Introduction To The Principles Of Linked Open Data

Key Info
Description - a brief synopsis, abstract or summary of what the learning resource is about: 

This lesson offers a brief and concise introduction to Linked Open Data (LOD). No prior knowledge is assumed. Readers should gain a clear understanding of the concepts behind linked open data, how it is used, and how it is created. The tutorial is split into five parts, plus further reading:
-Linked open data: what is it?
-The role of the Uniform Resource Identifier (URI)
-How LOD organizes knowledge: ontologies
-The Resource Description Framework (RDF) and data formats
-Querying linked open data with SPARQL
-Further reading and resources
The tutorial should take a couple of hours to complete, and you may find it helpful to re-read sections to solidify your understanding. Technical terms have been linked to their corresponding page on Wikipedia, and you are encouraged to pause and read about terms that you find challenging. After having learned some of the key principles of LOD, the best way to improve and solidify that knowledge is to practice. This tutorial provides opportunities to do so. By the end of the course, you should understand the basics of LOD, including key terms and concepts.
In order to provide readers with a solid grounding in the basic principles of LOD, this tutorial will not be able to offer comprehensive coverage of all LOD concepts. The following two LOD concepts will not be the focus of this lesson:
-The semantic web and semantic reasoning of datasets. A semantic reasoner would deduce that George VI is the brother or half-brother of Edward VIII, given the fact that a) Edward VIII is the son of George V and b) George VI is the son of George V. This tutorial does not focus on this type of task.
-Creating and uploading linked open datasets to the linked data cloud. Sharing your LOD is an important principle, which is encouraged below. However, the practicalities of contributing your LOD to the linked data cloud are beyond the scope of this lesson. Some resources that can help you get started with this task are available at the end of this tutorial.

This tutorial is also available in Spanish at:  https://programminghistorian.org/es/lecciones/introduccion-datos-abiertos-enlazados

Authoring Person(s) Name: 
Jonathan Blaney
Authoring Organization(s) Name: 
The Programming Historian
License - link to legal statement specifying the copyright status of the learning resource: 
Creative Commons Attribution 4.0 International - CC BY 4.0
Access Cost: 
No fee
Citation - format of the preferred citation for the learning resource: 
Jonathan Blaney, "Introduction to the Principles of Linked Open Data," The Programming Historian 6 (2017), https://doi.org/10.46430/phen0068.
Primary language(s) in which the learning resource was originally published or made available: 
English
Also available in - other languages in which the learning resource has been translated or made available other than the primary: 
Spanish
More info about
Keywords - short phrases describing what the learning resource is about: 
Data access methods
Data coding
Data formats
Data modeling
Digital humanities
Humanities data
Linked data
Network analysis
Open data
Subject Discipline - subject domain(s) toward which the learning resource is targeted: 
Arts and Humanities
Published / Broadcast: 
Sunday, May 7, 2017
ID - identifier that provides the means to locate the learning resource or its citation: 
10.46430/phen0068
Type - namespace prefix for the citable locator, if any: 
DOI
Publisher - organization credited with publishing or broadcasting the learning resource: 
The Programming Historian
Media Type - designation of the form in which the content of the learning resource is represented, e.g., moving image: 
Interactive Resource - requires a user to take action or make a request in order for the content to be understood, executed or experienced.
Educational Info
Purpose - primary educational reason for which the learning resource was created: 
Instruction - detailed information about aspects or processes related to data management or data skills.
Learning Resource Type - category of the learning resource from the point of view of a professional educator: 
Learning Activity - guided or unguided activity engaged in by a learner to acquire skills, concepts, or knowledge that may or may not be defined by a lesson. Examples: data exercises, data recipes.
Target Audience - intended audience for which the learning resource was created: 
Citizen scientist
Data professional
Early-career research scientist
Graduate student
Librarian
Mid-career research scientist
Research faculty
Research scientist
Undergraduate student
Intended time to complete - approximate amount of time the average student will take to complete the learning resource: 
More than 1 hour (but less than 1 day)