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2021-03-28 09:29:20
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IT & Software Other IT & Software Graph Databases

RDF and SPARQL Essentials

A practical introduction to RDF, Turtle, TriG and SPARQL for authoring and querying knowledge graph data
Hot & New
Rating: 4.8 out of 54.8 (8 ratings)
2,323 students
Created by Tish Chungoora
Last updated 4/2021
English
English
30-Day Money-Back Guarantee

What you'll learn

  • Knowledge graph technologies that are revolutionising the way we store and query data at scale
  • Author RDF data and perform Create, Read, Update and Delete (CRUD) operations using the SPARQL query language
  • Comfortably speak RDF and SPARQL and use the jargon in technical conversations with stakeholders
  • Acquire a rock-solid foundation for taking on more advanced training in semantic approaches such as RDFS and OWL

Requirements

  • Analytical background with basic mathematical skills
  • Prior exposure to data analysis, e.g. tabular data in Excel, SQL or no-SQL technologies
  • [Optional] Basic understanding of knowledge graphs
  • [Optional] A pre-installed RDF graph database

Description

Want to get hands-on with the hottest trends in data representation and data architecture? Want to learn the building blocks of how organisations across various sectors like IT, Manufacturing, Mass Media, Financial Services, Pharmaceutical and many more, are tearing down data silos to build self-descriptive datasets and drive next-level AI and analytics?

You've landed at the right spot! This course is about the Resource Description Framework or RDF for short, and SPARQL, which are two fundamental layers of the Semantic Web Stack for building knowledge graphs. Knowledge graphs are essentially datasets that are richly described and explicitly linked as networks. RDF is a simple data model for capturing these rich networks, and SPARQL is the query language for interrogating knowledge graphs that are expressed in RDF format.

While we are in the Information Age and technologies like relational databases (e.g. SQL) are old but not obsolete, and surely here to stay for many more years to come, organisations are quickly realising that their datasets need to be weaved together efficiently within the data value stream. This requires us to capture and describe data as networks and building a consolidated picture of our data resources, enabling us to answer key business questions more smartly, intuitively and at scale.

In this course, you'll learn how to work with RDF and SPARQL from a practical perspective. We're going to roll up our sleeves and dive into authoring RDF graphs in the Turtle and TriG formats, which are common human-friendly text formats for writing RDF data. We're going spend a great deal of time working with SPARQL and there will be loads of useful examples and problems we'll go through and solve along the way.

This course is for people who care about the future of data representation, data architecture and data engineering.

Who this course is for:

  • Data professionals curious about knowledge graph technologies that are based on RDF and SPARQL
  • Professionals who are at the start of their journey in using Semantic Web technologies
  • Aspiring knowledge graph architects

Course content

9 sections • 91 lectures • 1h 50m total length

  • Preview01:56
  • Preview01:12
  • Preview01:49
  • Preview00:35

  • RDF graph at a glance
    01:20
  • RDF triples
    01:19
  • Types of nodes in RDF
    01:40
  • RDF basics
    5 questions

  • Getting started
    02:42
  • [Activity] Getting started
    00:09
  • Running the graph database
    01:31
  • [Activity] Running the graph database
    00:11
  • Default IRI and writing RDF triples involving literal values
    04:46
  • Writing triples involving RDF type
    02:14
  • Completing the RDF triples for Bugs Bunny
    02:25
  • Who said Cecil Turtle? It's just Turtle
    01:06
  • [Activity] Write outgoing triples for Bugs_Bunny, Tex_Avery and A_Wild_Hare
    00:19
  • Preview02:04
  • [Activity] Write outgoing triples for Daffy_Duck and Porkys_Duck_Hunt
    00:17
  • [Activity] Triples for Sylvester and Taz, their creators and debut appearances
    00:18
  • Loading the Looney Tunes dataset into the RDF database
    00:59
  • [Activity] Load the dataset
    00:13

  • Basic query pattern
    03:04
  • Slicing results using LIMIT modifier
    01:11
  • [Activity] Basic graph pattern
    00:07
  • One (bunny's) hop away query pattern
    01:22
  • Who's Bugs Bunny's creator?
    00:28
  • What are Bugs Bunny's personality traits?
    00:32
  • [Activity] Sylvester's personality traits
    00:03
  • Two (bunny's) hop away query pattern
    02:43
  • [Activity] Birth dates of the creators of Taz
    00:06
  • Writing lean queries
    02:17
  • [Activity] Looney Tunes characters, their creators and their birth dates
    00:06
  • Counting things in the graph - sorry no money-splitting gag!
    01:56
  • [Activity] Count of number of Looney Tunes characters
    00:04
  • Removing duplicates in query results
    02:22
  • [Activity] Count of distinct types of creators
    00:05
  • Checking for existence of specific patterns - catch the one with no catchphrase!
    02:02
  • [Activity] Names of Looney Tunes characters with existing catchphrase
    00:07
  • List the characters who were co-created
    02:07
  • Preview01:44
  • How old was Tex Avery when he died?
    02:36
  • [Activity] Lifespan of each Looney Tunes character creator
    00:08
  • Who was the longest living character creator?
    01:22
  • Averaging age values of Looney Tunes character creators
    00:57
  • Running tests: More advanced use of BIND, with IF
    03:12
  • Running tests: More advanced use of BIND, with COALESCE and IF
    01:41
  • [Activity] Testing birth year values of Looney Tunes character creators
    00:26
  • Catchphrase mania: Working with OPTIONAL matches
    01:34
  • [Activity] Catchphrase mania
    00:08
  • Including results from solving two graph patterns: The UNION clause
    01:51
  • [Activity] List all the date values present in the graph
    00:21
  • Excluding results using the MINUS clause
    01:29
  • Counting and grouping the number of personality traits for each character
    01:26
  • [Activity] Count of creators per Looney Tunes character
    00:08
  • I am who I am: The DESCRIBE query
    02:38
  • [Activity] Outgoing and incoming RDF triples for Sylvester
    00:05
  • Truth or hare: The ASK query
    00:46
  • [Activity] Is "Isadore Frelang" Sylvester's creator's name?
    00:06
  • What’s CONSTRUCT, Doc?
    01:49
  • What’s CONSTRUCT, Doc? (ctd.)
    01:49
  • [Activity] Sub-graph of Looney Tunes characters and their debut release year
    00:08

  • Preview01:06
  • Inverse paths
    01:08
  • Sequence paths
    01:20
  • [Activity] The rabbit hole
    00:11
  • Recursive paths
    01:54
  • Recursive paths (ctd.)
    00:41
  • Listing possible paths
    03:46
  • [Activity] Joining the dots between Sylvester and Taz
    00:10

  • Inserting specific triples
    01:28
  • Deleting specific triples
    00:36
  • Inserting data based on graph patterns
    02:27
  • [Activity] Declaring reciprocal (i.e. symmetric) predicates
    00:11
  • The enemy of my rival could join forces with me: SPARQL INSERT (ctd.)
    01:17
  • [Activity] The enemy of my rival could join forces with me
    00:13
  • Deleting data based on graph patterns
    01:33

  • Overview
    01:12
  • Creating named graphs
    01:44
  • Querying a named graph
    01:22
  • [Activity] Graph me up!
    00:28
  • Dropping a named graph
    00:41
  • [Activity] Drop the graph!
    00:03

  • Overview
    00:47
  • What are the types of things in the graph?
    01:42
  • What are the predicates defined in the graph?
    00:36
  • What is the full vocabulary for the graph?
    02:14
  • [Activity] Graph vocabulary
    00:09

  • Summary
    02:24
  • Wrap-up
    02:11
  • Bonus: What's next?
    00:22
  • Acknowledgements and more
    00:36

Instructor

Tish Chungoora
Ph.D. | CSPO
Tish Chungoora
  • 4.3 Instructor Rating
  • 4,987 Reviews
  • 26,523 Students
  • 9 Courses

I am a seasoned technology consultant with a passion for empowering people to apply best-in-class tools and techniques for professional development. My key experience is in knowledge graph technologies, product management, business analysis and technical publications.

I have a Ph.D. in systems & knowledge engineering and an extensive background in product design engineering. My innovative works in these areas have featured in over a dozen articles published in leading journals and conferences.

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