Querying N-Triples from an Extensible Functional DBMS
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Semantics Developer's Guide
MarkLogic Server Semantic Graph Developer’s Guide 2 MarkLogic 10 May, 2019 Last Revised: 10.0-8, October, 2021 Copyright © 2021 MarkLogic Corporation. All rights reserved. MarkLogic Server MarkLogic 10—May, 2019 Semantic Graph Developer’s Guide—Page 2 MarkLogic Server Table of Contents Table of Contents Semantic Graph Developer’s Guide 1.0 Introduction to Semantic Graphs in MarkLogic ..........................................11 1.1 Terminology ..........................................................................................................12 1.2 Linked Open Data .................................................................................................13 1.3 RDF Implementation in MarkLogic .....................................................................14 1.3.1 Using RDF in MarkLogic .........................................................................15 1.3.1.1 Storing RDF Triples in MarkLogic ...........................................17 1.3.1.2 Querying Triples .......................................................................18 1.3.2 RDF Data Model .......................................................................................20 1.3.3 Blank Node Identifiers ..............................................................................21 1.3.4 RDF Datatypes ..........................................................................................21 1.3.5 IRIs and Prefixes .......................................................................................22 1.3.5.1 IRIs ............................................................................................22 -
Binary RDF for Scalable Publishing, Exchanging and Consumption in the Web of Data
WWW 2012 – PhD Symposium April 16–20, 2012, Lyon, France Binary RDF for Scalable Publishing, Exchanging and Consumption in the Web of Data Javier D. Fernández 1;2 Supervised by: Miguel A. Martínez Prieto 1 and Claudio Gutierrez 2 1 Department of Computer Science, University of Valladolid (Spain) 2 Department of Computer Science, University of Chile (Chile) [email protected] ABSTRACT era and hence they share a document-centric view, providing The Web of Data is increasingly producing large RDF data- human-focused syntaxes, disregarding large data. sets from diverse fields of knowledge, pushing the Web to In a typical scenario within the current state-of-the-art, a data-to-data cloud. However, traditional RDF represen- efficient interchange of RDF data is limited, at most, to com- tations were inspired by a document-centric view, which pressing the verbose plain data with universal compression results in verbose/redundant data, costly to exchange and algorithms. The resultant file has no logical structure and post-process. This article discusses an ongoing doctoral the- there is no agreed way to efficiently publish such data, i.e., sis addressing efficient formats for publication, exchange and to make them (publicly) available for diverse purposes and consumption of RDF on a large scale. First, a binary serial- users. In addition, the data are hardly usable at the time of ization format for RDF, called HDT, is proposed. Then, we consumption; the consumer has to decompress the file and, focus on compressed rich-functional structures which take then, to use an appropriate external tool (e.g. -
Rdfa in XHTML: Syntax and Processing Rdfa in XHTML: Syntax and Processing
RDFa in XHTML: Syntax and Processing RDFa in XHTML: Syntax and Processing RDFa in XHTML: Syntax and Processing A collection of attributes and processing rules for extending XHTML to support RDF W3C Recommendation 14 October 2008 This version: http://www.w3.org/TR/2008/REC-rdfa-syntax-20081014 Latest version: http://www.w3.org/TR/rdfa-syntax Previous version: http://www.w3.org/TR/2008/PR-rdfa-syntax-20080904 Diff from previous version: rdfa-syntax-diff.html Editors: Ben Adida, Creative Commons [email protected] Mark Birbeck, webBackplane [email protected] Shane McCarron, Applied Testing and Technology, Inc. [email protected] Steven Pemberton, CWI Please refer to the errata for this document, which may include some normative corrections. This document is also available in these non-normative formats: PostScript version, PDF version, ZIP archive, and Gzip’d TAR archive. The English version of this specification is the only normative version. Non-normative translations may also be available. Copyright © 2007-2008 W3C® (MIT, ERCIM, Keio), All Rights Reserved. W3C liability, trademark and document use rules apply. Abstract The current Web is primarily made up of an enormous number of documents that have been created using HTML. These documents contain significant amounts of structured data, which is largely unavailable to tools and applications. When publishers can express this data more completely, and when tools can read it, a new world of user functionality becomes available, letting users transfer structured data between applications and web sites, and allowing browsing applications to improve the user experience: an event on a web page can be directly imported - 1 - How to Read this Document RDFa in XHTML: Syntax and Processing into a user’s desktop calendar; a license on a document can be detected so that users can be informed of their rights automatically; a photo’s creator, camera setting information, resolution, location and topic can be published as easily as the original photo itself, enabling structured search and sharing. -
Exercise Sheet 1
Semantic Web, SS 2017 1 Exercise Sheet 1 RDF, RDFS and Linked Data Submit your solutions until Friday, 12.5.2017, 23h00 by uploading them to ILIAS. Later submissions won't be considered. Every solution should contain the name(s), email adress(es) and registration number(s) of its (co-)editor(s). Read the slides for more submission guidelines. 1 Knowledge Representation (4pts) 1.1 Knowledge Representation Humans usually express their knowledge in natural language. Why aren't we using, e.g., English for knowledge representation and the semantic web? 1.2 Terminological vs Concrete Knowledge What is the role of terminological knowledge (e.g. Every company is an organization.), and what is the role of facts (e.g. Microsoft is an organization. Microsoft is headquartered in Redmond.) in a semantic web system? Hint: Imagine an RDF ontology that contains either only facts (describing factual knowledge: states of aairs) or constraints (describing terminological knowledge: relations between con- cepts). What could a semantic web system do with it? Semantic Web, SS 2017 2 2 RDF (10pts) RDF graphs consist of triples having a subject, a predicate and an object. Dierent syntactic notations can be used in order to serialize RDF graphs. By now you have seen the XML and the Turtle syntax of RDF. In this task we will use the Notation3 (N3) format described at http://www.w3.org/2000/10/swap/Primer. Look at the following N3 le: @prefix model: <http://example.com/model1/> . @prefix cdk: <http://example.com/chemistrydevelopmentkit/> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . -
An Introduction to RDF
An Introduction to RDF Knowledge Technologies 1 Manolis Koubarakis Acknowledgement • This presentation is based on the excellent RDF primer by the W3C available at http://www.w3.org/TR/rdf-primer/ and http://www.w3.org/2007/02/turtle/primer/ . • Much of the material in this presentation is verbatim from the above Web site. Knowledge Technologies 2 Manolis Koubarakis Presentation Outline • Basic concepts of RDF • Serialization of RDF graphs: XML/RDF and Turtle • Other Features of RDF (Containers, Collections and Reification). Knowledge Technologies 3 Manolis Koubarakis What is RDF? •TheResource Description Framework (RDF) is a data model for representing information (especially metadata) about resources in the Web. • RDF can also be used to represent information about things that can be identified on the Web, even when they cannot be directly retrieved on the Web (e.g., a book or a person). • RDF is intended for situations in which information about Web resources needs to be processed by applications, rather than being only displayed to people. Knowledge Technologies 4 Manolis Koubarakis Some History • RDF draws upon ideas from knowledge representation, artificial intelligence, and data management, including: – Semantic networks –Frames – Conceptual graphs – Logic-based knowledge representation – Relational databases • Shameless self-promotion : The closest to RDF, pre-Web knowledge representation language is Telos: John Mylopoulos, Alexander Borgida, Matthias Jarke, Manolis Koubarakis: Telos: Representing Knowledge About Information Systems. ACM Trans. Inf. Syst. 8(4): 325-362 (1990). Knowledge Technologies 5 Manolis Koubarakis The Semantic Web “Layer Cake” Knowledge Technologies 6 Manolis Koubarakis RDF Basics • RDF is based on the idea of identifying resources using Web identifiers and describing resources in terms of simple properties and property values. -
On Blank Nodes
On Blank Nodes Alejandro Mallea1, Marcelo Arenas1, Aidan Hogan2, and Axel Polleres2;3 1 Department of Computer Science, Pontificia Universidad Católica de Chile, Chile Email: {aemallea,marenas}@ing.puc.cl 2 Digital Enterprise Research Institute, National University of Ireland Galway, Ireland Email: {aidan.hogan,axel.polleres}@deri.org 3 Siemens AG Österreich, Siemensstrasse 90, 1210 Vienna, Austria Abstract. Blank nodes are defined in RDF as ‘existential variables’ in the same way that has been used before in mathematical logic. However, evidence suggests that actual usage of RDF does not follow this definition. In this paper we thor- oughly cover the issue of blank nodes, from incomplete information in database theory, over different treatments of blank nodes across the W3C stack of RDF- related standards, to empirical analysis of RDF data publicly available on the Web. We then summarize alternative approaches to the problem, weighing up advantages and disadvantages, also discussing proposals for Skolemization. 1 Introduction The Resource Description Framework (RDF) is a W3C standard for representing in- formation on the Web using a common data model [18]. Although adoption of RDF is growing (quite) fast [4, § 3], one of its core features—blank nodes—has been sometimes misunderstood, sometimes misinterpreted, and sometimes ignored by implementers, other standards, and the general Semantic Web community. This lack of consistency between the standard and its actual uses calls for attention. The standard semantics for blank nodes interprets them as existential variables, de- noting the existence of some unnamed resource. These semantics make even simple entailment checking intractable. RDF and RDFS entailment are based on simple entail- ment, and are also intractable due to blank nodes [14]. -
Common Sense Reasoning with the Semantic Web
Common Sense Reasoning with the Semantic Web Christopher C. Johnson and Push Singh MIT Summer Research Program Massachusetts Institute of Technology, Cambridge, MA 02139 [email protected], [email protected] http://groups.csail.mit.edu/dig/2005/08/Johnson-CommonSense.pdf Abstract Current HTML content on the World Wide Web has no real meaning to the computers that display the content. Rather, the content is just fodder for the human eye. This is unfortunate as in fact Web documents describe real objects and concepts, and give particular relationships between them. The goal of the World Wide Web Consortium’s (W3C) Semantic Web initiative is to formalize web content into Resource Description Framework (RDF) ontologies so that computers may reason and make decisions about content across the Web. Current W3C work has so far been concerned with creating languages in which to express formal Web ontologies and tools, but has overlooked the value and importance of implementing common sense reasoning within the Semantic Web. As Web blogging and news postings become more prominent across the Web, there will be a vast source of natural language text not represented as RDF metadata. Common sense reasoning will be needed to take full advantage of this content. In this paper we will first describe our work in converting the common sense knowledge base, ConceptNet, to RDF format and running N3 rules through the forward chaining reasoner, CWM, to further produce new concepts in ConceptNet. We will then describe an example in using ConceptNet to recommend gift ideas by analyzing the contents of a weblog. -
RDF—The Basis of the Semantic Web 3
CHAPTER RDF—The basis of the Semantic Web 3 CHAPTER OUTLINE Distributing Data across the Web ........................................................................................................... 28 Merging Data from Multiple Sources ...................................................................................................... 32 Namespaces, URIs, and Identity............................................................................................................. 33 Expressing URIs in print..........................................................................................................35 Standard namespaces .............................................................................................................37 Identifiers in the RDF Namespace........................................................................................................... 38 Higher-order Relationships .................................................................................................................... 42 Alternatives for Serialization ................................................................................................................. 44 N-Triples................................................................................................................................44 Turtle.....................................................................................................................................45 RDF/XML.............................................................................................................................................. -
Resource Description Framework Technologies in Chemistry Egon L Willighagen1* and Martin P Brändle2
Willighagen and Brändle Journal of Cheminformatics 2011, 3:15 http://www.jcheminf.com/content/3/1/15 EDITORIAL Open Access Resource description framework technologies in chemistry Egon L Willighagen1* and Martin P Brändle2 Editorial would like to thank Pfizer, Inc., who had partially The Resource Description Framework (RDF) is provid- funded the article processing charges for this Thematic ing the life sciences with new standards around data Series. Pfizer, Inc. has had no input into the content of and knowledge management. The uptake in the life the publication or the articles themselves. All articles in sciences is significantly higher than the uptake of the the series were independently prepared by the authors eXtensible Markup Language (XML) and even relational and were subjected to the journal’s standard peer review databases, as was recently shown by Splendiani et al. [1] process. Chemistry is adopting these methods too. For example, In the remainder of this editorial, we will briefly out- Murray-Rust and co-workers used RDF already in 2004 line the various RDF technologies and how they have to distribute news items where chemical structures were been used in chemistry so far. embedded using RDF Site Summary 1.0 [2]. Frey imple- mented a system which would now be referred to as an 1 Concepts electronic lab notebook (ELN) [3]. The use of the The core RDF specification was introduced by the SPARQL query language goes back to 2007 where it World Wide Web Consortium (W3C) in 1999 [6] and was used in a system to annotate crystal structures [4]. defines the foundation of the RDF technologies. -
Inscribing the Blockchain with Digital Signatures of Signed RDF Graphs. a Worked Example of a Thought Experiment
Inscribing the blockchain with digital signatures of signed RDF graphs. A worked example of a thought experiment. The thing is, ad hoc hash signatures on the blockchain carry no information linking the hash to the resource for which the hash is acting as a digital signature. The onus is on the inscriber to associate the hash with the resource via a separate communications channel, either by publishing the association directly or making use of one of the third-party inscription services that also offer a resource persistence facility – you get to describe what is signed by the hash and they store the description in a database, usually for a fee, or you can upload the resource for storage, definitely for a fee. Riccardo Cassata has a couple of technical articles that expose more of the practical details: https://blog.eternitywall.it/2016/02/16/how-to-verify-notarization/ So what's published is a hexadecimal string indistinguishable from all the others which purportedly matches the hash of Riccardo's mugshot. But which? https://tineye.com/search/ed9f8022c9af413a350ec5758cda520937feab21 What’s needed is a means of creating an inscription that is not only a signature but also a resovable reference to the resource for which it acts as a digital signature. It would be even better if it were possible to create a signature of structured information, such as that describing a social media post – especially if we could leverage off’ve the W3’s recent Activity Streams standard: https://www.w3.org/TR/activitystreams-core/ An example taken from the -
Connecting RDA and RDF Linked Data for a Wide World of Connected Possibilities
Practice Connecting RDA and RDF Linked Data for a Wide World of Connected Possibilities Ashleigh Faith & Michelle Chrzanowski Ashleigh N. Faith, MLIS is an Adjunct Instructor at the University of Pittsburgh Information School, [email protected] Michelle Chrzanowski, MLS is a Reference Librarian at the Tidewater Community College Norfolk Campus Library, [email protected] Libraries have struggled with connecting a plethora of content and the metadata stored in catalogs to patrons. Adding more value to catalogs, more tools for reference librarians, and enriched patron search, linked data is a means to connect more people with more relevant information. With the recent transition to the Resource Description and Access (RDA) cataloging standard within libraries, linking data in library databases has become a much easier project to tackle, largely because of another standard called Resource Description Framework (RDF). Both focus on resource description and both are components of linked data within the library. Tying them together is the Functional Requirements for Bibliographic Records (FRBR) conceptual framework. Acknowledging that linked data components are most likely new to many librarians, this article seeks to explain what linked data is, how RDA and RDF are connected by FRBR, and how knowledge maps may improve information access. Introduction Interest in linked data has been growing. Recently, a search of the abstract databases Scopus, Web of Science, and Google Scholar show “linked data” as a search term an average of 45,633 times from 2010 to July 2015. From January to July 2015 alone, "linked data" was searched an average of 3,573 times. It is therefore no wonder that more people are paying attention to data and how it can be linked to other data. -
Semantic Integration and Analysis of Clinical Data-1024
Semantic integration and analysis of clinical data Hong Sun, Kristof Depraetere, Jos De Roo, Boris De Vloed, Giovanni Mels, Dirk Colaert Advanced Clinical Applications Research Group, Agfa HealthCare, Gent, Belgium {hong.sun, kristof.depraetere, jos.deroo, boris.devloed, giovanni.mels, dirk.colaert }@agfa.com Abstract. There is a growing need to semantically process and integrate clinical data from different sources for Clinical Data Management and Clinical Deci- sion Support in the healthcare IT industry. In the clinical practice domain, the semantic gap between clinical information systems and domain ontologies is quite often difficult to bridge in one step. In this paper, we report our experi- ence in using a two-step formalization approach to formalize clinical data, i.e. from database schemas to local formalisms and from local formalisms to do- main (unifying) formalisms. We use N3 rules to explicitly and formally state the mapping from local ontologies to domain ontologies. The resulting data ex- pressed in domain formalisms can be integrated and analyzed, though originat- ing from very distinct sources. Practices of applying the two-step approach in the infectious disorders and cancer domains are introduced. Keywords: Semantic interoperability, N3 rules, SPARQL, formal clinical data, data integration, data analysis, clinical information system. 1 Introduction A decade ago formal semantics, the study of logic within a linguistic framework, found a new means of expression, i.e. the World Wide Web and with it the Semantic Web [1]. The Semantic Web provides additional capabilities that enable information sharing between different resources which are semantically represented. It consists of a set of standards and technologies that include a simple data model for representing information (RDF) [2], a query language for RDF (SPARQL) [3], a schema language describing RDF vocabularies (RDFS) [4], a few syntaxes to represent RDF (RDF/XML [20], N3 [19]) and a language for describing and sharing ontologies (OWL) [5].