active – Linked Data for Professional Education https://ld4pe.dublincore.org Learning resources tagged by competency Thu, 19 Nov 2020 14:45:03 +0000 en-US hourly 1 https://wordpress.org/?v=4.9.16 Level Up: Online CSV to RDF Converter (Beta) https://ld4pe.dublincore.org/learning_resource/level-up-online-csv-to-rdf-converter-beta/ Fri, 18 Aug 2017 08:22:56 +0000 https://ld4pe.dublincore.org/learning_resource/level-up-online-csv-to-rdf-converter-beta/ This online converter for CSV files was created for the many people out there who are big supporters of "Open Data" but are uncomfortable with getting that data into a format that can be used for Linked Data (regardless of whether it was open or not). Whilst many are happy with saving tabular data as CSV files, a surprising amount are still fairly mystified by saving that same data in RDF format. For more information about "Why RDF?", "What's Linked Open Data?" and similar questions – please have a read of the FAQ; this page concentrates on how to use the converter options to tweak the RDF output. The final step is to simply download a zip file of the converted CSV. The zip file includes the data in three formats – RDF, Turtle (.ttl) and N-Triples (.nt).

URL: http://levelup.networkedplanet.com/instructions
Keywords: CSV (Comma Separated Values)
Publisher: NetwrokedPlanet
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P15M
Educational use: professionalDevelopment
Interactivity type: active

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Converting Relational Data Into RDF Format https://ld4pe.dublincore.org/learning_resource/converting-relational-data-into-rdf-format/ Tue, 08 Aug 2017 08:07:57 +0000 https://ld4pe.dublincore.org/learning_resource/converting-relational-data-into-rdf-format/ This tutorial shows two different methods of converting or materializing relational data into RDF graph data format: the D2RQ based method and the SQL based method. The D2RQ based method provides customizable mapping files that allow users to specify the generation of URIs, enabling the reuse of URIs across different columns, tables, schemas, or even databases. URI reuse here means using the same URI to represent the same resource. The SQL-based approach, as provided in this tutorial, does not handle escapes, character encoding, new lines, tabs, and other special characters.

URL: http://www.oracle.com/webfolder/technetwork/tutorials/obe/db/11g/r1/prod/datamgmt/relational_into_rdf/relational_data_into_rdf_format_otn.htm
Keywords: D2RQ Mapping Language, SQL (Structured Query Language), N-Triples, N3
Publisher: Oracle
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P1H
Educational use: instruction
Educational audience: professional
Interactivity type: active

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Structured Data Linter https://ld4pe.dublincore.org/learning_resource/structured-data-linter/ Fri, 21 Jul 2017 07:20:23 +0000 https://ld4pe.dublincore.org/learning_resource/structured-data-linter/ The Structured Data Linter is a tool aiding webmasters and web developers to verify the structured data present in their HTML pages. Search engines use structured data to understand webpages more accurately and to present enhanced search results. Linter understands microdata, JSON-LD and RDFa formats according to their latest specifications.
In addition to providing snippet visualizations for schema.org, Linter performs limited vocabulary validations for schema.org, Dublin Core Metadata Terms, Friend of a Friend (FOAF), GoodRelations, Facebook's Open Graph Protocol, Semantically-Interlinked Online Communities (SIOC), Facebook's Open Graph Protocol, Simple Knowledge Organization System (SKOS), and Data-Vocabulary.org.

URL: http://linter.structured-data.org/
Keywords: Rich snippets, RDFa, Microdata, Validation, Schema.org
Author: Kellogg, Gregg
Publisher: Structured Data Initiative
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P15M
Educational use: professionalDevelopment
Educational audience: professional
Interactivity type: active

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<sameAs>: interlinking the Web of Data https://ld4pe.dublincore.org/learning_resource/interlinking-the-web-of-data/ Fri, 21 Jul 2017 07:20:23 +0000 https://ld4pe.dublincore.org/learning_resource/interlinking-the-web-of-data/ The Web of Data has many equivalent URIs. This service helps you to find co-references between different data sets. The main store includes referents from DBpedia, VIAF, the British Library, and other authoritative sources. There are also links to many smaller sameAs stores that are being populated and used by projects and people. The latter are entirely independent from the main sameAs store, although some of the data may also be reflected in the main sameAs store..

URL: http://sameas.org/
Keywords: Web Ontology Language (OWL), HTTP URIs
Author: Glasser, Hugh
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P15M
Educational use: instruction
Educational audience: student
Interactivity type: active

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Free Your Metadata: Named entity extraction https://ld4pe.dublincore.org/learning_resource/free-your-metadata-named-entity-extraction/ Tue, 23 May 2017 07:03:37 +0000 https://ld4pe.dublincore.org/learning_resource/free-your-metadata-named-entity-extraction/ A brief tutorial explaining how to enrich a dataset even when many fields (notoriously description) contain unstructured text. To capture this potentially interesting information in machine-processable format, named entity recognition can be used via an extension to Open Refine (formerly Google Refine). This tutorial builds on two previous ones which explain how to clean and reconcile
an example dataset (from the Powerhouse Museum) to a specific controlled vocabulary (in the example, the Library of Congress Subject Headings). The textual walk-through demonstrates how to install the extension, open a new project, and perform the extraction of named entities.

URL: http://freeyourmetadata.org/named-entity-extraction/
Keywords: Open Refine, Google Refine, Named-entity extraction
Author: Verborgh, Ruben
Publisher: MaSTIC
Date created: 2016-01-01 05:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P20M
Interactivity type: active

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Free Your Metadata: Reconcile your metadata https://ld4pe.dublincore.org/learning_resource/free-your-metadata-reconcile-your-metadata/ Tue, 23 May 2017 07:03:37 +0000 https://ld4pe.dublincore.org/learning_resource/free-your-metadata-reconcile-your-metadata/ A brief tutorial showing how to reconcile an example dataset (from the Powerhouse Museum) to a specific controlled vocabulary (in the example, the Library of Congress Subject Headings) using Open Refine (formerly Google Refine). Reconciliation is about giving meaning to record values, making your metadata interpretable by the whole wide world. The walk-through demonstrates this iterative process by explaining how to: Choose a reconciliation service and install the proper RDF extension; Interpret the results of each reconciliation attempt; Refine and re-run the reconciliation process; Obtain the reconciled URLs necessary to link your metadata to the controlled vocabulary. Links to the sample data files and the tool itself are provided. Instructions are in text; screencast is "coming soon".

URL: http://freeyourmetadata.org/reconciliation/
Keywords: Open Refine, Google Refine, General Refine Expression Language (GREL), Data reconciliation
Author: Verborgh, Ruben
Publisher: MaSTIC
Date created: 2016-01-01 05:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P1H
Interactivity type: active

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Free Your Metadata: Clean up your metadata https://ld4pe.dublincore.org/learning_resource/free-your-metadata-clean-up-your-metadata/ Tue, 23 May 2017 07:03:37 +0000 https://ld4pe.dublincore.org/learning_resource/free-your-metadata-clean-up-your-metadata/ A brief tutorial containing both a screencast and text instructions for cleaning an example dataset (from the Powerhouse Museum) using Open Refine (formerly Google Refine). The walk-through includes the following steps: 1) Loading the data; 2) Inspecting the data; 3) Removing blank rows; 4) Removing duplicate rows; 5) Splitting cells with multiple values; 6) Removing blanks cells; 7) Clustering values; 8) Removing double category values. Links to the sample data files and the tool itself are provided.

URL: http://freeyourmetadata.org/cleanup/
Keywords: Open Refine, Google Refine, General Refine Expression Language (GREL), Data cleaning
Author: Verborgh, Ruben
Publisher: MaSTIC
Date created: 2016-01-01 05:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P1H
Interactivity type: active

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The Semantic Web and Linked Data Concepts: A Basic Overview Quiz 1A https://ld4pe.dublincore.org/learning_resource/the-semantic-web-and-linked-data-concepts-a-basic-overview-quiz-1a/ Fri, 19 May 2017 07:03:11 +0000 https://ld4pe.dublincore.org/learning_resource/the-semantic-web-and-linked-data-concepts-a-basic-overview-quiz-1a/ This quiz covers material presented in the first module of the BIBFRAME pilot training project at the Library of Congress. The quiz consists of ten multiple choice questions with the answers explained in popups after the user has made their selection. Topics covered include the role of semantically linked data in creating useful web services and connecting datasets on the web.

URL: https://www.loc.gov/catworkshop/bibframe/Training/part1a/index.htm
Keywords: Semantic Web, Linked Data
Publisher: Library of Congress
Date created: 2015-08-01 04:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P5M
Educational use: instruction
Educational audience: teacher-educationSpecialist
Interactivity type: active

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The Semantic Web and Linked Data Concepts: A Basic Overview Quiz 1B https://ld4pe.dublincore.org/learning_resource/the-semantic-web-and-linked-data-concepts-a-basic-overview-quiz-1b/ Fri, 19 May 2017 07:03:11 +0000 https://ld4pe.dublincore.org/learning_resource/the-semantic-web-and-linked-data-concepts-a-basic-overview-quiz-1b/ This quiz covers material presented in the first module of the BIBFRAME pilot training project at the Library of Congress. The quiz consists of five multiple choice questions with the answers explained in popups after the user has made their selection. Topics covered include the limits of the current MARC based environment contrasted with the promise of integrating data more fully with Semantic Web resources to enhance user services.

URL: https://www.loc.gov/catworkshop/bibframe/Training/part1b/index.htm
Keywords: Semantic Web, MARC (MAchine-Readable Cataloging), BIBFRAME
Publisher: Library of Congress
Date created: 2015-08-01 04:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P5M
Educational use: instruction
Educational audience: teacher-educationSpecialist
Interactivity type: active

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The Semantic Web and Linked Data Concepts: The RDF Data Model and Linked Open Data (LOD) Quiz https://ld4pe.dublincore.org/learning_resource/the-semantic-web-and-linked-data-concepts-the-rdf-data-model-and-linked-open-data-lod-quiz/ Fri, 19 May 2017 07:03:10 +0000 https://ld4pe.dublincore.org/learning_resource/the-semantic-web-and-linked-data-concepts-the-rdf-data-model-and-linked-open-data-lod-quiz/ This quiz covers material presented in the first module of the BIBFRAME pilot training project at the Library of Congress. The quiz consists of five multiple choice questions with the answers explained in popups after the user has made their selection. Questions address possible misconceptions regarding Linked Data principles and Linked Open Data (LOD), as well as the role of the RDF data model, triple statements, and vocabularies within the Semantic Web.

URL: https://www.loc.gov/catworkshop/bibframe/Training/part2/index.htm
Keywords: Linked Data, Semantic Web, HTTP URIs
Publisher: Library of Congress
Date created: 2015-08-01 04:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P5M
Educational use: professionalDevelopment
Educational audience: student
Interactivity type: active

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