N3logic: a Logical Framework for the World Wide Web 3 Order Logic Presents Problems Such As Paradox Traps
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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. -
Linked Data Overview and Usage in Social Networks
Linked Data Overview and Usage in Social Networks Gustavo G. Valdez Technische Universitat Berlin Email: project [email protected] Abstract—This paper intends to introduce the principles of Webpages, also possibly reference any Object or Concept (or Linked Data, show some possible uses in Social Networks, even relationships of concepts/objects). advantages and disadvantages of using it, aswell as presenting The second one combines the unique identification of the an example application of Linked Data to the field of social networks. first with a well known retrieval mechanism (HTTP), enabling this URIs to be looked up via the HTTP protocol. I. INTRODUCTION The third principle tackles the problem of using the same The web is a very good source of human-readable informa- document standards, in order to have scalability and interop- tion that has improved our daily life in several areas. By using erability. This is done by having a standard, the Resource De- rich text and hyperlinks, it made our access to information scription Framewok (RDF), which will be explained in section something more active rather than passive. But the web was III-A. This standards are very useful to provide resources that made for humans and not for machines, even though today are machine-readable and are identified by a URI. a lot of the acesses to the web are made by machines. This The fourth principle basically advocates that hyperlinks has lead to the search for adding structure, so that data is should be used not only to link webpages, but also to link more machine-readable. -
A Visual Notation for the Integrated Representation of OWL Ontologies
A Visual Notation for the Integrated Representation of OWL Ontologies Stefan Negru1 and Steffen Lohmann2 1Faculty of Computer Science, Alexandru Ioan Cuza University, General Berthelot 16, 700483 Iasi, Romania 2Institute for Visualization and Interactive Systems (VIS), Universit¨atsstraße 38, 70569 Stuttgart, Germany [email protected], [email protected] Keywords: Ontology Visualization, Visual Notation, OWL, Semantic Web, Knowledge Visualization, Ontologies. Abstract: The paper presents a visual notation for the Web Ontology Language (OWL) providing an integrated view on the classes and individuals of ontologies. The classes are displayed as circles, with the size of each circle representing its connectivity in the ontology. The individuals are represented as sections in the circles so that it is immediately clear from the visualization how many individuals the classes contain. The notation can be used to visualize the property relations of either the classes (conceptual layer) or of selected individuals (integrated layer), while certain elements are always shown for a better understanding. It requires only a small number of graphical elements and the resulting visualizations are comparatively compact. Yet, the notation is comprehensive, as it defines graphical representations for all OWL elements that can be reasonably visualized. The applicability of the notation is illustrated by the example of the Friend of a Friend (FOAF) ontology. 1 INTRODUCTION reasoning. Even though it provides great means to de- scribe and integrate information on the Web, its text- The Web of Data has attracted large interest for both based representation is difficult to understand for av- data publishers and consumers in the last years. -
RDF Query Languages Need Support for Graph Properties
RDF Query Languages Need Support for Graph Properties Renzo Angles1, Claudio Gutierrez1, and Jonathan Hayes1,2 1 Dept. of Computer Science, Universidad de Chile 2 Dept. of Computer Science, Technische Universit¨at Darmstadt, Germany {rangles,cgutierr,jhayes}@dcc.uchile.cl Abstract. This short paper discusses the need to include into RDF query languages the ability to directly query graph properties from RDF data. We study the support that current RDF query languages give to these features, to conclude that they are currently not supported. We propose a set of basic graph properties that should be added to RDF query languages and provide evidence for this view. 1 Introduction One of the main features of the Resource Description Framework (RDF) is its ability to interconnect information resources, resulting in a graph-like structure for which connectivity is a central notion [GLMB98]. As we will argue, basic concepts of graph theory such as degree, path, and diameter play an important role for applications that involve RDF querying. Considering the fact that the data model influences the set of operations that should be provided by a query language [HBEV04], it follows the need for graph operations support in RDF query languages. For example, the query “all relatives of degree 1 of Alice”, submitted to a genealogy database, amounts to retrieving the nodes adjacent to a resource. The query “are suspects A and B related?”, submitted to a police database, asks for any path connecting these resources in the (RDF) graph that is stored in this database. The query “what is the Erd˝osnumber of Alberto Mendelzon”, submitted to (a RDF version of) DBLP, asks simply for the length of the shortest path between the nodes representing Erd˝osand Mendelzon. -
Mapping Between Digital Identity Ontologies Through SISM
Mapping between Digital Identity Ontologies through SISM Matthew Rowe The OAK Group, Department of Computer Science, University of Sheffield, Regent Court, 211 Portobello Street, Sheffield S1 4DP, UK [email protected] Abstract. Various ontologies are available defining the semantics of dig- ital identity information. Due to the rise in use of lowercase semantics, such ontologies are now used to add metadata to digital identity informa- tion within web pages. However concepts exist in these ontologies which are related and must be mapped together in order to enhance machine- readability of identity information on the web. This paper presents the Social identity Schema Mapping (SISM) vocabulary which contains a set of mappings between related concepts in distinct digital identity ontolo- gies using OWL and SKOS mapping constructs. Key words: Semantic Web, Social Web, SKOS, OWL, FOAF, SIOC, PIMO, NCO, Microformats 1 Introduction The semantic web provides a web of machine-readable data. Ontologies form a vital component of the semantic web by providing conceptualisations of domains of knowledge which can then be used to provide a common understanding of some domain. A basic ontology contains a vocabulary of concepts and definitions of the relationships between those concepts. An agent reading a concept from an ontology can look up the concept and discover its properties and characteristics, therefore interpreting how it fits into that particular domain. Due to the great number of ontologies it is common for related concepts to be defined in separate ontologies, these concepts must be identified and mapped together. Web technologies such as Microformats, eRDF and RDFa have allowed web developers to encode lowercase semantics within XHTML pages. -
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#> . -
Microformats the Next (Small) Thing on the Semantic Web?
Standards Editor: Jim Whitehead • [email protected] Microformats The Next (Small) Thing on the Semantic Web? Rohit Khare • CommerceNet “Designed for humans first and machines second, microformats are a set of simple, open data formats built upon existing and widely adopted standards.” — Microformats.org hen we speak of the “evolution of the is precisely encoding the great variety of person- Web,” it might actually be more appropri- al, professional, and genealogical relationships W ate to speak of “intelligent design” — we between people and organizations. By contrast, can actually point to a living, breathing, and an accidental challenge is that any blogger with actively involved Creator of the Web. We can even some knowledge of HTML can add microformat consult Tim Berners-Lee’s stated goals for the markup to a text-input form, but uploading an “promised land,” dubbed the Semantic Web. Few external file dedicated to machine-readable use presume we could reach those objectives by ran- remains forbiddingly complex with most blog- domly hacking existing Web standards and hop- ging tools. ing that “natural selection” by authors, software So, although any intelligent designer ought to developers, and readers would ensure powerful be able to rely on the long-established facility of enough abstractions for it. file transfer to publish the “right” model of a social Indeed, the elegant and painstakingly inter- network, the path of least resistance might favor locked edifice of technologies, including RDF, adding one of a handful of fixed tags to an exist- XML, and query languages is now growing pow- ing indirect form — the “blogroll” of hyperlinks to erful enough to attack massive information chal- other people’s sites. -
From FOAF to English: Linguistic Contribution to Web Semantics
From FOAF to English: Linguistic Contribution to Web Semantics Max Silberztein Université de Franche-Comté [email protected] Abstract which sentence to produce. This article presents the linguistic component of such a system. This paper presents a linguistic module capable of generating a set of English sentences that 2 The linguistic framework correspond to a Resource Description Framework (RDF) statement; I discuss how a Based on the principles of linguistic approaches to generator can control the linguistic module, as generation laid out by Danlos (1987), I have used well as the various limitations of a pure the NooJ1 platform to construct a set of linguistic linguistic framework. resources that parses a sequence of RDF statements and produces a corresponding set of English 1 Introduction sentences. NooJ allows linguists to construct structured sets of linguistic resources (“modules”) Automatic Natural Language Generation Software in the form of dictionaries and grammars2 to aims to express information stored in a knowledge formalize a large gamut of linguistic phenomena: database as a Natural Language text. The orthography and spelling, inflectional, derivational information at the source typically consists of a and agglutinative morphology, local and structural series of simple atomic statements, such as “John syntax, transformational syntax, lexical and owns a house”, “Mary lives in Manchester”, “Peter predicative semantics. All linguistic analyses are is Ann’s cousin”. These statements are usually performed sequentially by adding and/or removing stored in a knowledge database or ontology in a linguistic annotations to/from a Text Annotation formal notation such as Prolog (e.g. Structure (TAS); at each level of the analysis, each “Own(John,House)”) or XML. -
Semantic Interaction with Music Content Using FOAF
Semantic Interaction with Music Content using FOAF Oscar` Celma1, Miquel Ram´ırez1, and Perfecto Herrera1 Music Technology Group, Institut Universitari de l’Audiovisual Universitat Pompeu Fabra Ocata 1, 08003 Barcelona, Spain. {ocelma, mramirez, pherrera}@iua.upf.es http://www.iua.upf.es/mtg Abstract. SIMAC (Semantic Interaction with Music Audio Contents) is an European Commission project (IST-2.3.1.7, Semantic-based knowl- edge systems) which aims to develop a set of prototypes to describe, semi-automatically, music audio content. SIMAC is about music meta- data, about what you can say of a piece of music, on what is hidden in a music file, in a collection of music files, and in the collective knowledge of a community of music lovers. This document proposes to enhance/extend the FOAF definition to model user musical tastes. One of the goals of the project is to explore music content discovery, based on both user profiling and content-based descriptions. 1 Introduction The main goal of SIMAC1 is doing research on semantic descriptors of music contents, in order to use them, by means of a set of prototypes, for providing song collection exploration, retrieval and recommendation services. These services are meant for “home” users, music content producers and distributors and academic users. One special feature is that these descriptions are composed by semantic descriptors. Music will be tagged using a language close to the user’s own way of describing its contents —moving the focus from low-level to higher-level (i.e. semantic) descriptions. SIMAC is about music metadata. We assume that metadata is all what one can say about a single music piece or a collection of music pieces. -
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.