expositive – Linked Data for Professional Education

Validating RDF Data

Fri, 15 Sep 2017 09:45:50 +0000

This book describes two languages for implementing constraints on RDF data, describing the main features of both Shape Expressions (ShEx) and Shapes Constraints Language (SHACL) from a user perspective, and also offering a comparison of the technologies. The authors develop a small number of examples that typify validation requirements and demonstrate how they can be met with ShEx and SHACL. The book is not intended to be a formal specification of the languages, for which the interested reader can consult the corresponding reference documents, but rather, it is meant to serve as an introduction to the technologies with some background about the rationale of their design and some points of comparison.

URL: http://www.morganclaypoolpublishers.com/catalog_Orig/product_info.php?products_id=1091
Keywords: Shape Expressions (ShEx), Shapes Constraints Language (SHACL), Data validation
Author: Kontokostas, Dimitris
Publisher: Morgan & Claypool Publishers
Date created: 2017-08-01 04:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P8H
Educational use: instruction
Educational audience: teacher-educationSpecialist
Interactivity type: expositive

Generating RDF from Tabular Data on the Web

Fri, 18 Aug 2017 08:22:56 +0000

This document defines the procedures and rules to be applied when converting tabular data into RDF. Tabular data may be complemented with metadata annotations that describe its structure, the meaning of its content and how it may form part of a collection of interrelated tabular data. This document specifies the effect of this metadata on the resulting RDF. This is a draft document and may be updated, replaced or obsoleted by other documents at any time. It is inappropriate to cite this document as other than work in progress.

URL: http://w3c.github.io/csvw/csv2rdf/
Keywords: CSV (Comma Separated Values)
Author: Kellogg, Gregg
Publisher: W3C
Date created: 2017-06-07 04:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P20M
Interactivity type: expositive

Linked Statistical Data Analysis

Sun, 13 Aug 2017 08:18:11 +0000

Linked Data design principles are increasingly employed to publish and consume high-fidelity, heterogeneous statistical datasets in a distributed fashion. While vast amounts of linked statistics are available, access and reuse of the data is subject to expertise in corresponding technologies. There exists no user-centered interfaces for researchers, journalists and interested people to compare statistical data retrieved from different sources on the Web. Given that the RDF Data Cube vocabulary is used to describe statistical data, its use makes it possible to discover and identify statistical data artifacts in a uniform way. In this article, the design and implementation of a user-centric application and service is presented. Behind the scene, the platform utilizes federated SPARQL queries to gather statistical data from distributed data stores. The R language for statistical computing is employed to perform statistical analyses and visualizations. The Shiny application and server bridges the front-end Web user interface with R on the server-side in order to compare statistical macrodata, and stores analyses results in RDF for future research. As a result, distributed linked statistics with accompanying provenance data can be more easily explored and analysed by interested parties.

URL: http://csarven.ca/linked-statistical-data-analysis
Keywords: Data analysis, R (programming language), Shiny server, Apache Jena, Federated queries
Author: Riedl, Reinhard
Publisher: CEUR (Central Europe Workshop Proceedings)
Date created: 2013-07-07 04:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P1H
Educational use: professionalDevelopment
Educational audience: professional
Interactivity type: expositive

Don’t Use a Hammer to Screw in a Nail: Alternatives to REGEX in SPARQL

Sun, 13 Aug 2017 08:18:11 +0000

This brief blog post explains that regular expressions are expensive to evaluate regardless of what language you are using them in. The author suggests that if you can avoid using a regular expression in favor of a simpler string computation, then you can likely get much better performance out of your SPARQL engine. Alternative strategies include using CONTAINS, LCASE, UCASE, STRSTARTS, and STRENDS. If more complex string operations are required, full-text extensions to the SPARQL engine may be an option.

URL: http://www.cray.com/blog/dont-use-hammer-screw-nail-alternatives-regex-sparql/
Keywords: SPARQL, CONTAINS, String operations, REGEX, Jena Text
Author: Vesse, Rob
Publisher: Cray
Date created: 2014-06-03 04:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P10M
Educational use: instruction
Educational audience: student
Interactivity type: expositive

Equality and Inequality in SPARQL

Sun, 13 Aug 2017 08:18:11 +0000

This brief blog post discusses issues surrounding expression semantics in SPARQL. Practices that people are used to from other languages (like the use of "=" and "!="), can often be confusing to new – and even not so new- SPARQL developers. The author suggests that an awareness of type errors will allow the user to understand what is occurring. Example queries show how type errors are treated when using FILTER. An alternative method involving project expressions or BIND is proposed.

URL: http://www.cray.com/blog/equality-inequality-sparql/
Keywords: SPARQL, BIND, FILTER, Type errors, Project expressions
Author: Vesse, Rob
Publisher: Cray
Date created: 2013-04-23 04:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P10M
Educational use: instruction
Educational audience: student
Interactivity type: expositive

Transforming the Medical Subject Headings into Linked Data: a new article in the Journal of Library Metadata

Tue, 08 Aug 2017 08:07:57 +0000

This article reviews the pilot project to convert the Medical Subject Headings (MeSH) from XML to Linked Data/RDF. The article examines the collaborative process, the technical and organizational issues tackled, and the future of Linked Data at the National Library of Medicine.

URL: http://aims.fao.org/activity/blog/transforming-medical-subject-headings-linked-data-new-article-journal-library-metadata
Keywords: Medical Subject Headings (MeSH), Semantic Web, LAMs (Libraries, Archives, and Museums)
Publisher: AIMS (Agricultural Information Management Standards)
Date created: 2016-02-11 05:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P10M
Educational audience: teacher-educationSpecialist
Interactivity type: expositive

Maximising (Re)Usability of Library Metadata Using Linked Data

Sun, 06 Aug 2017 07:58:04 +0000

In this video, the speaker explores challenges related to the re-usability of library linked metadata in the field of cultural heritage- and for other purposes. She argues that it is crucial that published Linked Data accurately represent core aspects of the original metadata related to language, provenance, license, and dataset metadata. The speaker proposes a "proper representation" of these features using W3C standards, best practices and guidelines for multilingual Linked Open Data.

URL: https://www.youtube.com/watch?v=IIDXZ-wj4Vs
Keywords: Libraries, Archives, and Museums (LAMs), Lemon (Lexicon Model for Ontologies), Linguistic Linked Open Data, VoID (Vocabulary of Interlinked Datasets), BabelNet
Author: Pérez, Asunción Gómez
Publisher: Technical University of Madrid
Date created: 2015-12-11 05:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P1H
Educational use: professionalDevelopment
Educational audience: student
Interactivity type: expositive

SKOS and Linked Data

Sun, 06 Aug 2017 07:58:04 +0000

This slideshare presentation introduces SKOS and explains how it can be used to represent RDF in a simple way. It explains how SKOS differs from OWL a more formal system of semantics. Along the way, basic Linked Data Principles are explained. Includes links to references and demos, which explain the benefits of using SKOS as well as areas that need to be developed further.

URL: https://www.slideshare.net/antoineisaac/skos-and-linked-data
Keywords: SKOS (Simple Knowledge Organization System), KOS (Knowledge Organization System), Thesaurus, Labels
Author: Isaac, Antoine
Publisher: Europeana
Date created: 2010-09-14 04:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P20M
Educational use: professionalDevelopment
Educational audience: student
Interactivity type: expositive

Semantic Web Misconceptions

Sat, 22 Jul 2017 07:21:14 +0000

The Semantic Web has been talked about for more than a decade. Over those years, several mistaken or misleading ideas about the Semantic Web have repeatedly popped up. This lessons looks at some of the most pervasive of these misconceptions and discusses both the confusion and the reality of the situation.

URL: http://www.cambridgesemantics.com/semantic-university/semantic-web-misconceptions
Keywords: Semantic Web, Artificial Intelligence (AI), Natural Language Processing (NLP), Ontologies
Publisher: Cambridge Semantics
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P10M
Educational use: instruction
Educational audience: student
Interactivity type: expositive

Library Linked Data Incubator Group: Datasets, Value Vocabularies, and Metadata Element Sets

Tue, 23 May 2017 07:03:37 +0000

This report on datasets, value vocabularies and metadata elements sets is a complement to the main report of the Library Linked Data Incubator Group. It contains a set of useful resources for creating or consuming Linked Data in the library domain. In particular, it lists numerous resources for discovering existing Liked Data datasets and RDF vocabularies for reuse. It is intended both for novices seeking an overview of Linked Data focusing on the library domain, and for experts in search of a quick look-up or refresher.

URL: https://www.w3.org/2005/Incubator/lld/XGR-lld-vocabdataset-20111025/
Keywords: Vocabulary, Ontology, Data Hub, Dataset, RDF, Libraries, Archives, and Museums (LAMs), Linked Open Data (LOD)
Author: Zeng, Marcia
Publisher: W3C
Date created: 2011-10-25 04:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P1H
Educational use: professionalDevelopment
Educational audience: student
Interactivity type: expositive