a rela- vidual relational databases. In this manner, the processor tional database. The processor generates an enriched automatically translates queries for information about the model query given an initial model query (e.g., a SPARQL relational database structure to a corresponding or query) against the semantic model. -
Querying Distributed RDF Data Sources with SPARQL
Querying Distributed RDF Data Sources with SPARQL Bastian Quilitz and Ulf Leser Humboldt-Universit¨at zu Berlin {quilitz,leser}@informatik.hu-berlin.de Abstract. Integrated access to multiple distributed and autonomous RDF data sources is a key challenge for many semantic web applications. As a reaction to this challenge, SPARQL, the W3C Recommendation for an RDF query language, supports querying of multiple RDF graphs. However, the current standard does not provide transparent query fed- eration, which makes query formulation hard and lengthy. Furthermore, current implementations of SPARQL load all RDF graphs mentioned in a query to the local machine. This usually incurs a large overhead in network traffic, and sometimes is simply impossible for technical or le- gal reasons. To overcome these problems we present DARQ, an engine for federated SPARQL queries. DARQ provides transparent query ac- cess to multiple SPARQL services, i.e., it gives the user the impression to query one single RDF graph despite the real data being distributed on the web. A service description language enables the query engine to decompose a query into sub-queries, each of which can be answered by an individual service. DARQ also uses query rewriting and cost-based query optimization to speed-up query execution. Experiments show that these optimizations significantly improve query performance even when only a very limited amount of statistical information is available. DARQ is available under GPL License at http://darq.sf.net/. 1 Introduction Many semantic web applications require the integration of data from distributed, autonomous data sources. Until recently it was rather difficult to access and query data in such a setting because there was no standard query language or interface. -
SPARQL Query Processing with Conventional Relational Database Systems
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by e-Prints Soton SPARQL query processing with conventional relational database systems Steve Harris IAM, University of Southampton, UK [email protected] Abstract. This paper describes an evolution of the 3store RDF storage system, extended to provide a SPARQL query interface and informed by lessons learned in the area of scalable RDF storage. 1 Introduction The previous versions of the 3store [1] RDF triplestore were optimised to pro- vide RDQL [2] (and to a lesser extent OKBC [3]) query services, and had no efficient internal representation of the language and datatype extensions from RDF 2004 [4]. This revision of the 3store software adds support for the SPARQL [5] query language, RDF datatype and language support. Some of the representation choices made in the implementation of the previous versions of 3store made efficient support for SPARQL queries difficult. Therefore, a new underlying rep- resentation for the RDF statements was required, as well as a new query en- gine capable of supporting the additional features of SPARQL over RDQL and OKBC. 2 Related Work The SPARQL query language is still at an early stage of standardisation, but there are already other implementations. 2.1 Federate Federate [6] is a relational database gateway, which maps RDF queries to existing database structures. Its goal is for compatibility with existing relational database systems, rather than as a native RDF storage and querying engine. However, it shares the approach of pushing as much processing down into the database engine as possible, though the algorithms employed are necessarily different. -
Profiting from Kitties on Ethereum: Leveraging Blockchain RDF Data with SANSA
Profiting from Kitties on Ethereum: Leveraging Blockchain RDF Data with SANSA Damien Graux1, Gezim Sejdiu2, Hajira Jabeen2, Jens Lehmann1;2, Danning Sui3, Dominik Muhs3 and Johannes Pfeffer3 1 Fraunhofer IAIS, Germany fdamien.graux,[email protected] 2 Smart Data Analytics, University of Bonn, Germany fsejdiu,jabeen,[email protected] 3 Alethio [email protected] fdanning.sui,[email protected] Abstract. In this poster, we will present attendees how the recent state- of-the-art Semantic Web tool SANSA could be used to tackle blockchain specific challenges. In particular, the poster will focus on the use case of CryptoKitties: a popular Ethereum-based online game where users are able to trade virtual kitty pets in a secure way. 1 Introduction During the recent years, the interest of the research community for blockchain technologies has raised up since the Bitcoin white paper published by Nakamoto [4]. Indeed, several applications either practical or theoretical have been made, for instance with crypto-currencies or with secured exchanges of data. More specifically, several blockchain systems have been designed, each one having their own set of properties, for example Ethereum [6] {further described in Section2{ which provides access to so-called smart-contracts. Recently, Mukhopadhyay et al. surveyed major crypto-currencies in [3]. In parallel to ongoing blockchain development, the research community has focused on the possibilities offered by the Semantic Web such as designing efficient data management systems, dealing with large and distributed knowledge RDF graphs. As a consequence, recently, some studies have started to connect the Semantic Web world with the blockchain one, see for example the study of English et al.