Uses available resources for named entity recognition, extraction, and reconciliation. – Linked Data for Professional Education

Open Refine 101

Fri, 25 Aug 2017 08:34:44 +0000

This free online course explains that while data cleaning, preparation and enrichment take up an enormous amount of time, and is nevertheless a crucial stage in the data science methodology. However, data transformation tools haven’t fully caught up with the popularity of data analysis. Learn why domain experts need powerful yet easy-to-use interfaces to explore new data sets, normalize them and process them via innovative services often available via an API only. The instructor demonstrates the strengths of OpenRefine, which are that it offers a self-service agile and iterative interface for data discovery and preparation, as well as an easy-to-learn scripting language.

URL: https://cognitiveclass.ai/courses/introduction-to-openrefine/
Keywords: Google Refine, General Refine Expression Language (GREL), Data enrichment, Data cleansing
Author: Magdinier, Martin
Publisher: Cognitive Class
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P7H
Educational use: instruction
Educational audience: teacher-educationSpecialist
Interactivity type: mixed

<sameAs>: interlinking the Web of Data

Fri, 21 Jul 2017 07:20:23 +0000

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

Free Your Metadata: Named entity extraction

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

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

Free Your Metadata: Reconcile your metadata

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

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

Joining the Linked Data Cloud in a Cost-Effective Manner

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

Linked Data holds the promise to derive additional value from existing data throughout different sectors, but practitioners currently lack a straightforward methodology and the tools to experiment with Linked Data. This article gives a pragmatic overview of how general purpose Interactive Data Transformation tools (IDTs) can be used to perform the two essential steps to bring data into the Linked Data cloud: data cleaning and reconciliation. These steps are explained with the help of freely available data (Cooper-Hewitt National Design Museum, New York) and tools (Google Refine), making the process repeatable and understandable for practitioners.

URL: http://dx.doi.org/10.3789/isqv24n2-3.2012.04
Keywords: Linked Open Data (LOD), Data cleaning, Atomization, Clustering, Data reconciliation
Author: Van de Walle, Rik
Publisher: ISQ (Information Standards Quarterly)
Date created: 2012-05-01 04:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P10M
Educational use: instruction
Educational audience: professional
Interactivity type: expositive

Linked Data for Libraries, Archives and Museums: How to clean, link and publish your metadata

Mon, 22 May 2017 07:03:30 +0000

This handbook teaches how to unlock the value of existing metadata through cleaning, reconciliation, enrichment and linking, as well as how to streamline the process of new metadata creation. It introduces the key concepts related to metadata standards and Linked Data and how they can be practically applied to existing metadata. Chapters are dedicated to modeling, cleaning, reconciling, enriching, and publishing one's data.

URL: http://book.freeyourmetadata.org/
Keywords: Libraries, Archives, and Museums (LAMs), Linked Open Data (LOD), HTTP URIs, Controlled vocabulary, Simple Knowledge Organization System (SKOS), Semantic Web
Author: Verborgh, Ruben
Publisher: Facet Publishing
Date created: 2014-06-19 04:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P5H
Educational use: professionalDevelopment
Educational audience: teacher-educationSpecialist
Interactivity type: mixed

Linking Lives: Creating an End-User Interface Using Linked Data

Mon, 22 May 2017 07:03:30 +0000

This article describes how LOCAH, a JISC-funded project working to make data from the Archives Hub available as Linked Data, continued on in a new form as "Linking Lives". Biographical data is presented on pages which are populated entirely by Linked Data from various authoritative sources (e.g., VIAF, DBpedia). One challenge faced involved data collection via the application' server vs client's web browse. Another was whether to reconcile of multiple source URIs via creation and persistence of a new URI or to map multiple URIs using the "owl:sameAs property".

URL: http://www.niso.org/publications/isq/2012/v24no2-3/stevenson/
Keywords: Linked Open Data (LOD), Libraries, Archives, and Museums (LAMs), HTTP URIs
Author: Stevenson, Jane
Publisher: ISQ (Information Standards Quarterly)
Date created: 2012-05-01 04:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P20M
Educational use: instruction
Educational audience: professional
Interactivity type: expositive

Linked Data: The World is Your Database

Wed, 08 Mar 2017 06:53:17 +0000

This PDF contains slides used at a talk given at KMWorld 2016. It begins by introducing the basic principles of Linked Data and the advantages of adopting it. This is followed by a brief overview of how the RDF data model and its serializations work and suggestions on how to get started.

URL: http://www.greenchameleon.com/uploads/KWM_Clarke_Loh_LOD_20161115_pub_lr.pdf
Keywords: HTTP URIs, Taxonomy, Controlled Vocabulary, Semantic enrichment
Author: Clarke, Dave
Publisher: Synaptica
Date created: 2016-11-01 04:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P20M
Educational use: instruction
Educational audience: student
Interactivity type: expositive

Make Your Thesaurus Smart

Wed, 21 Dec 2016 06:43:13 +0000

This video explains how Linked Open Data (LOD) concepts can be used in conjunction with your thesaurus to create dynamic web pages, offer relevant content from other sources, add value to research portals, and transform the Internet into a giant database for satisfying queries. A use case is presented which centers around the use of DBpedia's Spotlight tool for annotating mentions of DBpedia resources in Natural Language text, providing capabilities useful for Named Entity Recognition, Name Resolution, and other information extraction tasks.

URL: https://www.youtube.com/watch?v=dSJeLl11M5g
Keywords: Named Entity Recognition (NER), Natural language, DBpedia, Spotlight
Author: Vasicek, Dan
Publisher: Access Innovations
Date created: 2015-06-03 04:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P40M
Educational use: professionalDevelopment
Educational audience: professional
Interactivity type: expositive

Mining the Web of Linked Data with RapidMiner

Sat, 16 Jan 2016 13:43:29 +0000

Lots of data from different domains is published as Linked Open Data. While there are quite a few browsers for that data, as well as intelligent tools for particular purposes, a versatile tool for deriving additional knowledge by mining the Web of Linked Data is still missing. In this challenge entry, we introduce the RapidMiner Linked Open Data extension. The extension hooks into the powerful data mining platform RapidMiner, and offers operators for accessing Linked Open Data in RapidMiner, allowing for using it in sophisticated data analysis workflows without the need to know SPARQL or RDF. As an example, we show how statistical data on scientific publications, published as an RDF data cube, can be linked to further datasets and analyzed using additional background knowledge from various LOD datasets.

URL: http://videolectures.net/iswc2014_paulheim_rapidminer/
Keywords: RapidMiner, Data Mining, Linked Open Data, Scalability, Predictive analytics
Author: Ristoski, Petar
Date created: 2014-12-19 05:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P15M