Linked Library Data: Early Activity and Development
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Applications
Applications CSE 595 – Semantic Web Instructor: Dr. Paul Fodor Stony Brook University http://www3.cs.stonybrook.edu/~pfodor/courses/cse595.html GoodRelations BBC Artists BBC World Cup Website Lecture Outline Government Data New York Times Sig.ma and Sindice Swoogle OpenCalais Schema.org data.world Elsevier Audi Data Integration Swiss Life EnerSearch E-Learning Web Services Multimedia Collection Indexing at Scotland Yard Online Procurement at Daimler Device Interoperability at Nokia 2 Publication Management @ Semantic Web Primer GoodRelations E-commerce, and in particular Business-to-Consumer (B2C) e- commerce, has been one of the main drivers behind the rapid adoption of the World Wide Web in everyday live It is now commonplace to see URLs listed on storefronts and goods vehicles Taking the UK as an example, the B2C market has grown from £87 million in April 2000 to £68.4 billion by the end of 2009, a thousand-fold increase over a single decade USA 2017 B2C market was $660 billion, but the growth is decreasing 3 statista.com @ Semantic Web Primer GoodRelations E-commerce marketplace is suffering from all the deficits of the traditional web: E-commerce websites are typically generated from structured information systems, listing price, availability, type of product, delivery options, etc., but by the time this information reaches the company’s web pages, it has been turned into HTML and all machine-interpretable structure has disappeared, with the result that machines can no longer distinguish a price from a product-code -
A Comparative Evaluation of Geospatial Semantic Web Frameworks for Cultural Heritage
heritage Article A Comparative Evaluation of Geospatial Semantic Web Frameworks for Cultural Heritage Ikrom Nishanbaev 1,* , Erik Champion 1,2,3 and David A. McMeekin 4,5 1 School of Media, Creative Arts, and Social Inquiry, Curtin University, Perth, WA 6845, Australia; [email protected] 2 Honorary Research Professor, CDHR, Sir Roland Wilson Building, 120 McCoy Circuit, Acton 2601, Australia 3 Honorary Research Fellow, School of Social Sciences, FABLE, University of Western Australia, 35 Stirling Highway, Perth, WA 6907, Australia 4 School of Earth and Planetary Sciences, Curtin University, Perth, WA 6845, Australia; [email protected] 5 School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Perth, WA 6845, Australia * Correspondence: [email protected] Received: 14 July 2020; Accepted: 4 August 2020; Published: 12 August 2020 Abstract: Recently, many Resource Description Framework (RDF) data generation tools have been developed to convert geospatial and non-geospatial data into RDF data. Furthermore, there are several interlinking frameworks that find semantically equivalent geospatial resources in related RDF data sources. However, many existing Linked Open Data sources are currently sparsely interlinked. Also, many RDF generation and interlinking frameworks require a solid knowledge of Semantic Web and Geospatial Semantic Web concepts to successfully deploy them. This article comparatively evaluates features and functionality of the current state-of-the-art geospatial RDF generation tools and interlinking frameworks. This evaluation is specifically performed for cultural heritage researchers and professionals who have limited expertise in computer programming. Hence, a set of criteria has been defined to facilitate the selection of tools and frameworks. -
V a Lida T in G R D F Da
Series ISSN: 2160-4711 LABRA GAYO • ET AL GAYO LABRA Series Editors: Ying Ding, Indiana University Paul Groth, Elsevier Labs Validating RDF Data Jose Emilio Labra Gayo, University of Oviedo Eric Prud’hommeaux, W3C/MIT and Micelio Iovka Boneva, University of Lille Dimitris Kontokostas, University of Leipzig VALIDATING RDF DATA This book describes two technologies for RDF validation: Shape Expressions (ShEx) and Shapes Constraint Language (SHACL), the rationales for their designs, a comparison of the two, and some example applications. RDF and Linked Data have broad applicability across many fields, from aircraft manufacturing to zoology. Requirements for detecting bad data differ across communities, fields, and tasks, but nearly all involve some form of data validation. This book introduces data validation and describes its practical use in day-to-day data exchange. The Semantic Web offers a bold, new take on how to organize, distribute, index, and share data. Using Web addresses (URIs) as identifiers for data elements enables the construction of distributed databases on a global scale. Like the Web, the Semantic Web is heralded as an information revolution, and also like the Web, it is encumbered by data quality issues. The quality of Semantic Web data is compromised by the lack of resources for data curation, for maintenance, and for developing globally applicable data models. At the enterprise scale, these problems have conventional solutions. Master data management provides an enterprise-wide vocabulary, while constraint languages capture and enforce data structures. Filling a need long recognized by Semantic Web users, shapes languages provide models and vocabularies for expressing such structural constraints. -
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 -
Product Schema, SEO, Structured Data | Caliber Media Group & Schema.Org Products | Product Schema | SEO
ProductCamp: Product Schema, SEO, Structured Data | Caliber Media Group & Schema.org Products | Product Schema | SEO Caliber Media Group presented at Product Camp Southern California 2014, and Caliber also volunteered its services towards this conference’s success. Caliber Media Group ProductCamp: Product Schema, SEO, Structured Data | Caliber Media Group & Schema.org Products | Schema | Examples Resources | Tools | Readings 2 ProductCamp SoCal 2014 & Schema: Google, after Schema ProductCamp SoCal 2014 & Schema: Google via Disconnect & Yahoo, after Schema , ProductCamp SoCal 2014 & Schema: How did Caliber help ProductCamp beat all of the other events? ProductCamp SoCal 2014 & Schema: So what was inside the pages? ProductCamp SoCal 2014 & Schema: So what was inside the pages? ProductCamp SoCal 2014 & Schema: So what was inside the pages? Search => Schema, with JSON-LD Search & Schema: When & Who? Very short version… Martin Hepp http://www.heppnetz.de/projects/goodrelations/ ProductCamp SoCal 2014 & Schema: When & Who? Short version…here they come… ProductCamp SoCal 2014 & Schema: GoodRelations added… Search & Schema: Why, and… What does Schema do for me? http://www.schema.org ProductCamp SoCal 2014 & Schema: Product since this is ProductCamp http://schema.org/Product ProductCamp SoCal 2014 & Schema: An actual Product, since this is ProductCamp… ProductCamp SoCal 2014 & Schema: Recall, Products as Structured Data Structure -- Hierarchy -- Structured Data Search & Schema: Show me Schema examples… Schema: Product ontology | microdata | Knowledge Graph ProductCamp SoCal 2014 & Schema: Product ProductCamp SoCal 2014 & Schema: Google ProductCamp SoCal 2014 & Schema: Product Schema locally ProductCamp SoCal 2014 & Schema: Product locally ProductCamp SoCal 2014 & Schema: Local Schema gone wild… Search & Product Schema | Knowledge Graph from Google Knowledge Vault – where? Search & Product Schema | Knowledge Graph – where? Google Tables. -
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. -
The Application of Semantic Web Technologies to Content Analysis in Sociology
THEAPPLICATIONOFSEMANTICWEBTECHNOLOGIESTO CONTENTANALYSISINSOCIOLOGY MASTER THESIS tabea tietz Matrikelnummer: 749153 Faculty of Economics and Social Science University of Potsdam Erstgutachter: Alexander Knoth, M.A. Zweitgutachter: Prof. Dr. rer. nat. Harald Sack Potsdam, August 2018 Tabea Tietz: The Application of Semantic Web Technologies to Content Analysis in Soci- ology, , © August 2018 ABSTRACT In sociology, texts are understood as social phenomena and provide means to an- alyze social reality. Throughout the years, a broad range of techniques evolved to perform such analysis, qualitative and quantitative approaches as well as com- pletely manual analyses and computer-assisted methods. The development of the World Wide Web and social media as well as technical developments like optical character recognition and automated speech recognition contributed to the enor- mous increase of text available for analysis. This also led sociologists to rely more on computer-assisted approaches for their text analysis and included statistical Natural Language Processing (NLP) techniques. A variety of techniques, tools and use cases developed, which lack an overall uniform way of standardizing these approaches. Furthermore, this problem is coupled with a lack of standards for reporting studies with regards to text analysis in sociology. Semantic Web and Linked Data provide a variety of standards to represent information and knowl- edge. Numerous applications make use of these standards, including possibilities to publish data and to perform Named Entity Linking, a specific branch of NLP. This thesis attempts to discuss the question to which extend the standards and tools provided by the Semantic Web and Linked Data community may support computer-assisted text analysis in sociology. First, these said tools and standards will be briefly introduced and then applied to the use case of constitutional texts of the Netherlands from 1884 to 2016. -
Open Source Copyrights
Kuri App - Open Source Copyrights: 001_talker_listener-master_2015-03-02 ===================================== Source Code can be found at: https://github.com/awesomebytes/python_profiling_tutorial_with_ros 001_talker_listener-master_2016-03-22 ===================================== Source Code can be found at: https://github.com/ashfaqfarooqui/ROSTutorials acl_2.2.52-1_amd64.deb ====================== Licensed under GPL 2.0 License terms can be found at: http://savannah.nongnu.org/projects/acl/ acl_2.2.52-1_i386.deb ===================== Licensed under LGPL 2.1 License terms can be found at: http://metadata.ftp- master.debian.org/changelogs/main/a/acl/acl_2.2.51-8_copyright actionlib-1.11.2 ================ Licensed under BSD Source Code can be found at: https://github.com/ros/actionlib License terms can be found at: http://wiki.ros.org/actionlib actionlib-common-1.5.4 ====================== Licensed under BSD Source Code can be found at: https://github.com/ros-windows/actionlib License terms can be found at: http://wiki.ros.org/actionlib adduser_3.113+nmu3ubuntu3_all.deb ================================= Licensed under GPL 2.0 License terms can be found at: http://mirrors.kernel.org/ubuntu/pool/main/a/adduser/adduser_3.113+nmu3ubuntu3_all. deb alsa-base_1.0.25+dfsg-0ubuntu4_all.deb ====================================== Licensed under GPL 2.0 License terms can be found at: http://mirrors.kernel.org/ubuntu/pool/main/a/alsa- driver/alsa-base_1.0.25+dfsg-0ubuntu4_all.deb alsa-utils_1.0.27.2-1ubuntu2_amd64.deb ====================================== -
Nosql Databases
Query & Exploration SQL, Search, Cypher, … Stream Processing Platforms Data Storm, Spark, .. Data Ingestion Serving ETL, Distcp, Batch Processing Platforms BI, Cubes, Kafka, MapReduce, SparkSQL, BigQuery, Hive, Cypher, ... RDBMS, Key- OpenRefine, value Stores, … Data Definition Tableau, … SQL DDL, Avro, Protobuf, CSV Storage Systems HDFS, RDBMS, Column Stores, Graph Databases Computing Platforms Distributed Commodity, Clustered High-Performance, Single Node Query & Exploration SQL, Search, Cypher, … Stream Processing Platforms Data Storm, Spark, .. Data Ingestion Serving ETL, Distcp, Batch Processing Platforms BI, Cubes, Kafka, MapReduce, SparkSQL, BigQuery, Hive, Cypher, ... RDBMS, Key- OpenRefine, value Stores, … Data Definition Tableau, … SQL DDL, Avro, Protobuf, CSV Storage Systems HDFS, RDBMS, Column Stores, Graph Databases Computing Platforms Distributed Commodity, Clustered High-Performance, Single Node Computing Single Node Parallel Distributed Computing Computing Computing CPU GPU Grid Cluster Computing Computing A single node (usually multiple cores) Attached to a data store (Disc, SSD, …) One process with potentially multiple threads R: All processing is done on one computer BidMat: All processing is done on one computer with specialized HW Single Node In memory Retrieve/Stores from Disc Pros Simple to program and debug Cons Can only scale-up Does not deal with large data sets Single Node solution for large scale exploratory analysis Specialized HW and SW for efficient Matrix operations Elements: Data engine software for -
Rdfs:Frbr– Towards an Implementation Model for Library Catalogs Using Semantic Web Technology
rdfs:frbr– Towards an Implementation Model for Library Catalogs Using Semantic Web Technology Stefan Gradmann SUMMARY. The paper sets out from a few basic observations (biblio- graphic information is still mostly part of the ‘hidden Web,’ library au- tomation methods still have a low WWW-transparency, and take-up of FRBR has been rather slow) and continues taking a closer look at Se- mantic Web technology components. This results in a proposal for im- plementing FRBR as RDF-Schema and of RDF-based library catalogues built on such an approach. The contribution concludes with a discussion of selected strategic benefits resulting from such an approach. [Article copies available for a fee from The Haworth Document Delivery Service: 1-800-HAWORTH. E-mail address: <[email protected]> Web- site: <http://www.HaworthPress.com> © 2005 by The Haworth Press, Inc. All rights reserved.] Stefan Gradmann, PhD, is Head, Hamburg University “Virtual Campus Library” Unit, which is part of the computing center and has a mission of providing information management services to the university as a whole, including e-publication services and open access to electronic scientific information resources. Address correspondence to: Stefan Gradmann, Virtuelle Campusbibliothek Regionales Rechenzentrum der Universität Hamburg, Schlüterstrasse 70, D-20146 Hamburg, Germany (E-mail: [email protected]). [Haworth co-indexing entry note]: “rdfs:frbr–Towards an Implementation Model for Library Cata- logs Using Semantic Web Technology.” Gradmann, Stefan. Co-published simultaneously in Cataloging & Classification Quarterly (The Haworth Information Press, an imprint of The Haworth Press, Inc.) Vol. 39, No. 3/4, 2005, pp. 63-75; and: Functional Requirements for Bibliographic Records (FRBR): Hype or Cure-All? (ed: Patrick Le Boeuf) The Haworth Information Press, an imprint of The Haworth Press, Inc., 2005, pp. -
Introduction to Linked Data and Its Lifecycle on the Web
Introduction to Linked Data and its Lifecycle on the Web Sören Auer, Jens Lehmann, Axel-Cyrille Ngonga Ngomo, Amrapali Zaveri AKSW, Institut für Informatik, Universität Leipzig, Pf 100920, 04009 Leipzig {lastname}@informatik.uni-leipzig.de http://aksw.org Abstract. With Linked Data, a very pragmatic approach towards achieving the vision of the Semantic Web has gained some traction in the last years. The term Linked Data refers to a set of best practices for publishing and interlinking struc- tured data on the Web. While many standards, methods and technologies devel- oped within by the Semantic Web community are applicable for Linked Data, there are also a number of specific characteristics of Linked Data, which have to be considered. In this article we introduce the main concepts of Linked Data. We present an overview of the Linked Data lifecycle and discuss individual ap- proaches as well as the state-of-the-art with regard to extraction, authoring, link- ing, enrichment as well as quality of Linked Data. We conclude the chapter with a discussion of issues, limitations and further research and development challenges of Linked Data. This article is an updated version of a similar lecture given at Reasoning Web Summer School 2011. 1 Introduction One of the biggest challenges in the area of intelligent information management is the exploitation of the Web as a platform for data and information integration as well as for search and querying. Just as we publish unstructured textual information on the Web as HTML pages and search such information by using keyword-based search engines, we are already able to easily publish structured information, reliably interlink this informa- tion with other data published on the Web and search the resulting data space by using more expressive querying beyond simple keyword searches. -
Easybuild Documentation Release 20210907.0
EasyBuild Documentation Release 20210907.0 Ghent University Tue, 07 Sep 2021 08:55:41 Contents 1 What is EasyBuild? 3 2 Concepts and terminology 5 2.1 EasyBuild framework..........................................5 2.2 Easyblocks................................................6 2.3 Toolchains................................................7 2.3.1 system toolchain.......................................7 2.3.2 dummy toolchain (DEPRECATED) ..............................7 2.3.3 Common toolchains.......................................7 2.4 Easyconfig files..............................................7 2.5 Extensions................................................8 3 Typical workflow example: building and installing WRF9 3.1 Searching for available easyconfigs files.................................9 3.2 Getting an overview of planned installations.............................. 10 3.3 Installing a software stack........................................ 11 4 Getting started 13 4.1 Installing EasyBuild........................................... 13 4.1.1 Requirements.......................................... 14 4.1.2 Using pip to Install EasyBuild................................. 14 4.1.3 Installing EasyBuild with EasyBuild.............................. 17 4.1.4 Dependencies.......................................... 19 4.1.5 Sources............................................. 21 4.1.6 In case of installation issues. .................................. 22 4.2 Configuring EasyBuild.......................................... 22 4.2.1 Supported configuration